diff --git "a/data/lauzhack-2024/lauzhack_github_repo_metadata.json" "b/data/lauzhack-2024/lauzhack_github_repo_metadata.json" new file mode 100644--- /dev/null +++ "b/data/lauzhack-2024/lauzhack_github_repo_metadata.json" @@ -0,0 +1,8807 @@ +{ + "https://github.com/4cademy/I.R.I.S._LauzHack_2024": { + "commit_count_default_branch": 41, + "contributors_count": 4, + "contributors_top": [ + { + "contributions": 24, + "html_url": "https://github.com/4cademy", + "login": "4cademy" + }, + { + "contributions": 11, + "html_url": "https://github.com/mehdi533", + "login": "mehdi533" + }, + { + "contributions": 4, + "html_url": "https://github.com/CHUKLA", + "login": "CHUKLA" + }, + { + "contributions": 2, + "html_url": "https://github.com/GKrafft2", + "login": "GKrafft2" + } + ], + "created_at": "2024-11-30T13:21:59Z", + "default_branch": "main", + "description": "Our project for the Vitol challenge at LauzHack 2024 in Lausanne", + "dirs_total_count": 1, + "files_root_entries": [ + { + "path": ".DS_Store", + "size": 6148, + "type": "file" + }, + { + "path": ".env", + "size": 79, + "type": "file" + }, + { + "path": ".gitignore", + "size": 141, + "type": "file" + }, + { + "path": "README.md", + "size": 851, + "type": "file" + }, + { + "path": "app.py", + "size": 12168, + "type": "file" + }, + { + "path": "chatbot.py", + "size": 5318, + "type": "file" + }, + { + "path": "frankfurt-germany-may-2-2023-260nw-2350806495.webp", + "size": 14826, + "type": "file" + }, + { + "path": "images", + "size": 0, + "type": "dir" + }, + { + "path": "images_matching.py", + "size": 4126, + "type": "file" + }, + { + "path": "prompts.py", + "size": 21586, + "type": "file" + }, + { + "path": "requirements.txt", + "size": 2972, + "type": "file" + }, + { + "path": "segmentation.py", + "size": 6711, + "type": "file" + }, + { + "path": "vision.py", + "size": 5373, + "type": "file" + } + ], + "files_total_count": 13, + "first_commit_date_default_branch": "2024-11-30T13:33:53Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 55282 + } + ], + "last_commit_date_default_branch": "2024-12-01T22:25:01Z", + "last_commit_oid_default_branch": "24793bc99278d6e0c0c79dde4991ce940b83c465", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "4cademy/IRIS", + "owner": "4cademy", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_5e47f0fdc1ad8070", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T22:25:01Z", + "readme_length": 849, + "readme_text": "# IRIS - Intelligent Recognition & Image Search\n\n## Demo Video\n\n[![IMAGE ALT TEXT HERE](https://img.youtube.com/vi/z9r4e49M3I4/0.jpg)](https://www.youtube.com/watch?v=z9r4e49M3I4)\n\n## Prerequisites\n```\ngit clone https://github.com/4cademy/I.R.I.S._LauzHack_2024.git repo\ncd repo\ntouch .env\n```\n- Create an API-KEY for SerpApi here: https://serpapi.com/manage-api-key\n- Past it into the created `.env` file like this: `SEARCH_API_KEY=your_api_key_here`\n\n```bash\nexport AWS_DEFAULT_REGION=\"us-west-2\"\nexport AWS_ACCESS_KEY_ID=\"your_aws_access_key_id\"\nexport AWS_SECRET_ACCESS_KEY=\"your_aws_secret_access_key\"\nexport AWS_SESSION_TOKEN=\"your_aws_session_token\"\nexport OPENAI_API_KEY=\"your_openai_api_key\"\n```\n## Installation\n```bash\npip install -r requirements.txt\npython app.py\n```\n\nGo to the URL shown in the console (normally: http://127.0.0.1:7860/)", + "readme_title": "IRIS - Intelligent Recognition & Image Search", + "releases_count": 0, + "repo": "I.R.I.S._LauzHack_2024", + "repo_name": "IRIS", + "stars": 2, + "topics": [], + "updated_at": "2024-12-15T22:55:06Z", + "url": "https://github.com/4cademy/IRIS", + "watchers": 1 + }, + "https://github.com/AmirMFarhang/LauzHack-CassadagApp": { + "commit_count_default_branch": 12, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 6, + "html_url": "https://github.com/keitaVigano", + "login": "keitaVigano" + }, + { + "contributions": 5, + "html_url": "https://github.com/saraborello", + "login": "saraborello" + }, + { + "contributions": 1, + "html_url": "https://github.com/AmirMFarhang", + "login": "AmirMFarhang" + } + ], + "created_at": "2024-11-30T17:43:22Z", + "default_branch": "main", + "description": "A platform for forcasting information based on historical information with AI collaboration and specific medical interpolation, which consider all kind of market aspects for biochemical compounds from sales to side effects, helpful to analyze products with historical info or newly made synthetic apps", + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 3169, + "type": "file" + }, + { + "path": "README.md", + "size": 327, + "type": "file" + }, + { + "path": "bristor_analisys.ipynb", + "size": 544297, + "type": "file" + }, + { + "path": "bristor_modeling.py", + "size": 3936, + "type": "file" + }, + { + "path": "elbonia_analisys.ipynb", + "size": 314782, + "type": "file" + }, + { + "path": "elbonia_modeling.py", + "size": 4392, + "type": "file" + }, + { + "path": "fiore_analisys.ipynb", + "size": 588641, + "type": "file" + }, + { + "path": "flore_modeling.py", + "size": 3984, + "type": "file" + } + ], + "files_total_count": 8, + "first_commit_date_default_branch": "2024-11-30T17:43:22Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 1447720 + }, + { + "language": "Python", + "size": 12312 + } + ], + "last_commit_date_default_branch": "2024-12-06T09:47:19Z", + "last_commit_oid_default_branch": "16fca6073154f318dcf398a29dfcf1a15e35a2cf", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "AmirMFarhang/LauzHack-CassadagApp", + "owner": "AmirMFarhang", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_d1147dc6d583822d", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 1, + "pull_requests_total": 1, + "pushed_at": "2024-12-09T22:46:13Z", + "readme_length": 324, + "readme_text": "# LauzHack-CassadagApp\nA platform for forcasting information based on historical information with AI collaboration and specific medical interpolation, which consider all kind of market aspects for biochemical compounds from sales to side effects, helpful to analyze products with historical info or newly made synthetic apps", + "readme_title": "LauzHack-CassadagApp", + "releases_count": 0, + "repo": "LauzHack-CassadagApp", + "repo_name": "LauzHack-CassadagApp", + "stars": 0, + "topics": [], + "updated_at": "2024-12-06T09:47:28Z", + "url": "https://github.com/AmirMFarhang/LauzHack-CassadagApp", + "watchers": 2 + }, + "https://github.com/AndreaIannoli/JuicyBank": { + "commit_count_default_branch": 9, + "contributors_count": 2, + "contributors_top": [ + { + "contributions": 6, + "html_url": "https://github.com/giammirove", + "login": "giammirove" + }, + { + "contributions": 3, + "html_url": "https://github.com/AndreaIannoli", + "login": "AndreaIannoli" + } + ], + "created_at": "2024-11-30T13:06:30Z", + "default_branch": "main", + "description": "The repo for the UBS LauzHack's challenge", + "dirs_total_count": 1, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 3139, + "type": "file" + }, + { + "path": "LICENSE", + "size": 1070, + "type": "file" + }, + { + "path": "README.md", + "size": 283, + "type": "file" + }, + { + "path": "scripts", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 6, + "first_commit_date_default_branch": "2024-11-30T13:06:30Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": true, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 26814 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:45:26Z", + "last_commit_oid_default_branch": "d1b84652411bc50ab6083e91bca878f7c035f7bb", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": "MIT License", + "license_spdx": "MIT", + "name_with_owner": "AndreaIannoli/JuicyBank", + "owner": "AndreaIannoli", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_0e715080c82c5020", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:45:38Z", + "readme_length": 282, + "readme_text": "# JuicyBank\nThe repo for the UBS LauzHack's challenge\n\nGianmaria Rovelli - gianmaria.rovelli@epfl.ch\nDaniele Cacciapaglia - cacciapagliadaniele8@gmail.com\nAndrea Iannoli - andrea.iannoli01@gmail.com\nAndreea Scrob - andreea.scrob@studio.unibo.it\n\nKaggle Team Name : `succo di frutta`", + "readme_title": "JuicyBank", + "releases_count": 0, + "repo": "JuicyBank", + "repo_name": "JuicyBank", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T13:23:53Z", + "url": "https://github.com/AndreaIannoli/JuicyBank", + "watchers": 1 + }, + "https://github.com/Bimo99B9/UBS-Lauzhack-Entity-Resolution": { + "commit_count_default_branch": 51, + "contributors_count": 5, + "contributors_top": [ + { + "contributions": 23, + "html_url": "https://github.com/Bimo99B9", + "login": "Bimo99B9" + }, + { + "contributions": 18, + "html_url": "https://github.com/CarlOwOs", + "login": "CarlOwOs" + }, + { + "contributions": 7, + "html_url": "https://github.com/tranhuonglan", + "login": "tranhuonglan" + }, + { + "contributions": 2, + "html_url": "https://github.com/MarioRicoIbanez", + "login": "MarioRicoIbanez" + }, + { + "contributions": 1, + "html_url": null, + "login": "Carlos Hurtado Comin" + } + ], + "created_at": "2024-11-30T12:41:24Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 3, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 3211, + "type": "file" + }, + { + "path": "README.md", + "size": 3964, + "type": "file" + }, + { + "path": "assets", + "size": 0, + "type": "dir" + }, + { + "path": "blocking_utils", + "size": 0, + "type": "dir" + }, + { + "path": "demo.ipynb", + "size": 126554, + "type": "file" + }, + { + "path": "inference.py", + "size": 13524, + "type": "file" + }, + { + "path": "main.py", + "size": 17679, + "type": "file" + }, + { + "path": "preprocess.py", + "size": 2419, + "type": "file" + }, + { + "path": "preprocessing_utils", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 12, + "first_commit_date_default_branch": "2024-11-30T12:41:25Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 126554 + }, + { + "language": "Python", + "size": 50205 + } + ], + "last_commit_date_default_branch": "2024-12-01T11:19:31Z", + "last_commit_oid_default_branch": "55326ce296ea446fafd1a8816f71674af1e1ff98", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "Bimo99B9/UBS-Lauzhack-Entity-Resolution", + "owner": "Bimo99B9", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_8a3b16e1f52e2c25", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T11:19:34Z", + "readme_length": 3959, + "readme_text": "# UBS Entity Resolution - Lauzhack 2024\n## Dignity Team\n\n- Daniel López Gala - daniel.lopezgala@epfl.ch \n- Carlos Hurtado - carloshurtadocomin@gmail.com \n- Mario Rico Ibáñez - mario.ricoibanez@epfl.ch\n- Tran Huong Lan - tranhuonglantk@gmail.com\n\nKaggle Team Name: *Dignity*\n\n![](assets/dignity.jpg)\n\n---\n\nThis project focuses on resolving financial entities by leveraging Local Sensitive Hashing (LSH) to efficiently identify and match similar non-UBS entities in transaction records. It is tailored for the financial industry, where precision and scalability are very important.\n\n## Key Features\n\n### Linear Models for Financial Entity Matching\nThe system uses LSH for blocking and similarity-based feature engineering, making it linear in terms of complexity:\n- **Scalability**: LSH reduces the number of pairwise comparisons, enabling linear performance relative to data size.\n- **Robustness**: Features like phonetic encoding (Soundex, Metaphone, NYSIIS), company detection, and custom similarity metrics make the model highly adaptable to diverse financial datasets.\n\nThese methods ensure quick and accurate matching, making the approach ideal for financial transactions where entity resolution needs to be precise, scalable, and interpretable.\n\n### Workflow\n1. **Preprocessing** \n - Standardizes input datasets by normalizing names, addresses, and phone numbers.\n - Maps categorical variables into numerical formats.\n\n2. **Feature Engineering** \n - Extracts and encodes phonetic features for entity matching.\n - Identifies companies using keyword-based detection.\n - Splits names into \"given_name\" and \"surname,\" enabling nuanced comparisons.\n\n3. **LSH for Blocking** \n - Employs LSH to group similar entities into buckets, reducing the number of comparisons needed.\n\n4. **Similarity Scoring** \n - Combines phonetic encoding, string similarity (Jaro-Winkler), and attribute weighting for fine-grained matching.\n\n5. **Evaluation** \n - Measures performance using precision, recall, and F1-score.\n\n## Models Used\n### Local Sensitive Hashing (LSH)\n- **Blocking**: Groups entities based on attributes like names, addresses, and phone numbers using n-grams and MinHash.\n- **Efficiency**: Significantly reduces computational costs by limiting comparisons to similar buckets.\n\n### Phonetic Encodings\n- **Soundex, Metaphone, NYSIIS**: Improve matching accuracy for noisy and diverse name datasets.\n- **Adaptability**: Handles variations in spelling and cultural differences in entity names.\n\n### String Similarity\n- **Jaro-Winkler Distance**: Computes robust similarity scores for attributes like names and phone numbers.\n- **Attribute Weighting**: Prioritizes key attributes (e.g., IBAN, surname) to align with financial data resolution requirements.\n\n## Preprocessing Steps\n- Lowercase normalization and removal of special characters.\n- Title stripping for names (e.g., \"Dr.\", \"Mr.\").\n- Standardized phone numbers.\n\n## How to Run\n1. Place input files in the `data/` directory:\n - `account_booking_train.csv`\n - `external_parties_train.csv`\n - `account_booking_test.csv`\n - `external_parties_test.csv`\n\n2. Run the main script:\n ```bash\n python main.py\n ```\n\n3. Processed files will be saved in the `data/processed/` directory, including:\n - `external_parties_train.csv`\n - `submission.csv`\n\n## Evaluation Metrics\n- **Precision**: Proportion of correctly identified pairs.\n- **Recall**: Coverage of true matches.\n- **F1-Score**: Harmonizes precision and recall.\n\n## Why This Approach Works for Financial Entity Matching\n- **Linear Scalability**: Handles large datasets efficiently, crucial for financial systems with millions of transactions.\n- **Domain-Specific Features**: Incorporates financial-specific attributes (e.g., IBAN, company detection).\n- **Accuracy**: Combines blocking, similarity, and phonetic features to minimize false positives and negatives.\n\n---\n\nCreated by the **Dignity** team for the Lauzhack 2024!", + "readme_title": "UBS Entity Resolution - Lauzhack 2024", + "releases_count": 0, + "repo": "UBS-Lauzhack-Entity-Resolution", + "repo_name": "UBS-Lauzhack-Entity-Resolution", + "stars": 3, + "topics": [], + "updated_at": "2025-10-09T10:38:24Z", + "url": "https://github.com/Bimo99B9/UBS-Lauzhack-Entity-Resolution", + "watchers": 1 + }, + "https://github.com/BrunoManzano/LauzHack": { + "commit_count_default_branch": 27, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 17, + "html_url": "https://github.com/BrunoManzano", + "login": "BrunoManzano" + }, + { + "contributions": 8, + "html_url": "https://github.com/martioms01", + "login": "martioms01" + }, + { + "contributions": 2, + "html_url": "https://github.com/iv97n", + "login": "iv97n" + } + ], + "created_at": "2024-11-30T11:43:41Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 10, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 3139, + "type": "file" + }, + { + "path": "README.md", + "size": 11, + "type": "file" + }, + { + "path": "app", + "size": 0, + "type": "dir" + }, + { + "path": "data", + "size": 0, + "type": "dir" + }, + { + "path": "notebooks", + "size": 0, + "type": "dir" + }, + { + "path": "run.py", + "size": 124, + "type": "file" + }, + { + "path": "static", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 29, + "first_commit_date_default_branch": "2024-11-30T11:43:41Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 4087734 + }, + { + "language": "Python", + "size": 21853 + }, + { + "language": "HTML", + "size": 9353 + }, + { + "language": "CSS", + "size": 865 + } + ], + "last_commit_date_default_branch": "2024-12-01T11:00:55Z", + "last_commit_oid_default_branch": "9c22afc003258b5400cd4be93b20dc7cc8f5ea33", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "BrunoManzano/LauzHack", + "owner": "BrunoManzano", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_0132035b1863d3fb", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T11:01:04Z", + "readme_length": 10, + "readme_text": "# LauzHack", + "readme_title": "LauzHack", + "releases_count": 0, + "repo": "LauzHack", + "repo_name": "LauzHack", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T11:04:48Z", + "url": "https://github.com/BrunoManzano/LauzHack", + "watchers": 1 + }, + "https://github.com/CS-433/ml-project-2-natural-stupidity": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'CS-433/ml-project-2-natural-stupidity'.\"}]", + "owner": "CS-433", + "project_foreign_key": "lhp_3eb85ab259f043f0", + "repo": "ml-project-2-natural-stupidity" + }, + "https://github.com/Corentin00/sf": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'Corentin00/sf'.\"}]", + "owner": "Corentin00", + "project_foreign_key": "lhp_7e31365dcc603f03", + "repo": "sf" + }, + "https://github.com/D0men1c0/LauzHack": { + "commit_count_default_branch": 58, + "contributors_count": 4, + "contributors_top": [ + { + "contributions": 38, + "html_url": "https://github.com/Tonio635", + "login": "Tonio635" + }, + { + "contributions": 9, + "html_url": "https://github.com/bralani", + "login": "bralani" + }, + { + "contributions": 9, + "html_url": "https://github.com/D0men1c0", + "login": "D0men1c0" + }, + { + "contributions": 2, + "html_url": "https://github.com/DevIos01", + "login": "DevIos01" + } + ], + "created_at": "2024-11-30T16:48:48Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 70, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 41, + "type": "file" + }, + { + "path": "LICENSE", + "size": 1065, + "type": "file" + }, + { + "path": "NLP.ipynb", + "size": 1716644, + "type": "file" + }, + { + "path": "NLP.py", + "size": 9801, + "type": "file" + }, + { + "path": "README.md", + "size": 9009, + "type": "file" + }, + { + "path": "VisonAI - Mobile Application", + "size": 0, + "type": "dir" + }, + { + "path": "src", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 166, + "first_commit_date_default_branch": "2024-11-30T19:52:09Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": true, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 1716644 + }, + { + "language": "Python", + "size": 46061 + }, + { + "language": "Dart", + "size": 24808 + }, + { + "language": "C++", + "size": 24562 + }, + { + "language": "CMake", + "size": 19513 + }, + { + "language": "Ruby", + "size": 2803 + }, + { + "language": "Swift", + "size": 2043 + }, + { + "language": "C", + "size": 1425 + }, + { + "language": "HTML", + "size": 1224 + }, + { + "language": "Dockerfile", + "size": 477 + } + ], + "last_commit_date_default_branch": "2024-12-03T20:46:25Z", + "last_commit_oid_default_branch": "f4d11f4d3dfbe3badbf8e24b2078f7b4988cbd8b", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": "MIT License", + "license_spdx": "MIT", + "name_with_owner": "D0men1c0/LauzHack", + "owner": "D0men1c0", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_0423752768297ae5", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-03T20:46:35Z", + "readme_length": 9004, + "readme_text": "# VisionAI Assistant\n\n**VisionAI Assistant** is a mobile application designed to analyze and interpret visual content using advanced artificial intelligence technologies. Users can upload images and video and interact with the system via natural language inputs, whether through text or voice commands. The application processes these inputs to provide comprehensive insights, including object detection, segmentation, and the extraction of specific attributes from images.\n\nThis project was developed during the **Lauz Hack** hackathon at EPFL in just **22 hours**, with a team of four people collaborating on distinct fields to parallelize the work. The roles were divided as follows:\n- **NLP Specialist**: Focused on natural language query understanding and feature extraction.\n- **Computer Vision Engineer**: Developed the segmentation pipeline and integrated it with the SAM model.\n- **Frontend Developer**: Built the Flutter-based user interface to handle multi-modal input and display results.\n- **Backend and Cloud Developer**: Deployed and hosted the system on **AWS EC2**, ensuring stable and scalable performance. Additionally, managed the Flask server to facilitate seamless communication between the models and the frontend.\n\nGiven the tight timeframe, this architecture demonstrates the team's efficiency in integrating state-of-the-art AI models into a functional and scalable system. However, there is significant potential for future improvements.\n\n---\n\n## Architecture Overview\n\nThe application architecture is composed of several key components:\n\n### **Frontend**\n- Built using **Flutter**, enabling cross-platform interface. \n- The frontend supports multiple modes of interaction, allowing users to provide inputs via:\n - Text\n - Voice recordings\n - Directly uploaded images (video support is planned for future improvements).\n\n### **Backend**\n- Developed with **Flask**, a lightweight Python-based web framework.\n- Manages:\n - Communication between the user interface and the AI models.\n - Image processing and segmentation tasks.\n - Query analysis and result presentation.\n\n### **Hosting**\n- The Flask server and all AI models are deployed on an **AWS EC2 instance**, ensuring scalability and reliable performance.\n\n### **Natural Language Understanding**\n- We used **SBERT (Sentence-BERT)** to process the user's natural language query. SBERT identifies the main object or feature to analyze into complex input (e.g., \"cars\" in the query *\"Hey, could you tell me how many red trucks with certain size are at the center of the image?\"*).\n- The similarity-based approach allows the system to match the query against predefined classes like \"cars,\" \"boats,\" \"trees\", or \"people.\"\n\n### **Computer Vision Model**\n- Image segmentation is performed using **Meta's Segment Anything Model (SAM 2)**, which processes the image based on instructions derived from the user's query. \n- SAM is combined with **natural language prompts**, improving its capability to segment objects or regions of interest directly from the text input. \n - GitHub Repo: [lang-segment-anything](https://github.com/luca-medeiros/lang-segment-anything)\n\n### **Prompt Processing and Feature Extraction**\n- After the **SAM model** segments the image, it outputs bounding boxes representing each detected segment. These bounding boxes, along with their coordinates, are stored in a dataset. \n- Our system computes and populates additional features for each segment (e.g., color, size, position) through feature engineering based on the raw segmentation data. \n- **ChatGPT (GPT-4o)** is then used to interpret the user's natural language prompt and execute code that filters the dataset to extract relevant results:\n - For example:\n - Query: *\"How many red ships are in this picture?\"*\n - Workflow:\n 1. The precomputed dataset contains attributes for each segment (`Object: Boat`, `Color: Red`, `Size`, `Area`, `Coordinate`, etc.).\n 2. GPT parses the user's query, identifies the relevant features (e.g., `Object: Boat`, `Color: Red`), and writes code to filter the dataset accordingly.\n 3. The filtered dataset is analyzed to calculate the result (e.g., \"4 red boats\").\n 4. The application visually highlights only the bounding boxes that match the query, overlaying them on the image.\n- This process leverages GPT to execute automated filtering and analysis while ensuring precision through precomputed features in the dataset.\n\n---\n\n## Workflow in Detail\n\n1. **User Input**\n - The user interacts with the app using natural language, either through text or voice. Example:\n > *\"Hi, can you segment all the red cars in the center of this image that are around 3 meters in size?\"*\n - If input is provided via voice, the **Whisper** speech-to-text model converts the recording into text.\n\n2. **Query Understanding**\n - The text input is processed by **SBERT**, which matches the query to predefined categories or classes. For instance:\n - Query: *\"red cars in the center\"*\n - Identified class: *\"Car\"*\n\n3. **Image Segmentation**\n - The **SAM 2 model** receives the image and the segmented class (e.g., *\"cars\"*).\n - SAM segments all objects of the identified class and outputs bounding boxes for each detected segment.\n\n4. **Dataset Creation and Feature Engineering**\n - The bounding boxes from SAM are used to create a dataset, with each segment annotated with attributes such as:\n - **Color**: Detected through pixel-level analysis of the segment.\n - **Size**: Computed based on the dimensions of the bounding box.\n - **Position**: Derived from the coordinates of the bounding box within the image.\n - This dataset forms the foundation for all subsequent analysis.\n\n5. **Query Refinement and Filtering**\n - The natural language query, along with the dataset, is passed to **ChatGPT (GPT-4o)**. \n - GPT interprets the query and generates code to filter the dataset based on the requested features. For example:\n - Query: *\"How many red trucks are in this image?\"*\n - GPT writes and executes code to:\n 1. Filter segments where `Object = Truck` and `Color = Red`.\n 2. Count the filtered segments.\n - This automated process ensures the dataset is refined to match the user’s request.\n\n6. **Output Presentation**\n - The filtered dataset is used to generate the final visual output.\n - Relevant segments are highlighted directly on the image (e.g., bounding boxes around red trucks).\n - The results (e.g., \"4 red trucks\") are displayed in the app’s user interface, along with the annotated image.\n\n---\n\n\n## Advantages of VisionAI Assistant\n\n### **Enhanced Query Capabilities**\nUnlike general-purpose multimodal models (e.g., ChatGPT with basic image input), VisionAI Assistant allows users to make complex queries about specific image features. Examples include:\n- Counting objects of a specific type (e.g., *\"How many blue cars are in the parking lot?\"*).\n- Filtering objects by attributes like size, position, or color.\n\n### **Modular and Scalable Design**\nBy separating natural language processing, image segmentation, and feature extraction into distinct modules, the system is:\n- Easier to maintain and upgrade.\n- Scalable for more complex use cases, such as video analysis or real-time segmentation.\n\n### **Custom Feature Engineering**\nThe use of an intermediate dataset for feature engineering allows for advanced queries. For example:\n- *\"Which cars are red, larger than 3 meters, and located on the left side of the image?\"*\n- Such queries are processed efficiently using our feature engineering pipeline.\n\n---\n\n## Limitations and Future Improvements\n\n### **Current Limitations**\n- **Video Processing**: Currently, only image processing is supported due to the computational limits of the hosting server. Video support requires a stronger virtual machine for faster inference.\n- **Prompt Engineering**: While effective, further improvements in prompt refinement could enhance model accuracy and relevance.\n\n### **Future Enhancements**\n1. **Scalable Infrastructure**: Upgrading the hosting environment to handle high-throughput tasks like video processing.\n2. **Expanded Feature Set**: Adding more attributes (e.g., material type, motion patterns for video) to the dataset for richer analysis.\n3. **Interactive Query Refinement**: Allowing users to iteratively refine their queries based on intermediate results.\n\n---\n\n### **Conclusion**\n\nVisionAI Assistant demonstrates the potential of integrating advanced AI models with intuitive interfaces to tackle complex visual analysis tasks efficiently. Despite being developed in only **22 hours**, the system achieves a high level of functionality and modularity. The collaborative effort of specialists in NLP, Computer Vision, Backend Development, and Cloud Engineering highlights the power of parallelized teamwork. While the project shows great promise, there are clear opportunities for enhancement, particularly in scalability and feature richness.", + "readme_title": "VisionAI Assistant", + "releases_count": 0, + "repo": "LauzHack", + "repo_name": "LauzHack", + "stars": 3, + "topics": [], + "updated_at": "2025-04-30T21:45:38Z", + "url": "https://github.com/D0men1c0/LauzHack", + "watchers": 1 + }, + "https://github.com/Dylan-vrl/AnimInk": { + "commit_count_default_branch": 4, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 4, + "html_url": "https://github.com/dyvrl", + "login": "dyvrl" + } + ], + "created_at": "2024-12-01T10:07:33Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 338, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 1327, + "type": "file" + }, + { + "path": "Assets", + "size": 0, + "type": "dir" + }, + { + "path": "LICENSE.txt", + "size": 1064, + "type": "file" + }, + { + "path": "Packages", + "size": 0, + "type": "dir" + }, + { + "path": "ProjectSettings", + "size": 0, + "type": "dir" + }, + { + "path": "README.md", + "size": 1677, + "type": "file" + }, + { + "path": "RuntimeActionBindings.json", + "size": 1790, + "type": "file" + } + ], + "files_total_count": 2344, + "first_commit_date_default_branch": "2024-12-01T10:07:25Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": true, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "C#", + "size": 3586317 + }, + { + "language": "ShaderLab", + "size": 85491 + }, + { + "language": "JavaScript", + "size": 33707 + }, + { + "language": "Objective-C++", + "size": 27504 + }, + { + "language": "Mathematica", + "size": 15479 + }, + { + "language": "HLSL", + "size": 13994 + }, + { + "language": "Objective-C", + "size": 1156 + }, + { + "language": "C", + "size": 1118 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:26:01Z", + "last_commit_oid_default_branch": "28ca562fc2b41d0f87f025ef840c6119e832cdee", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": "MIT License", + "license_spdx": "MIT", + "name_with_owner": "dyvrl/AnimInk", + "owner": "Dylan-vrl", + "parent_repo": null, + "parent_url": null, + "primary_language": "C#", + "project_foreign_key": "lhp_3ab888624307ad9b", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:26:04Z", + "readme_length": 1676, + "readme_text": "# AnimInk\n\nAnimInk s an innovative VR application that enables users to collaborate in real-time by interacting with shared 3D models and draw annotations thanks to the MX Ink stylus. \nDesigned for creative and interactive experiences, the app leverages the Meta XR SDK for immersive VR functionality and Fusion 2 for seamless multiplayer networking.\n\nIt has been primarily designed for 3D animators. Using VR to quickly prototype the poses of your animations allows the animator to get a better perspective over their\n3D model. The stylus provides a precise interaction with the mesh and allows for an efficiient collaboration thanks to annotations.\n\n## Features\n- Real-Time Collaboration: Multiple users can interact with the same 3D environment simultaneously.\n- MX Ink Stylus Integration: Use the stylus for all interactions, including:\n - Grabbing IK Targets: Move targets to manipulate models and match specific poses.\n - Drawing: Create 3D sketches in the VR space.\n\n## Requirements\n\n- Meta Quest 2, 3 or 3S\n- MX Ink stylus\n- Unity 2022.3.X\n- Meta XR SDK (pre-installed)\n- Fusion 2 (pre-configured)\n\n## Get started:\n- Download this repo and open it in Unity\n- Set Up Fusion 2:\n - Ensure you have an active Fusion 2 account.\n - Configure the Photon settings with your app's unique ID in the Fusion Dashboard.\n- Build the game\n- Upload the apk to your headset (which is paired to the stylus)\n\n## Usage\n- The front button is used to grab objects in range. Blue boxes are all grabbable.\n- The middle button is used to draw.\n- Alternately, tip can be used to draw\n- Click on the back button to confirm your drawing. You can then move it using the newly created blue box.", + "readme_title": "AnimInk", + "releases_count": 0, + "repo": "AnimInk", + "repo_name": "AnimInk", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T10:26:08Z", + "url": "https://github.com/dyvrl/AnimInk", + "watchers": 1 + }, + "https://github.com/EPFL-Fresk/fresk-backend": { + "commit_count_default_branch": 3, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 3, + "html_url": "https://github.com/paultisaw", + "login": "paultisaw" + } + ], + "created_at": "2024-11-30T22:32:00Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 8, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 310, + "type": "file" + }, + { + "path": "README.md", + "size": 338, + "type": "file" + }, + { + "path": "add_fnr.sh", + "size": 113, + "type": "file" + }, + { + "path": "application.conf", + "size": 368, + "type": "file" + }, + { + "path": "build.sbt", + "size": 1084, + "type": "file" + }, + { + "path": "db_data", + "size": 0, + "type": "dir" + }, + { + "path": "docker-compose.yml", + "size": 634, + "type": "file" + }, + { + "path": "fixnreplace.json", + "size": 1884, + "type": "file" + }, + { + "path": "get_assosciations.sh", + "size": 40, + "type": "file" + }, + { + "path": "project", + "size": 0, + "type": "dir" + }, + { + "path": "publish.sh", + "size": 260, + "type": "file" + }, + { + "path": "src", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 16, + "first_commit_date_default_branch": "2024-11-30T22:34:11Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": true, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 1, + "issues_total": 1, + "languages_top": [ + { + "language": "Scala", + "size": 16199 + }, + { + "language": "Shell", + "size": 413 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:58:02Z", + "last_commit_oid_default_branch": "619f2325f2b8bd8aad733aef179509bfd79e1cb3", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "EPFL-Fresk/fresk-backend", + "owner": "EPFL-Fresk", + "parent_repo": null, + "parent_url": null, + "primary_language": "Scala", + "project_foreign_key": "lhp_fcb726875a7ea5f4", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:58:09Z", + "readme_length": 337, + "readme_text": "## sbt project compiled with Scala 3\n\n### Usage\n\nThis is a normal sbt project. You can compile code with `sbt compile`, run it with `sbt run`, and `sbt console` will start a Scala 3 REPL.\n\nFor more information on the sbt-dotty plugin, see the\n[scala3-example-project](https://github.com/scala/scala3-example-project/blob/main/README.md).", + "readme_title": "## sbt project compiled with Scala 3", + "releases_count": 0, + "repo": "fresk-backend", + "repo_name": "fresk-backend", + "stars": 0, + "topics": [], + "updated_at": "2024-12-04T12:05:42Z", + "url": "https://github.com/EPFL-Fresk/fresk-backend", + "watchers": 0 + }, + "https://github.com/EPFL-Fresk/fresk-frontend": { + "commit_count_default_branch": 14, + "contributors_count": 2, + "contributors_top": [ + { + "contributions": 11, + "html_url": "https://github.com/muchembledMartin", + "login": "muchembledMartin" + }, + { + "contributions": 3, + "html_url": "https://github.com/camillelnne", + "login": "camillelnne" + } + ], + "created_at": "2024-11-30T12:34:03Z", + "default_branch": "main", + "description": "Flutter front-end for Fresk", + "dirs_total_count": 65, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 691, + "type": "file" + }, + { + "path": ".metadata", + "size": 1706, + "type": "file" + }, + { + "path": "README.md", + "size": 485, + "type": "file" + }, + { + "path": "analysis_options.yaml", + "size": 193, + "type": "file" + }, + { + "path": "android", + "size": 0, + "type": "dir" + }, + { + "path": "ios", + "size": 0, + "type": "dir" + }, + { + "path": "lib", + "size": 0, + "type": "dir" + }, + { + "path": "linux", + "size": 0, + "type": "dir" + }, + { + "path": "macos", + "size": 0, + "type": "dir" + }, + { + "path": "pubspec.lock", + "size": 6733, + "type": "file" + }, + { + "path": "pubspec.yaml", + "size": 285, + "type": "file" + }, + { + "path": "web", + "size": 0, + "type": "dir" + }, + { + "path": "windows", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 131, + "first_commit_date_default_branch": "2024-11-30T12:33:12Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 4, + "issues_open": 7, + "issues_total": 11, + "languages_top": [ + { + "language": "C++", + "size": 23756 + }, + { + "language": "CMake", + "size": 19404 + }, + { + "language": "Dart", + "size": 2870 + }, + { + "language": "Swift", + "size": 1702 + }, + { + "language": "C", + "size": 1425 + }, + { + "language": "HTML", + "size": 1214 + }, + { + "language": "Kotlin", + "size": 118 + }, + { + "language": "Objective-C", + "size": 38 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:58:01Z", + "last_commit_oid_default_branch": "b498a455e252017fbb914a8d39f2d3fd0948c0da", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "EPFL-Fresk/fresk-frontend", + "owner": "EPFL-Fresk", + "parent_repo": null, + "parent_url": null, + "primary_language": "C++", + "project_foreign_key": "lhp_fcb726875a7ea5f4", + "pull_requests_closed": 0, + "pull_requests_merged": 4, + "pull_requests_open": 1, + "pull_requests_total": 5, + "pushed_at": "2024-12-01T13:05:02Z", + "readme_length": 441, + "readme_text": "# Fresk\n\nFlutter frontend for the Fresk project !\n\n## Project strucure\n```\nlib/\n├── main.dart # Entry point of the app\n├── models/ # Data models\n├── widgets/ # Custom widgets\n├── screens/ # App screens\n│ └── home_screen.dart # Screen with the graph\n├── utils/ # Utilities or helpers\n└── assets/ # Static assets like images and logos\n```", + "readme_title": "Fresk", + "releases_count": 0, + "repo": "fresk-frontend", + "repo_name": "fresk-frontend", + "stars": 0, + "topics": [], + "updated_at": "2024-12-04T12:09:53Z", + "url": "https://github.com/EPFL-Fresk/fresk-frontend", + "watchers": 0 + }, + "https://github.com/EncryptEx/machine-control-monitoring": { + "commit_count_default_branch": 49, + "contributors_count": 5, + "contributors_top": [ + { + "contributions": 22, + "html_url": "https://github.com/EncryptEx", + "login": "EncryptEx" + }, + { + "contributions": 11, + "html_url": "https://github.com/ArnauCS03", + "login": "ArnauCS03" + }, + { + "contributions": 9, + "html_url": "https://github.com/PauMayench", + "login": "PauMayench" + }, + { + "contributions": 5, + "html_url": "https://github.com/GenisLopez5", + "login": "GenisLopez5" + }, + { + "contributions": 2, + "html_url": null, + "login": "arnau.claramunt" + } + ], + "created_at": "2024-11-30T11:31:49Z", + "default_branch": "main", + "description": "Assembled a 3D printed conveyor belt machine, created a digital-twin in Unity and used a chatbot with a small LLM to also interact with the machine remotely.", + "dirs_total_count": 42, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 1322, + "type": "file" + }, + { + "path": "README.md", + "size": 4481, + "type": "file" + }, + { + "path": "UnityProject", + "size": 0, + "type": "dir" + }, + { + "path": "chatbot_api", + "size": 0, + "type": "dir" + }, + { + "path": "rpi", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 542, + "first_commit_date_default_branch": "2024-11-30T11:31:50Z", + "forks": 1, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "C#", + "size": 227053 + }, + { + "language": "ShaderLab", + "size": 80492 + }, + { + "language": "Python", + "size": 27820 + }, + { + "language": "Mathematica", + "size": 15479 + }, + { + "language": "HLSL", + "size": 13994 + }, + { + "language": "HTML", + "size": 4268 + }, + { + "language": "Dockerfile", + "size": 145 + }, + { + "language": "Shell", + "size": 129 + } + ], + "last_commit_date_default_branch": "2024-12-08T14:54:49Z", + "last_commit_oid_default_branch": "df97c34ad9d1c01733523a836b51253478d40590", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "EncryptEx/machine-control-monitoring", + "owner": "EncryptEx", + "parent_repo": null, + "parent_url": null, + "primary_language": "C#", + "project_foreign_key": "lhp_c7c72fc12f8c1120", + "pull_requests_closed": 0, + "pull_requests_merged": 2, + "pull_requests_open": 0, + "pull_requests_total": 2, + "pushed_at": "2024-12-08T14:54:49Z", + "readme_length": 4466, + "readme_text": "# Machine Control & Monitoring with Unity and AI Chatbot\n\n\"logo\"\n\n[Hackathon](https://lauzhack.com/) EPFL Lausanne, Switzerland
\nNovember 30 - December 1\n---\n## Authors\n- Arnau Claramunt\n- Genís López\n- Jaume López\n- Pay Mayench\n\n[![GitHub followers](https://img.shields.io/github/followers/ArnauCS03?label=ArnauCS03)](https://github.com/ArnauCS03)    \n[![GitHub followers](https://img.shields.io/github/followers/GenisLopez5?label=GenisLopez5)](https://github.com/GenisLopez5)    \n[![GitHub followers](https://img.shields.io/github/followers/EncryptEx?label=EncryptEx)](https://github.com/EncryptEx)    \n[![GitHub followers](https://img.shields.io/github/followers/PauMayench?label=PauMayench)](https://github.com/PauMayench)

\n\n\n---\n\n## Project Overview\n\nThis project is the implementation of the **Bobst Company challenge** presented at the LauzHack24 Hackathon. We assembled a 3D printed conveyor belt machine, represent the virtual model in Unity and use a chatbot with a small LLM to also interact with the machine.\n\n**Key Features**: \n- **3D-Printed Conveyor Belt** controlled by a Raspberry Pi. \n- Real-time data collection (speed, box counter, energy usage). \n- AI-powered chatbot for troubleshooting and monitoring via **Ollama's Llama 3.2**. \n- Interactive HMI built in **Unity** for real-time control and visualization. \n- Dockerized architecture for easy deployment.\n- Bridge between Unity and Ollama with FastAPI.\n\n\n---\n\n## 🛠️ Technologies & Tools \n\n| **Component** | **Technology** | **Purpose** |\n|----------------------|-------------------|-----------------------------------------------|\n| **Hardware** | Raspberry Pi | Controls conveyor belt and collects metrics. |\n| **Modeling** | Unity | Creates a 3D visualization of the machine. |\n| **API Layer** | FastAPI | Communication between AI and Unity and Unity to Raspberry Pi. |\n| **AI** | Ollama (Llama 3.2)| Context-aware troubleshooting LLM chatbot. |\n| **Deployment** | Docker | Simplified deployment of all components. |\n\n---\n\n## Bob the AI Chatbot \n\n\n\n\nMeet **Bob**, our AI-powered assistant built on **Ollama's Llama 3.2**. Bob is integrated into the system, providing real-time assistance, troubleshooting, and even direct control over the conveyor belt.\n\n---\n\n### 🧠 How Bob Works \n\n1. **Understand Context**: \n Bob uses the machine's current state (e.g., motor status, speed, output metrics) as context for user interactions.\n\n2. **Interpret User Queries**: \n Natural language queries are passed to Bob along with the machine state for precise and actionable responses.\n\n3. **Execute Actions**: \n When appropriate, Bob translates its recommendations into **machine actions** via API calls to the Unity that then calls the Raspberry Pi.\n\n\n
\n\n\n## 🔮 Future Improvements\n- Add more sensors for enhanced data insights.\n- Introduce predictive maintenance using AI.\n- Expand HMI with detailed production analytics.\n\n
\n\n---\n\n### Screenshots\n\nConveyor belt machine:\n![IMG20241201111510](https://github.com/user-attachments/assets/a1c6302c-2a39-4ec9-8342-4851ba1c60b9)\n\n\nThe machine operates with a safety feature that performs a secure stop to prevent accidents when a hand is detected near the belt:\n\n\nhttps://github.com/user-attachments/assets/0fd7f19d-bdc7-44b0-82ea-ef1dd0de94f4\n\n\n\nUnity interface:\n![Captura_5](https://github.com/user-attachments/assets/ef5957ea-d579-46e6-9464-a22fba821c0b)\n![aimage](https://github.com/user-attachments/assets/7947538a-e56b-42aa-b0e9-361fe7e13a50)\n\n\nAPI for talking to the Raspberry Pi 5:\n![Screenshot from 2024-12-01 04-36-22](https://github.com/user-attachments/assets/71442875-a2fd-4d2d-a9a7-f798587fd7a7)\n\n\n\n
\n\n---\n\n### Setup instructions\n\n1. Clone the Repository: \n```bash\ngit clone git@github.com:EncryptEx/machine-control-monitoring.git\ncd machine-control-monitoring\n```\n\n2. Build and run Dockers containers: (form the `chatbot_api` folder)\n```bash\ndocker-compose up --build\n```\n\n3. Launch Unity Application:
\nOpen the Unity project in your IDE and run the scene.\n\n4. Interact with Bob:
\nUse the chatbot interface in Unity to troubleshoot and control the conveyor.\n\n\n

", + "readme_title": "Machine Control & Monitoring with Unity and AI Chatbot", + "releases_count": 0, + "repo": "machine-control-monitoring", + "repo_name": "machine-control-monitoring", + "stars": 4, + "topics": [], + "updated_at": "2026-01-23T08:31:19Z", + "url": "https://github.com/EncryptEx/machine-control-monitoring", + "watchers": 1 + }, + "https://github.com/GabrielJuan349/TraceXR": { + "commit_count_default_branch": 38, + "contributors_count": 5, + "contributors_top": [ + { + "contributions": 28, + "html_url": "https://github.com/GabrielJuan349", + "login": "GabrielJuan349" + }, + { + "contributions": 6, + "html_url": "https://github.com/JG03dev", + "login": "JG03dev" + }, + { + "contributions": 2, + "html_url": "https://github.com/finnithegamer", + "login": "finnithegamer" + }, + { + "contributions": 1, + "html_url": null, + "login": "1599053@uab.cat" + }, + { + "contributions": 1, + "html_url": "https://github.com/yeray142", + "login": "yeray142" + } + ], + "created_at": "2024-11-30T12:54:00Z", + "default_branch": "main", + "description": "Meta Quest application for Vitol challenge to track and recognize objects and patterns in Mixed Reality. LAUZHACK", + "dirs_total_count": 9, + "files_root_entries": [ + { + "path": ".env.example", + "size": 50, + "type": "file" + }, + { + "path": ".github", + "size": 0, + "type": "dir" + }, + { + "path": ".gitignore", + "size": 3171, + "type": "file" + }, + { + "path": ".gitmodules", + "size": 78, + "type": "file" + }, + { + "path": "LICENSE", + "size": 1069, + "type": "file" + }, + { + "path": "README.md", + "size": 4357, + "type": "file" + }, + { + "path": "WebXR", + "size": 0, + "type": "file" + }, + { + "path": "agent-src", + "size": 0, + "type": "dir" + }, + { + "path": "assets", + "size": 0, + "type": "dir" + }, + { + "path": "examples", + "size": 0, + "type": "dir" + }, + { + "path": "models", + "size": 0, + "type": "dir" + }, + { + "path": "presentation Slides", + "size": 0, + "type": "dir" + }, + { + "path": "requirements.txt", + "size": 1149, + "type": "file" + } + ], + "files_total_count": 23, + "first_commit_date_default_branch": "2024-11-30T12:54:00Z", + "forks": 0, + "has_ci": true, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": true, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 1562429 + }, + { + "language": "Python", + "size": 9136 + } + ], + "last_commit_date_default_branch": "2024-12-02T09:43:50Z", + "last_commit_oid_default_branch": "509c74472f05fe4024407862421adcec9d3bfd33", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": "MIT License", + "license_spdx": "MIT", + "name_with_owner": "GabrielJuan349/TraceXR", + "owner": "GabrielJuan349", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_4d8bd4157500d352", + "pull_requests_closed": 0, + "pull_requests_merged": 3, + "pull_requests_open": 0, + "pull_requests_total": 3, + "pushed_at": "2024-12-02T09:44:37Z", + "readme_length": 4238, + "readme_text": "

\n \n \"Logo\"\n \n\n

TraceXR

\n\n

\n Meta Quest application for Vitol challenge to track and recognize objects and patterns in Mixed Reality.\n
\n Report bug\n ·\n Request feature\n

\n

\n\n\n## Table of contents\n\n- [Quick start](#quick-start)\n- [About this project](#about-this-project)\n- [Status](#status)\n- [What's included](#whats-included)\n- [Bugs and feature requests](#bugs-and-feature-requests)\n- [Creators](#creators)\n- [Copyright and license](#copyright-and-license)\n\n\n## Quick start\n\n### Model download - ONNX format\nYou can find our ONNX model for EfficientNet B7 trained on TU-Berlin Sketch dataset in [Google Drive](https://drive.google.com/file/d/1s6j8zwpggz0hqwEiRSArXn19FGD4639y/view?usp=sharing).\n\n## About this project\n\nThis project combines multiple challenges from [LauzHack](https://lauzhack.com/) of [EPFL, Switzerland](https://www.epfl.ch/en/), which are proposed by companies such as [AXA Group](https://axa.com/) (an Artificial Intelligence model that can run on a laptop, mobile device, or immersive device), [Logitech](https://www.logitech.com/) (using the [MX Ink](https://www.logitech.com/es-es/products/vr/mx-ink.html) together with the [Meta Quest 3/3S](https://www.meta.com/ch/en/quest/quest-3/) to create a Mixed Reality (XR) application), and primarily [Vitol](https://www.vitol.com/) (creating an AI service for recognizing static and moving objects and/or a chatbot capable of interacting with the user).\n\nAs shown in the image below, this project is a multi-agent AI system combining Speech-To-Text with [OpenAI Whisper](https://openai.com/index/whisper/) for multi-agent routing and generating written responses when necessary using [Qwen2.5-0.5b](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct-GGUF). It also utilizes [YoLo11](https://github.com/ultralytics/ultralytics) for object detection in images, an [EfficientNet-B7](https://pytorch.org/vision/main/models/efficientnet.html) ([Arxiv](https://arxiv.org/pdf/1905.11946)) for recognizing patterns or drawings made with the MX Ink, and finally, [OpenAI TTS](https://platform.openai.com/docs/guides/text-to-speech) for Text-to-Speech.\n\n\"Multi\n\nThe implementation within the Meta Quest has been done using WebXR. For more information... [WebXR]( https://github.com/JG03dev/WebXR)\n\n## Status\n\nDuring the LauzHack is in development\n\n## What's included\n\n\n```text\nagent-src/\n│ ├── agent/\n│ │ ├── image_prepos.py\n│ │ ├── router.py\n│ │ └── main.py\n│ └── data-models/\n│ ├── label_mapping.pkl\n│ └── efficientnet_b7.onnx\n├── models/\n│ ├──efficient_net_b7.ipynb\n│ ├──mobile_net.ipynb\n│ └──yolov8.ipynb\n├── assets/\n├── examples/\n├── .env.example\n├── requirements.txt\n```\n\n## Bugs and feature requests\n\nHave a bug or a feature request? Please first read the [issue guidelines](https://reponame/blob/master/CONTRIBUTING.md) and search for existing and closed issues. If your problem or idea is not addressed yet, [please open a new issue](https://reponame/issues/new).\n\n\n## Creators\n\n **Gabriel Juan**\n - GitHub: [@GabrielJuan349](https://github.com/GabrielJuan349)\n - LinkedIn: [in/gabi-juan](https://www.linkedin.com/in/gabi-juan)\n\n**Jan Gras**\n - GitHub: [@JG03dev](https://github.com/JG03dev)\n - LinkedIn: [in/jangras](https://www.linkedin.com/in/jangras/)\n\n**Yeray Cordero**\n - GitHub: [@yeray142](https://github.com/yeray142)\n - LinkedIn: [in/yeray142](https://www.linkedin.com/in/yeray142/)\n\n**Nikalas Boyanov**\n - GitHub: [@finnithegamer](https://github.com/finnithegamer)\n - LinkedIn: [in/nikalas-boyanov-nunev](https://www.linkedin.com/in/nikalas-boyanov-nunev)\n\n## Copyright and license\n\nCode and documentation copyright 2024-2036 the authors. Code released under the [MIT License](https://reponame/blob/master/LICENSE).\n\nEnjoy :metal:", + "readme_title": "

", + "releases_count": 0, + "repo": "TraceXR", + "repo_name": "TraceXR", + "stars": 2, + "topics": [ + "computer-vision", + "deep-learning", + "drawing", + "object-detection", + "object-tracking", + "unity", + "xr", + "xr-multiplayer" + ], + "updated_at": "2025-07-30T15:58:31Z", + "url": "https://github.com/GabrielJuan349/TraceXR", + "watchers": 1 + }, + "https://github.com/Gustavove/lauzhack2024": { + "commit_count_default_branch": 57, + "contributors_count": 2, + "contributors_top": [ + { + "contributions": 53, + "html_url": "https://github.com/Gustavove", + "login": "Gustavove" + }, + { + "contributions": 4, + "html_url": "https://github.com/Jalec", + "login": "Jalec" + } + ], + "created_at": "2024-11-30T14:31:04Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 11, + "files_root_entries": [ + { + "path": ".idea", + "size": 0, + "type": "dir" + }, + { + "path": "Frontend", + "size": 0, + "type": "dir" + }, + { + "path": "QuestBrowser", + "size": 0, + "type": "dir" + }, + { + "path": "README.md", + "size": 2335, + "type": "file" + }, + { + "path": "WebSocket", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 46, + "first_commit_date_default_branch": "2024-11-30T14:31:04Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": "https://lauzhack2024.vercel.app/", + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "JavaScript", + "size": 11836 + }, + { + "language": "TypeScript", + "size": 6898 + }, + { + "language": "HTML", + "size": 701 + }, + { + "language": "CSS", + "size": 233 + } + ], + "last_commit_date_default_branch": "2024-12-01T09:50:18Z", + "last_commit_oid_default_branch": "d941a7815e4cb36d1cd29fa8aab4628326bb4aa4", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "Gustavove/lauzhack2024", + "owner": "Gustavove", + "parent_repo": null, + "parent_url": null, + "primary_language": "JavaScript", + "project_foreign_key": "lhp_570ffaba1e136502", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T09:50:22Z", + "readme_length": 2327, + "readme_text": "# Collaborative Classroom Project - LauzHack Hackathon\n\n## Overview\n\nThe **Collaborative Classroom Project** is an innovative solution for real-time, interactive learning in a virtual classroom environment. Built for the **MetaQuest 3S** and using **MX Ink**, this project enables teachers to create, share, and collaborate with students as they teach, all within a fully immersive experience. Students can view the teacher's creations live on their own browser clients, facilitating an engaging and collaborative learning process.\n\n## Features\n\n- **Real-time Collaboration:** Teachers can create content and share it live with students, all while interacting with the content through a shared virtual environment.\n- **Immersive Experience:** Using **WebXR**, teachers can draw and interact with content from their MetaQuest 3S in real time, bringing a new dimension to virtual learning.\n- **Student Client:** Students use a simple web browser to view the teacher’s content, making it easy to access without special hardware.\n- **WebSocket Communication:** WebSockets enable seamless communication between the teacher's client (MetaQuest 3S) and student clients, ensuring live updates as the teacher draws and creates.\n- **ReactJS & Three.js for 3D Visualization:** The student-side interface is built using **ReactJS** and **Three.js** to provide an interactive and engaging experience.\n\n## Technologies Used\n\n- **ReactJS:** Frontend framework used for building the student-facing website client.\n- **Three.js:** JavaScript library for rendering 3D graphics within the browser, creating an immersive experience for students.\n- **WebXR:** Used for the teacher’s point-of-view, allowing them to draw and interact within the virtual environment via the MetaQuest 3S.\n- **WebSockets:** Facilitates real-time communication between the teacher and students, allowing live updates to be pushed from the teacher’s drawing session to the student clients.\n- **Node.js:** Backend server that handles WebSocket connections and manages the flow of data.\n- **Git:** Version control system used to manage code changes and collaboration during development.\n\n## Installation\n\n### Prerequisites\n\nBefore you can get started, you need to have the following tools installed:\n\n- **Node.js** (v14 or later)\n- **npm** (Node Package Manager)\n- **Git**", + "readme_title": "Collaborative Classroom Project - LauzHack Hackathon", + "releases_count": 0, + "repo": "lauzhack2024", + "repo_name": "lauzhack2024", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T11:01:39Z", + "url": "https://github.com/Gustavove/lauzhack2024", + "watchers": 1 + }, + "https://github.com/Howieboss02/lauzhack-2024": { + "commit_count_default_branch": 56, + "contributors_count": 5, + "contributors_top": [ + { + "contributions": 18, + "html_url": "https://github.com/mziem", + "login": "mziem" + }, + { + "contributions": 15, + "html_url": null, + "login": "ewa.miazga" + }, + { + "contributions": 11, + "html_url": "https://github.com/tflkarolina", + "login": "tflkarolina" + }, + { + "contributions": 7, + "html_url": "https://github.com/ewaMiazga", + "login": "ewaMiazga" + }, + { + "contributions": 5, + "html_url": "https://github.com/Howieboss02", + "login": "Howieboss02" + } + ], + "created_at": "2024-11-30T13:11:34Z", + "default_branch": "main", + "description": "Project for Lauzhack2024", + "dirs_total_count": 21, + "files_root_entries": [ + { + "path": ".env", + "size": 65, + "type": "file" + }, + { + "path": ".gitignore", + "size": 36, + "type": "file" + }, + { + "path": "LICENSE", + "size": 1074, + "type": "file" + }, + { + "path": "README.md", + "size": 3876, + "type": "file" + }, + { + "path": "app.py", + "size": 1786, + "type": "file" + }, + { + "path": "background.js", + "size": 258, + "type": "file" + }, + { + "path": "content.js", + "size": 2023, + "type": "file" + }, + { + "path": "fake.avif", + "size": 104285, + "type": "file" + }, + { + "path": "icon.png", + "size": 319, + "type": "file" + }, + { + "path": "liar_dataset-master", + "size": 0, + "type": "dir" + }, + { + "path": "manifest.json", + "size": 459, + "type": "file" + }, + { + "path": "node_modules", + "size": 0, + "type": "dir" + }, + { + "path": "package-lock.json", + "size": 862, + "type": "file" + }, + { + "path": "package.json", + "size": 53, + "type": "file" + }, + { + "path": "panel.html", + "size": 3992, + "type": "file" + }, + { + "path": "panel.js", + "size": 16839, + "type": "file" + }, + { + "path": "pythong", + "size": 0, + "type": "dir" + }, + { + "path": "requirements.txt", + "size": 32, + "type": "file" + }, + { + "path": "sentiment.py", + "size": 1266, + "type": "file" + }, + { + "path": "static", + "size": 0, + "type": "dir" + }, + { + "path": "styles.css", + "size": 2735, + "type": "file" + }, + { + "path": "tests.ipynb", + "size": 77986, + "type": "file" + } + ], + "files_total_count": 154, + "first_commit_date_default_branch": "2024-11-30T13:11:34Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": true, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 140022 + }, + { + "language": "JavaScript", + "size": 19120 + }, + { + "language": "Python", + "size": 12546 + }, + { + "language": "HTML", + "size": 3992 + }, + { + "language": "CSS", + "size": 2735 + } + ], + "last_commit_date_default_branch": "2024-12-01T12:38:14Z", + "last_commit_oid_default_branch": "f0f986c7e4a74a6a6893a3c310d25fb0977d3dd4", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": "MIT License", + "license_spdx": "MIT", + "name_with_owner": "Howieboss02/lauzhack-2024", + "owner": "Howieboss02", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_d811d6ba10fdbabc", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T12:38:18Z", + "readme_length": 3874, + "readme_text": "# lauzhack-2024\n\n\n[![Contributors][contributors-shield]][contributors-url]\n[![MIT License][license-shield]][license-url]\n\n### Authors\n- [Ewa Miazga](https://github.com/ewaMiazga)\n- [Stanisław Howard](https://github.com/Howieboss02)\n- [Karolina Tofil](https://github.com/tflkarolina)\n- [Maksym Ziemlewski](https://github.com/mziem)\n\n

\n Table of Contents\n
    \n
  1. \n About The Project\n \n
    2. \n
  2. \n For Developers\n \n
\n
\n\n## About The Project\n\n### Motivation\nOur goal was to develop a browser extension that empowers users by providing concise summaries of the news they read and the Twitter posts they browse. This extension goes beyond simple summarization by offering a comprehensive analysis, prompting users to critically evaluate the credibility of the content they consume. By asking whether the news might be fake, the extension raises awareness and encourages users to reflect on how often they may encounter misinformation or fake news.\n\n### Goal \nTo create a user-friendly browser extension that acts as a personal assistant for analyzing online content. The extension performs comprehensive analyses, including hate speech detection, emotion recognition, sentiment analysis, fake news verification, and irony detection, helping users critically evaluate the news and social media posts they consume.\n\n## For Developers\n\n### Build With\n\n* [![React][React.js]][React-url]\n* [![Python][Python.org]][Python-url]\n* [![Flask][Flask.com]][Flask-url]\n\n

(back to top)

\n\n\n### Getting started\n\n\n#### Step 1: Create and Activate the Virtual Environment\n\n##### Linux\n```bash\n# Create a virtual environment if not already created\npython3 -m venv venv\n\n# Activate the virtual environment\nsource venv/bin/activate\n\n# Install the required packages\npip install -r requirements.txt\n```\n##### Windows\n```bash\n# Create a virtual environment if not already created\npython -m venv venv\n\n# Activate the virtual environment\nvenv\\Scripts\\activate\n\n# Install the required packages\npip install -r requirements.txt\n```\n\n---\n\n#### Step 2: Run the Flask Application\n```bash\n# Run the Flask application\npython app.py\n```\n\n#### Step 3: Set Environment Variables\n\n##### Linux\n```bash\n# Set the environment variables\nexport FLASK_APP=app.py\nexport FLASK_ENV=development\n```\n\n##### Windows\n```bash\n# Set the environment variables\nset FLASK_APP=app.py\nset FLASK_ENV=development\n```\n\n\n---\n\n##### Step 4: Deactivate the Virtual Environment\n```bash\n# Deactivate the virtual environment\ndeactivate\n```\n\n---\n\n### License\nDistributed under the MIT License. See `LICENSE.txt` for more information.\n\n

(back to top)

\n\n[contributors-shield]: https://img.shields.io/badge/CONTRIBUTORS-4-brightyellow?style=for-the-badge\n[contributors-url]:https://github.com/Howieboss02/lauzhack-2024/graphs/contributors\n[license-shield]: https://img.shields.io/badge/LICENSE-MIT-brightyellow?style=for-the-badge\n[license-url]: https://github.com/Howieboss02/lauzhack-2024/blob/main/LICENSE\n\n\n[React.js]: https://img.shields.io/badge/JS-black?logo=javascript\n[React-url]: https://developer.mozilla.org/en-US/docs/Web/JavaScript\n[Python.org]: https://img.shields.io/badge/Python-brightgreeen?style=flat&logo=python&logoColor=FFE873&color=306998\n[Python-url]: https://www.python.org/\n[Flask.com]: https://img.shields.io/badge/Flask-black?style=plastic&logo=flask&color=%2361dafb\n[Flask-url]: https://flask.palletsprojects.com/en/3.0.x/", + "readme_title": "lauzhack-2024", + "releases_count": 0, + "repo": "lauzhack-2024", + "repo_name": "lauzhack-2024", + "stars": 1, + "topics": [], + "updated_at": "2024-12-09T23:42:47Z", + "url": "https://github.com/Howieboss02/lauzhack-2024", + "watchers": 1 + }, + "https://github.com/Jeii23/pochify2": { + "commit_count_default_branch": 42, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 26, + "html_url": "https://github.com/Jeii23", + "login": "Jeii23" + }, + { + "contributions": 10, + "html_url": null, + "login": "Nowiisss" + }, + { + "contributions": 6, + "html_url": "https://github.com/Nowiisss", + "login": "Nowiisss" + } + ], + "created_at": "2024-11-30T17:52:05Z", + "default_branch": "master", + "description": null, + "dirs_total_count": 14, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 490, + "type": "file" + }, + { + "path": ".idea", + "size": 0, + "type": "dir" + }, + { + "path": ".mvn", + "size": 0, + "type": "dir" + }, + { + "path": "README.md", + "size": 5284, + "type": "file" + }, + { + "path": "mvnw", + "size": 10284, + "type": "file" + }, + { + "path": "mvnw.cmd", + "size": 6734, + "type": "file" + }, + { + "path": "pom.xml", + "size": 4873, + "type": "file" + }, + { + "path": "src", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 31, + "first_commit_date_default_branch": "2024-11-30T17:52:33Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Java", + "size": 23072 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:37:06Z", + "last_commit_oid_default_branch": "eec51019a72676ba91a55d21a9de9c967af190c0", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "Jeii23/pochify2", + "owner": "Jeii23", + "parent_repo": null, + "parent_url": null, + "primary_language": "Java", + "project_foreign_key": "lhp_a786a143cfabf854", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:37:06Z", + "readme_length": 5282, + "readme_text": "# Pochify\n\nPochify is a JavaFX-based implementation of the traditional Spanish card game **La Pocha**. This interactive application allows players to enjoy the classic game with friends, featuring dynamic player names, rotating player order, bidding, and scoring mechanisms. Developed during a hackathon, Pochify aims to deliver an engaging digital experience of La Pocha.\n\n## Table of Contents\n\n- [Features](#features)\n- [Getting Started](#getting-started)\n - [Prerequisites](#prerequisites)\n - [Installation](#installation)\n- [How to Play](#how-to-play)\n- [Project Structure](#project-structure)\n- [Technologies Used](#technologies-used)\n- [Contributors](#contributors)\n- [License](#license)\n- [Acknowledgments](#acknowledgments)\n\n## Features\n\n- **User-Friendly Interface**: Intuitive GUI built with JavaFX for an enjoyable user experience.\n- **Custom Player Names**: Ability to input and display custom names for each player.\n- **Rotating Player Order**: Automatic rotation of the starting player each round.\n- **Bidding System**: Players place bids, with validation to prevent invalid bids.\n- **Scoring Mechanism**: Automatic calculation and updating of player scores after each round.\n- **Consistent Window Size**: Maintains the same window size across different views for a seamless experience.\n- **Keyboard Shortcuts**: Supports pressing \"Enter\" to submit inputs for faster gameplay.\n\n## Getting Started\n\n### Prerequisites\n\n- **Java Development Kit (JDK) 11 or higher**\n - Download and install from [Oracle's website](https://www.oracle.com/java/technologies/javase-jdk11-downloads.html) or use OpenJDK.\n- **Maven**\n - Download and install from [Maven's website](https://maven.apache.org/download.cgi).\n\n### Installation\n\n1. **Clone the Repository**\n\n ```bash\n git clone https://github.com/yourusername/pochify.git\n cd pochify\n ```\n\n2. **Build the Project with Maven**\n\n ```bash\n mvn clean package\n ```\n\n This will compile the project and package it into a runnable JAR file located in the `target` directory.\n\n3. **Run the Application**\n\n ```bash\n java -jar target/pochify-1.0.jar\n ```\n\n Make sure to adjust the JAR file name according to the version generated.\n\n## How to Play\n\n1. **Launch the Game**\n\n Run the application using the command above.\n\n2. **Select Number of Players**\n\n - Choose between 3, 4, or 5 players on the startup screen.\n\n3. **Enter Player Names**\n\n - Input custom names for each player in the provided text fields.\n\n4. **Place Bids**\n\n - Players take turns to place their bids.\n - The last player is restricted from making a bid that would make the total bids equal to the number of cards in the round.\n\n5. **View Round Details**\n\n - After all bids are placed, the round details are displayed, including round number, type, number of cards, and player bids.\n\n6. **Input Tricks Won**\n\n - Each player inputs the number of tricks they won in the round.\n\n7. **View Updated Scores**\n\n - Scores are calculated based on bids and tricks won.\n - The updated scores are displayed for all players.\n\n8. **Proceed to Next Round**\n\n - The starting player rotates, and the next round begins.\n - Repeat the bidding and playing process until the game concludes.\n\n## Project Structure\n\n- **`src/main/java/org/example/pochi/`**: Contains the main application and controllers.\n - **`GameApplication.java`**: The entry point of the application.\n - **Controllers**:\n - `GameController.java`: Handles the initial game setup.\n - `SetPlayerNamesController.java`: Manages player name input.\n - `NewRoundController.java`: Manages bidding for each round.\n - `GameDetailsController.java`: Displays round details.\n - `FinalizeRoundController.java`: Handles input of tricks won.\n - `ViewScoresController.java`: Displays updated scores after each round.\n- **`src/main/java/org/example/pochi/backend/`**: Contains game logic and data models.\n - **`Partida.java`**: Manages game state, player rotation, and round progression.\n - **`Jugador.java`**: Represents a player with attributes like name, score, and current bid.\n - **`TipusRonda.java`**: Enum defining different types of rounds.\n- **`src/main/resources/org/example/pochi/`**: Contains FXML files for the UI layouts.\n - `game-view.fxml`: Startup screen for selecting the number of players.\n - `set-player-names-view.fxml`: Screen for entering player names.\n - `new-round-view.fxml`: Screen where players place their bids.\n - `game-details-view.fxml`: Displays details after bidding.\n - `finalize-round-view.fxml`: Screen where players input the number of tricks won.\n - `view-scores-view.fxml`: Displays updated scores after each round.\n\n## Technologies Used\n\n- **Java 11 or higher**\n- **JavaFX**\n- **Maven**\n\n## Contributors\n\n- **Jaume Costa** - [jeiidev@proton.me](mailto:jeiidev@proton.me)\n- **Noa Capellas** - [ainoa.cpalen@gmail.com](mailto:ainoa.cpalen@gmail.com)\n\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## Acknowledgments\n\n- **Hackathon Organizers**: For providing the platform to develop this project.\n- **JavaFX Community**: For resources and tutorials that aided development.\n- **Testers**: Friends and colleagues who tested the game and provided valuable feedback.\n\n---", + "readme_title": "Pochify", + "releases_count": 0, + "repo": "pochify2", + "repo_name": "pochify2", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T10:37:10Z", + "url": "https://github.com/Jeii23/pochify2", + "watchers": 1 + }, + "https://github.com/Kooleum/Lauzhack-2024-SmartNotes": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'Kooleum/Lauzhack-2024-SmartNotes'.\"}]", + "owner": "Kooleum", + "project_foreign_key": "lhp_67b5629197933722", + "repo": "Lauzhack-2024-SmartNotes" + }, + "https://github.com/Lylisse/BOBST_LauzHack24": { + "commit_count_default_branch": 3, + "contributors_count": 2, + "contributors_top": [ + { + "contributions": 2, + "html_url": "https://github.com/MathieuVanoirbeek", + "login": "MathieuVanoirbeek" + }, + { + "contributions": 1, + "html_url": "https://github.com/Lylisse", + "login": "Lylisse" + } + ], + "created_at": "2024-11-30T11:00:19Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": "README.md", + "size": 0, + "type": "file" + }, + { + "path": "app.py", + "size": 6386, + "type": "file" + }, + { + "path": "index.html", + "size": 14262, + "type": "file" + } + ], + "files_total_count": 3, + "first_commit_date_default_branch": "2024-11-30T11:16:15Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "HTML", + "size": 14262 + }, + { + "language": "Python", + "size": 6386 + } + ], + "last_commit_date_default_branch": "2024-12-01T11:05:34Z", + "last_commit_oid_default_branch": "50e55c964470171c0a95892850778dac87864c24", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "Lylisse/BOBST_LauzHack24", + "owner": "Lylisse", + "parent_repo": null, + "parent_url": null, + "primary_language": "HTML", + "project_foreign_key": "lhp_1039c108081da24b", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T11:05:35Z", + "readme_length": null, + "readme_text": null, + "readme_title": null, + "releases_count": 0, + "repo": "BOBST_LauzHack24", + "repo_name": "BOBST_LauzHack24", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T11:05:38Z", + "url": "https://github.com/Lylisse/BOBST_LauzHack24", + "watchers": 1 + }, + "https://github.com/MVPee/LauzHack-2024": { + "commit_count_default_branch": 21, + "contributors_count": 4, + "contributors_top": [ + { + "contributions": 10, + "html_url": "https://github.com/Yonyc", + "login": "Yonyc" + }, + { + "contributions": 7, + "html_url": "https://github.com/MVPee", + "login": "MVPee" + }, + { + "contributions": 2, + "html_url": "https://github.com/dspilleb", + "login": "dspilleb" + }, + { + "contributions": 2, + "html_url": "https://github.com/jdecorte-be", + "login": "jdecorte-be" + } + ], + "created_at": "2024-10-30T14:17:18Z", + "default_branch": "main", + "description": "Hackathon LauzHack 2024 (24h)", + "dirs_total_count": 3, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 4, + "type": "file" + }, + { + "path": "check_result.py", + "size": 2672, + "type": "file" + }, + { + "path": "data", + "size": 0, + "type": "dir" + }, + { + "path": "dataset_correction.py", + "size": 2153, + "type": "file" + }, + { + "path": "detect.py", + "size": 2256, + "type": "file" + }, + { + "path": "filter_associations.py", + "size": 693, + "type": "file" + }, + { + "path": "marius.py", + "size": 4479, + "type": "file" + }, + { + "path": "normalize.py", + "size": 1048, + "type": "file" + }, + { + "path": "persons_association.py", + "size": 5336, + "type": "file" + }, + { + "path": "readme.md", + "size": 1626, + "type": "file" + } + ], + "files_total_count": 13, + "first_commit_date_default_branch": "2024-11-30T13:22:38Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": "https://lauzhack.com/", + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 18637 + } + ], + "last_commit_date_default_branch": "2024-12-04T16:15:04Z", + "last_commit_oid_default_branch": "bfd0e46609cb46f05ba59e604aea33af47a08557", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "MVPee/LauzHack-2024", + "owner": "MVPee", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_5b5280ad185f8547", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-04T16:15:04Z", + "readme_length": 1609, + "readme_text": "

\n\t💻 Lauzhack 2024\n

\n\n

\n\t\"GitHub\n\t\"Code\n\t\"GitHub\n\t\"GitHub\n

\n\n# 💡 About the project\n> UBS LauzHack Hackathon Challenge (24 hours)\n\nThis project, developed during a 24-hour UBS hackathon, addresses the challenge of identifying identical users within a massive set of banking transaction data. By leveraging advanced data processing and matching algorithms, our solution efficiently detects and connects user profiles across multiple transactions, ensuring accuracy and scalability.\n\n# 📜 Features:\n\n- High-performance data parsing and analysis for large-scale datasets.\n- Intelligent matching algorithms to identify duplicate users based on transaction patterns, metadata, and identifiers.\n- Scalable and adaptable for integration into banking systems.\n\n# ⚙️ Performance Stats:\n\n- Transactions Processed: 1,450,000\n- Time Taken: 90 seconds\n- Matching Accuracy: 66%\n\n# 👥 Team\n\nThis hackathon project was collaboratively developed by\n- [Yonyc (Arnaud)](https://github.com/Yonyc)\n- [jdecorte (John)](https://github.com/jdecorte-be)\n- [dspilleb (Dan)](https://github.com/dspilleb)\n- [MVPee (Marius)](https://github.com/MVPee)", + "readme_title": "💡 About the project", + "releases_count": 0, + "repo": "LauzHack-2024", + "repo_name": "LauzHack-2024", + "stars": 0, + "topics": [ + "2024", + "24hour", + "challenge", + "datascience", + "hackathon", + "lauzhack", + "ubs" + ], + "updated_at": "2025-11-16T16:21:50Z", + "url": "https://github.com/MVPee/LauzHack-2024", + "watchers": 1 + }, + "https://github.com/MakeGreatBox/AI": { + "commit_count_default_branch": 2, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 2, + "html_url": "https://github.com/oscarvdcr", + "login": "oscarvdcr" + } + ], + "created_at": "2024-12-01T10:09:13Z", + "default_branch": "main", + "description": "Computer vision AI to count boxes and proces which are good ones and bad ones", + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": "tenim_ia_chat.py", + "size": 5638, + "type": "file" + } + ], + "files_total_count": 1, + "first_commit_date_default_branch": "2024-12-01T10:13:00Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": false, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 5638 + } + ], + "last_commit_date_default_branch": "2024-12-01T11:00:54Z", + "last_commit_oid_default_branch": "cc94967cd91b2aa1d8ad55344d2af758896face1", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "MakeGreatBox/AI", + "owner": "MakeGreatBox", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_a05eb2ec7ffaba81", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:59:59Z", + "readme_length": null, + "readme_text": null, + "readme_title": null, + "releases_count": 0, + "repo": "AI", + "repo_name": "AI", + "stars": 1, + "topics": [], + "updated_at": "2024-12-09T23:44:55Z", + "url": "https://github.com/MakeGreatBox/AI", + "watchers": 0 + }, + "https://github.com/MakeGreatBox/backend": { + "commit_count_default_branch": 12, + "contributors_count": 2, + "contributors_top": [ + { + "contributions": 11, + "html_url": "https://github.com/elver5041", + "login": "elver5041" + }, + { + "contributions": 1, + "html_url": "https://github.com/pllinasv", + "login": "pllinasv" + } + ], + "created_at": "2024-11-30T14:23:17Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 1, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 7, + "type": "file" + }, + { + "path": ".python-version", + "size": 7, + "type": "file" + }, + { + "path": "Dockerfile", + "size": 230, + "type": "file" + }, + { + "path": "azure_connection.py", + "size": 2604, + "type": "file" + }, + { + "path": "database", + "size": 0, + "type": "dir" + }, + { + "path": "main.py", + "size": 2166, + "type": "file" + }, + { + "path": "mongo_connection.py", + "size": 228, + "type": "file" + }, + { + "path": "mqtt_connection.py", + "size": 1352, + "type": "file" + }, + { + "path": "requirements.txt", + "size": 114, + "type": "file" + } + ], + "files_total_count": 11, + "first_commit_date_default_branch": "2024-12-01T01:55:36Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": true, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": false, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 8118 + }, + { + "language": "Dockerfile", + "size": 230 + } + ], + "last_commit_date_default_branch": "2024-12-10T15:42:37Z", + "last_commit_oid_default_branch": "3c2e0e0f54dadeb70a398431e6a55bc87931e80f", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "MakeGreatBox/backend", + "owner": "MakeGreatBox", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_a05eb2ec7ffaba81", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-10T15:42:43Z", + "readme_length": null, + "readme_text": null, + "readme_title": null, + "releases_count": 0, + "repo": "backend", + "repo_name": "backend", + "stars": 0, + "topics": [], + "updated_at": "2024-12-10T15:42:46Z", + "url": "https://github.com/MakeGreatBox/backend", + "watchers": 0 + }, + "https://github.com/MakeGreatBox/frontend": { + "commit_count_default_branch": 21, + "contributors_count": 2, + "contributors_top": [ + { + "contributions": 18, + "html_url": "https://github.com/pllinasv", + "login": "pllinasv" + }, + { + "contributions": 3, + "html_url": "https://github.com/oscarvdcr", + "login": "oscarvdcr" + } + ], + "created_at": "2024-11-30T14:17:08Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 18, + "files_root_entries": [ + { + "path": "- copia.gitignore", + "size": 463, + "type": "file" + }, + { + "path": ".eslintrc.json", + "size": 61, + "type": "file" + }, + { + "path": ".gitignore", + "size": 463, + "type": "file" + }, + { + "path": "README.md", + "size": 1014, + "type": "file" + }, + { + "path": "api", + "size": 0, + "type": "dir" + }, + { + "path": "app", + "size": 0, + "type": "dir" + }, + { + "path": "components", + "size": 0, + "type": "dir" + }, + { + "path": "img", + "size": 0, + "type": "dir" + }, + { + "path": "next.config.ts", + "size": 133, + "type": "file" + }, + { + "path": "package-lock.json", + "size": 235052, + "type": "file" + }, + { + "path": "package.json", + "size": 1031, + "type": "file" + }, + { + "path": "postcss.config.mjs", + "size": 135, + "type": "file" + }, + { + "path": "public", + "size": 0, + "type": "dir" + }, + { + "path": "server.js", + "size": 456, + "type": "file" + }, + { + "path": "tailwind.config.ts", + "size": 242, + "type": "file" + }, + { + "path": "tsconfig.json", + "size": 652, + "type": "file" + } + ], + "files_total_count": 43, + "first_commit_date_default_branch": "2024-11-30T14:19:43Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "TypeScript", + "size": 23027 + }, + { + "language": "JavaScript", + "size": 591 + }, + { + "language": "CSS", + "size": 341 + } + ], + "last_commit_date_default_branch": "2024-12-01T21:31:41Z", + "last_commit_oid_default_branch": "6d2592169f2b009befdced71b5edbedaad662048", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "MakeGreatBox/frontend", + "owner": "MakeGreatBox", + "parent_repo": null, + "parent_url": null, + "primary_language": "TypeScript", + "project_foreign_key": "lhp_a05eb2ec7ffaba81", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T21:31:46Z", + "readme_length": 1013, + "readme_text": "# SmartBox Control System\nWelcome to MakeGreatBox, a solution developed during LauzHack to tackle the challenge of controlling a production machine in a cardboard box factory. This system streamlines the process of managing box production by introducing a centralized, user-friendly interface for monitoring, configuring, and controlling the production line in real time.\n\n# Features\nReal-time Machine Monitoring: Track the current status of the production machine (e.g., speed, temperature, and errors).\n\nProduction Configuration: Customize parameters such as box dimensions, material thickness, and batch size.\n\nError Management: Receive alerts and troubleshoot machine errors efficiently.\n\nPerformance Analytics: View production metrics such as throughput and machine utilization.\n\nHistorical Data: View what happened on specific dates to better understand how it's going.\n\n# Tech Stack\n\n## Frontend:\n\n## Backend:\n\n## Database:\n\n## Hardware Integration:\n\nRaspberry Pi 5 for machine communication.\n\n# How to use", + "readme_title": "SmartBox Control System", + "releases_count": 0, + "repo": "frontend", + "repo_name": "frontend", + "stars": 0, + "topics": [], + "updated_at": "2024-12-07T14:25:40Z", + "url": "https://github.com/MakeGreatBox/frontend", + "watchers": 0 + }, + "https://github.com/MakeGreatBox/hardware": { + "commit_count_default_branch": 3, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 3, + "html_url": "https://github.com/bepes-code", + "login": "bepes-code" + } + ], + "created_at": "2024-11-30T14:22:51Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": "sensors.py", + "size": 11360, + "type": "file" + } + ], + "files_total_count": 1, + "first_commit_date_default_branch": "2024-12-01T09:28:27Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": false, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 11360 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:55:25Z", + "last_commit_oid_default_branch": "734257e30b888b7ab044b5a813ae1272560fb38f", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "MakeGreatBox/hardware", + "owner": "MakeGreatBox", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_a05eb2ec7ffaba81", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:55:29Z", + "readme_length": null, + "readme_text": null, + "readme_title": null, + "releases_count": 0, + "repo": "hardware", + "repo_name": "hardware", + "stars": 1, + "topics": [], + "updated_at": "2024-12-09T23:45:09Z", + "url": "https://github.com/MakeGreatBox/hardware", + "watchers": 0 + }, + "https://github.com/MarkusUrbanPersonal/connect_global_app": { + "commit_count_default_branch": 40, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 40, + "html_url": "https://github.com/MarkusUrbanPersonal", + "login": "MarkusUrbanPersonal" + } + ], + "created_at": "2024-11-30T18:09:01Z", + "default_branch": "main", + "description": "A new app to connect with people developed at LauzHack 2024", + "dirs_total_count": 6, + "files_root_entries": [ + { + "path": "README.md", + "size": 2700, + "type": "file" + }, + { + "path": "auth", + "size": 0, + "type": "dir" + }, + { + "path": "web", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 49, + "first_commit_date_default_branch": "2024-11-30T18:08:57Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "JavaScript", + "size": 34781 + }, + { + "language": "HTML", + "size": 31298 + }, + { + "language": "CSS", + "size": 5769 + } + ], + "last_commit_date_default_branch": "2024-12-01T09:50:32Z", + "last_commit_oid_default_branch": "a3cd6ec50ee1f34c1e7cc13ae10fd82b0beb5336", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "MarkusUrbanPersonal/connect_global_app", + "owner": "MarkusUrbanPersonal", + "parent_repo": null, + "parent_url": null, + "primary_language": "JavaScript", + "project_foreign_key": "lhp_6c0ad88021c63ac2", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T09:50:32Z", + "readme_length": 2668, + "readme_text": "

\n \"drawing\"\n

\n
\n

\n\n

\n\n![Banner](https://github.com/user-attachments/assets/7b7b13a8-68ab-4ad2-998a-b61804584fc2)\n\n\n\n### **The concept** ☀️\nMeeting people can be challenging, especially when travelling or attending events like Hackathons. This is where **Connect** comes in. \n\n### **How it works** 📱\n\n#### **1. Create an account**\nTo join the app, you'll have to fill some basic information. \n\n\n\n#### **2. Join a group**\nAfter joining, you can select the event that you're attending, that could be almost anything. There could even be groups for university classes, office employees or even neighbourhoods!\n\n\n\n#### **3. Select your interests**\nThis interests include main topics, but the list can be tailored to any specific event. There's also a search bar to find more interests. \n\n\n\n#### **4. Discover similar users**\nAfter adding your interests, other members with similar interests start to appear on the main screen. Hooray! \n\n\n\n#### **5. Make new connections**\nYou can check your common interests and start a conversation. **Making new connections has never been easier!** ☀️\n\n\n\n\n### Tech Stack\nThe web-app has been created using:\n \n 🔵 **HTML**\n \n 🟢 **CSS**\n \n 🟨 **Javascript**\n \n ✨ **Flowbite** *(UI Components)*\n\n 🐍 **Python** *(basic backend)*\n\n\n### **The future** ✨\nWhat about going one step further, and using *bluetooth* to actually connect users, as they're walking through common areas? The phone could display the common interests and conversation would start instantly. That is a future vision for this project. Until then, **Connect** is a great way to meet with new people at all kind of events. \n\n

\n \n

", + "readme_title": "

", + "releases_count": 0, + "repo": "connect_global_app", + "repo_name": "connect_global_app", + "stars": 1, + "topics": [ + "application", + "flowbite", + "html", + "javascript", + "tailwindcss" + ], + "updated_at": "2024-12-09T23:42:43Z", + "url": "https://github.com/MarkusUrbanPersonal/connect_global_app", + "watchers": 1 + }, + "https://github.com/Matthieu-Andre/Lauzhack_2024": { + "commit_count_default_branch": 63, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 45, + "html_url": "https://github.com/maschull106", + "login": "maschull106" + }, + { + "contributions": 10, + "html_url": "https://github.com/SloDamn", + "login": "SloDamn" + }, + { + "contributions": 8, + "html_url": "https://github.com/Matthieu-Andre", + "login": "Matthieu-Andre" + } + ], + "created_at": "2024-11-30T09:56:52Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 15, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 3217, + "type": "file" + }, + { + "path": "App", + "size": 0, + "type": "dir" + }, + { + "path": "LICENSE", + "size": 1071, + "type": "file" + }, + { + "path": "README.md", + "size": 3306, + "type": "file" + }, + { + "path": "assets", + "size": 0, + "type": "dir" + }, + { + "path": "clothes", + "size": 0, + "type": "dir" + }, + { + "path": "requirements.txt", + "size": 791, + "type": "file" + }, + { + "path": "server", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 113, + "first_commit_date_default_branch": "2024-11-30T09:56:52Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": true, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 32994 + }, + { + "language": "TypeScript", + "size": 24822 + }, + { + "language": "JavaScript", + "size": 1123 + }, + { + "language": "HTML", + "size": 279 + } + ], + "last_commit_date_default_branch": "2024-12-01T11:04:57Z", + "last_commit_oid_default_branch": "c8a5890abea0958ff56d2c5ebcd73ae956e8d5ad", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": "MIT License", + "license_spdx": "MIT", + "name_with_owner": "Matthieu-Andre/Lauzhack_2024", + "owner": "Matthieu-Andre", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_29a8ab4232c426dc", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T11:05:00Z", + "readme_length": 3282, + "readme_text": "# WearIt: Your Smart Dressing Companion 👗👕🎽\n\n![WearIt Logo](https://github.com/Matthieu-Andre/Lauzhack_2024/blob/main/assets/logo.png?raw=true \"WearIt Logo\")\nhttps://github.com/Matthieu-Andre/Lauzhack_2024?tab=readme-ov-file\n**WearIt** is a mobile application designed to make your mornings easier and your wardrobe smarter. By cataloging your clothes, WearIt provides daily outfit recommendations tailored to your preferences, the weather, and more. Whether you're a student with a packed wardrobe or someone looking to streamline their dressing process, WearIt has you covered.\n\n---\n\n## 🛠 Features\n- **Wardrobe Organizer** \n Easily add clothes with photos. The app automatically detects the type of clothing and extracts features like color and weather suitability. \n\n- **Daily Outfit Suggestions** \n Get personalized outfit ideas that match your style, the weather, and the occasion.\n\n- **Weather-Based Recommendations** \n WearIt integrates real-time weather updates to ensure your outfit is always appropriate.\n\n- **Usage Insights** \n Discover patterns in your wardrobe usage and rediscover neglected items.\n\n- **Simplified Morning Routine** \n Spend less time deciding what to wear and more time being confident in your look.\n\n---\n\n## 🎯 Who Is It For?\n**WearIt** is perfect for: \n- **Students** managing cluttered wardrobes. \n- **Busy Professionals** who want stress-free mornings. \n- **Anyone** aiming to maximize their clothing collection and dress effortlessly.\n\n---\n\n## 🚀 Getting Started\n\n### Prerequisites\n- A smartphone with Android or iOS.\n- An internet connection for weather updates.\n\n---\n\n## 📚 Tech Stack\n- **Frontend:** [React Native](https://reactnative.dev/) for a smooth, cross-platform experience. \n- **Backend:** [FastAPI](https://fastapi.tiangolo.com/) for robust API services. \n- **Database:** SQLite for lightweight and efficient data management. \n- **Weather API:** Accurate weather data for context-aware recommendations. \n- **Prototyping:** [Figma](https://www.figma.com/) was used to design and refine the user interface.\n\n---\n\n## 🌟 Vision for the Future\n- **3D Outfit Visualization**: See your outfits on a 3D model of yourself for better visualization. \n- **Friend Networks**: Share your \"Outfit of the Day\" with friends and vote on each other's next-day outfits. \n- **Advanced Style Tips**: AI-powered recommendations based on fashion trends. \n- **Event-Specific Outfits**: Suggestions tailored to specific occasions. \n\n---\n\n**WearIt**: Transform your wardrobe, simplify your mornings, and own your style! \n\n\n\n![Demo](https://github.com/Matthieu-Andre/Lauzhack_2024/blob/main/assets/s1.png?raw=true)\n![Demo](https://github.com/Matthieu-Andre/Lauzhack_2024/blob/main/assets/s2.png?raw=true)\n![Demo](https://github.com/Matthieu-Andre/Lauzhack_2024/blob/main/assets/s3.png?raw=true)\n![Demo](https://github.com/Matthieu-Andre/Lauzhack_2024/blob/main/assets/s4.png?raw=true)\n![Demo](https://github.com/Matthieu-Andre/Lauzhack_2024/blob/main/assets/s5.png?raw=true)\n![Demo](https://github.com/Matthieu-Andre/Lauzhack_2024/blob/main/assets/s6.png?raw=true)\n![Demo](https://github.com/Matthieu-Andre/Lauzhack_2024/blob/main/assets/s7.png?raw=true)\n![Demo](https://github.com/Matthieu-Andre/Lauzhack_2024/blob/main/assets/s8.png?raw=true)", + "readme_title": "WearIt: Your Smart Dressing Companion 👗👕🎽", + "releases_count": 0, + "repo": "Lauzhack_2024", + "repo_name": "Lauzhack_2024", + "stars": 1, + "topics": [], + "updated_at": "2024-12-09T23:42:18Z", + "url": "https://github.com/Matthieu-Andre/Lauzhack_2024", + "watchers": 1 + }, + "https://github.com/MatyaAydin/LauzHack2024": { + "commit_count_default_branch": 17, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 9, + "html_url": null, + "login": "BRUNO Elie" + }, + { + "contributions": 6, + "html_url": "https://github.com/MatyaAydin", + "login": "MatyaAydin" + }, + { + "contributions": 2, + "html_url": null, + "login": "sim" + } + ], + "created_at": "2024-11-30T14:22:40Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 11, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 3247, + "type": "file" + }, + { + "path": ".gitmodules", + "size": 71, + "type": "file" + }, + { + "path": "README.md", + "size": 63, + "type": "file" + }, + { + "path": "__pycache__", + "size": 0, + "type": "dir" + }, + { + "path": "csvs", + "size": 0, + "type": "dir" + }, + { + "path": "data", + "size": 0, + "type": "dir" + }, + { + "path": "interface.py", + "size": 6318, + "type": "file" + }, + { + "path": "pic_analyse.py", + "size": 2509, + "type": "file" + }, + { + "path": "prompt.py", + "size": 2145, + "type": "file" + }, + { + "path": "request_openAI.py", + "size": 926, + "type": "file" + }, + { + "path": "runs", + "size": 0, + "type": "dir" + }, + { + "path": "scripts", + "size": 0, + "type": "dir" + }, + { + "path": "simulated_boat_data", + "size": 0, + "type": "dir" + }, + { + "path": "sort", + "size": 0, + "type": "file" + }, + { + "path": "track2.py", + "size": 557, + "type": "file" + }, + { + "path": "video_analyse.py", + "size": 1366, + "type": "file" + }, + { + "path": "yolov8s.pt", + "size": 22588772, + "type": "file" + } + ], + "files_total_count": 50, + "first_commit_date_default_branch": "2024-11-30T14:22:41Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 24573 + }, + { + "language": "Shell", + "size": 1033 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:41:34Z", + "last_commit_oid_default_branch": "47439210744601eec5c61111ed520512326fe4c4", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "MatyaAydin/LauzHack2024", + "owner": "MatyaAydin", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_73126a21f3209127", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:41:42Z", + "readme_length": 63, + "readme_text": "# LauzHack2024\n\nVittol challenge\n\n### Team Members:\nMatya Aydin", + "readme_title": "LauzHack2024", + "releases_count": 0, + "repo": "LauzHack2024", + "repo_name": "LauzHack2024", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T10:41:46Z", + "url": "https://github.com/MatyaAydin/LauzHack2024", + "watchers": 1 + }, + "https://github.com/MikiVanousek/vitol": { + "commit_count_default_branch": 150, + "contributors_count": 5, + "contributors_top": [ + { + "contributions": 46, + "html_url": "https://github.com/andolg", + "login": "andolg" + }, + { + "contributions": 40, + "html_url": "https://github.com/theS3b", + "login": "theS3b" + }, + { + "contributions": 29, + "html_url": "https://github.com/MikiVanousek", + "login": "MikiVanousek" + }, + { + "contributions": 26, + "html_url": "https://github.com/Jakhongir0103", + "login": "Jakhongir0103" + }, + { + "contributions": 9, + "html_url": "https://github.com/charafkamel", + "login": "charafkamel" + } + ], + "created_at": "2024-11-30T16:02:14Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 34, + "files_root_entries": [ + { + "path": ".env.example", + "size": 15, + "type": "file" + }, + { + "path": ".gitignore", + "size": 3236, + "type": "file" + }, + { + "path": ".gradio", + "size": 0, + "type": "dir" + }, + { + "path": "LICENSE", + "size": 1063, + "type": "file" + }, + { + "path": "Previous Locations Creator.ipynb", + "size": 18037852, + "type": "file" + }, + { + "path": "README.md", + "size": 3276, + "type": "file" + }, + { + "path": "app.ipynb", + "size": 482298, + "type": "file" + }, + { + "path": "backend", + "size": 0, + "type": "dir" + }, + { + "path": "bot", + "size": 0, + "type": "dir" + }, + { + "path": "environment.yml", + "size": 7518, + "type": "file" + }, + { + "path": "img", + "size": 0, + "type": "dir" + }, + { + "path": "location.py", + "size": 9028, + "type": "file" + }, + { + "path": "sattelite_downloader", + "size": 0, + "type": "dir" + }, + { + "path": "tiles", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 770, + "first_commit_date_default_branch": "2022-10-24T22:01:28Z", + "forks": 4, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": true, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 20375579 + }, + { + "language": "Python", + "size": 317650 + } + ], + "last_commit_date_default_branch": "2024-12-04T20:20:27Z", + "last_commit_oid_default_branch": "5008ae41b33cfb1eb3dad59e210477fe4e2559b3", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": "MIT License", + "license_spdx": "MIT", + "name_with_owner": "MikiVanousek/vitol", + "owner": "MikiVanousek", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_6caa8a42e5f97267", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-04T20:20:28Z", + "readme_length": 3240, + "readme_text": "![](img/thumbnail_hackathon_2.jpg)\n© 2024 OpenAI\n\n# Description\n**Any Question Any Place** is an AI-powered platform that combines Large Language Models (LLM) and Computer Vision (CV) to analyze satellite imagery interactively. \n\n### How it works:\n1. **Input**: \n - A satellite image (e.g., of storage tanks)\n - A natural language question about the image (e.g., \"How many storage tanks have a diameter greater than 5m?\")\n\n2. **Processing**:\n - The LLM acts as an expert interpreter\n - It analyzes the user's question\n - It selects and calls appropriate computer vision tools \n - It post-processes the output before generating a human-friendly responses\n\n3. **Features**:\n - Supports various interpretation tasks using specialized remote sensing datasets\n - Uses image captioning to help the LLM better understand satellite imagery context\n - Provides natural language responses to complex visual queries\n\nThis platform bridges the gap between technical satellite image analysis and user-friendly interaction, allowing anyone to extract insights from satellite imagery through simple questions.\n\n# Use cases\n### Objects\n**Supported classes:**\n\nplane, ship, storage tank, ground track field, large vehicle, small vehicle, helicopter\n\n**Question Examples:**\n\n- How many ships are there in the image? *(count)*\n- How many storage tanks are there with a diameter above 5m? *(count with constranting on size)*\n- How many planes are in the image? *(if non-existing object, is not counted)*\n- How many cars are there in the image? *(non-supported classes are responded by GPT-4o mini)*\n- How many cars are there that are not parked?\n\n### Fields\n**Supported classes:**\n\nurban land, agriculture, rangeland, forest land, water, barren land\n\n**Question: Examples**\n\n- What is the area of agricultural land/forest? *(deforestation analysis)*\n- What is the ratio of water in the image?\n- What occupies the largest area in the image?\n\n### Solar\n\n**Question Example:**\n\n- What is the coverage of the solar panels in the image?\n\n**Any type of questions not mentioned above will be answered by GPT-4o mini**\n\n# Demonstration\n![](img/cars.png)\nCounting with specifications\n\n![](img/diameter.png)\nCounting with constrating on diameter\n\n![](img/threshold.png)\nThesholding on uncertainty\n\n![](img/big%20ships.png)\nCounting big ships\n\n![](img/forest.png)\nArea in square meter of the forest in an image (you could ask e.g. area of water, urban land, agriculture)\n\n![](img/solar_panels.png)\nArea in square meter of solar panels\n\n# Usage\n### Install dependencies\n```\nconda env create -f environment.yml\n```\n\n### Structure\n```\nvitol/\n├── app.ipynb\n├── backend # CV models\n├── bot # LLM around CV models\n├── sattelite_downloader # Sattelite image downloader\n├── app.ipynb # Demo on Gradio\n```\n\n# Contributers:\n- [Mikuláš Vanoušek](https://github.com/MikiVanousek)\n- [Jakhongir0103](https://github.com/Jakhongir0103)\n- [Sébastien Delsad](https://github.com/theS3b)\n- [Kamel Charaf](https://github.com/charafkamel)", + "readme_title": "Description", + "releases_count": 0, + "repo": "vitol", + "repo_name": "vitol", + "stars": 2, + "topics": [], + "updated_at": "2025-11-04T17:05:54Z", + "url": "https://github.com/MikiVanousek/vitol", + "watchers": 1 + }, + "https://github.com/R4oulDuk3/bober": { + "commit_count_default_branch": 28, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 26, + "html_url": "https://github.com/R4oulDuk3", + "login": "R4oulDuk3" + }, + { + "contributions": 1, + "html_url": null, + "login": "GavriloV" + }, + { + "contributions": 1, + "html_url": null, + "login": "shus" + } + ], + "created_at": "2024-11-30T11:52:46Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 6, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 3298, + "type": "file" + }, + { + "path": "README.md", + "size": 1672, + "type": "file" + }, + { + "path": "analytics", + "size": 0, + "type": "dir" + }, + { + "path": "config.json", + "size": 35, + "type": "file" + }, + { + "path": "config_reloader_main.py", + "size": 421, + "type": "file" + }, + { + "path": "core", + "size": 0, + "type": "dir" + }, + { + "path": "enums.py", + "size": 224, + "type": "file" + }, + { + "path": "explore", + "size": 0, + "type": "dir" + }, + { + "path": "exporter_side_car_main.py", + "size": 393, + "type": "file" + }, + { + "path": "implementations", + "size": 0, + "type": "dir" + }, + { + "path": "infrastructure", + "size": 0, + "type": "dir" + }, + { + "path": "interfaces", + "size": 0, + "type": "dir" + }, + { + "path": "main.py", + "size": 1811, + "type": "file" + }, + { + "path": "requirements.txt", + "size": 75, + "type": "file" + } + ], + "files_total_count": 47, + "first_commit_date_default_branch": "2024-11-30T11:56:53Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 65680 + } + ], + "last_commit_date_default_branch": "2024-12-01T12:43:05Z", + "last_commit_oid_default_branch": "6040ff22c500fabf76a31ab1f5356fa560304464", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "R4oulDuk3/bober", + "owner": "R4oulDuk3", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_19563f916f71382c", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T12:43:05Z", + "readme_length": 1668, + "readme_text": "# Bober Stack 🦫\n### LausHack 2024 - BOBST Challenge Project\n\n## Overview\nBober Stack is a full-stack monitoring and control system developed for BOBST packaging company during LausHack 2024. The project name comes from \"bober\" (beaver) - our mascot representing BOBST's connection to paper and cardboard packaging.\n\nThe system provides real-time control and monitoring of a miniature Arduino-operated packaging conveyor belt through a Raspberry Pi interface.\n\n## Architecture\n![Architecture Diagram Placeholder]()\n- Angular Frontend for user interface\n- Spring Boot Backend API\n- Prometheus for metrics collection\n- Python service on Raspberry Pi\n- Arduino-controlled conveyor belt\n\n## Features\n- **Real-time Control Panel**\n - 5-step speed control (10-14 units)\n - Power management\n - System status monitoring\n\n
\n \n- **Live Metrics Dashboard**: PU usage and frequency, Memory utilization, Disk usage, System load, Custom application metrics\n \n
\n\n- **Alert System**: Real-time system alerts, Multiple severity levels, Visual indicators, Configurable alert rules\n \n
\n\n- **Logging Interface**: System events tracking, Operation logs, Error monitoring\n \n
\n\n- **BOBST Platform Integration**: Direct access to BOBST operator equipment portal\n\n## Tech Stack\n### Frontend\n- Angular 17\n- TypeScript\n- Angular Material UI\n- Chart.js\n- SCSS\n\n### Backend\n- Java 17\n- Spring Boot\n- Prometheus\n- Docker\n- Maven\n\n### IoT\n- Python\n- Raspberry Pi\n- Arduino\n\n## Setup Instructions\n\n### Prerequisites\n- Node.js and npm\n- Java 17\n- Maven\n- Docker\n- Python 3\n- Raspberry Pi\n- Arduino setup\n\n### Frontend Setup\n1. Install dependencies:\n```bash\nnpm install", + "readme_title": "Bober Stack 🦫", + "releases_count": 0, + "repo": "bober", + "repo_name": "bober", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T12:43:08Z", + "url": "https://github.com/R4oulDuk3/bober", + "watchers": 1 + }, + "https://github.com/R4oulDuk3/lauzhack-2024": { + "commit_count_default_branch": 26, + "contributors_count": 4, + "contributors_top": [ + { + "contributions": 15, + "html_url": null, + "login": "shus" + }, + { + "contributions": 7, + "html_url": "https://github.com/R4oulDuk3", + "login": "R4oulDuk3" + }, + { + "contributions": 3, + "html_url": "https://github.com/Savke57", + "login": "Savke57" + }, + { + "contributions": 1, + "html_url": "https://github.com/theShus", + "login": "theShus" + } + ], + "created_at": "2024-11-29T20:41:51Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 37, + "files_root_entries": [ + { + "path": ".idea", + "size": 0, + "type": "dir" + }, + { + "path": "Lauzhack2024.iml", + "size": 307, + "type": "file" + }, + { + "path": "README.md", + "size": 1672, + "type": "file" + }, + { + "path": "backend.iml", + "size": 374, + "type": "file" + }, + { + "path": "backend", + "size": 0, + "type": "dir" + }, + { + "path": "frontend", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 79, + "first_commit_date_default_branch": "2024-11-29T20:46:18Z", + "forks": 1, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "TypeScript", + "size": 23611 + }, + { + "language": "Java", + "size": 11634 + }, + { + "language": "SCSS", + "size": 9716 + }, + { + "language": "HTML", + "size": 7396 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:31:34Z", + "last_commit_oid_default_branch": "806769aa2e748a9f72466b2d1d8503e8377f8062", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "R4oulDuk3/lauzhack-2024", + "owner": "R4oulDuk3", + "parent_repo": null, + "parent_url": null, + "primary_language": "TypeScript", + "project_foreign_key": "lhp_19563f916f71382c", + "pull_requests_closed": 0, + "pull_requests_merged": 1, + "pull_requests_open": 0, + "pull_requests_total": 1, + "pushed_at": "2024-12-01T10:31:35Z", + "readme_length": 1668, + "readme_text": "# Bober Stack 🦫\n### LausHack 2024 - BOBST Challenge Project\n\n## Overview\nBober Stack is a full-stack monitoring and control system developed for BOBST packaging company during LausHack 2024. The project name comes from \"bober\" (beaver) - our mascot representing BOBST's connection to paper and cardboard packaging.\n\nThe system provides real-time control and monitoring of a miniature Arduino-operated packaging conveyor belt through a Raspberry Pi interface.\n\n## Architecture\n![Architecture Diagram Placeholder]()\n- Angular Frontend for user interface\n- Spring Boot Backend API\n- Prometheus for metrics collection\n- Python service on Raspberry Pi\n- Arduino-controlled conveyor belt\n\n## Features\n- **Real-time Control Panel**\n - 5-step speed control (10-14 units)\n - Power management\n - System status monitoring\n\n
\n \n- **Live Metrics Dashboard**: PU usage and frequency, Memory utilization, Disk usage, System load, Custom application metrics\n \n
\n\n- **Alert System**: Real-time system alerts, Multiple severity levels, Visual indicators, Configurable alert rules\n \n
\n\n- **Logging Interface**: System events tracking, Operation logs, Error monitoring\n \n
\n\n- **BOBST Platform Integration**: Direct access to BOBST operator equipment portal\n\n## Tech Stack\n### Frontend\n- Angular 17\n- TypeScript\n- Angular Material UI\n- Chart.js\n- SCSS\n\n### Backend\n- Java 17\n- Spring Boot\n- Prometheus\n- Docker\n- Maven\n\n### IoT\n- Python\n- Raspberry Pi\n- Arduino\n\n## Setup Instructions\n\n### Prerequisites\n- Node.js and npm\n- Java 17\n- Maven\n- Docker\n- Python 3\n- Raspberry Pi\n- Arduino setup\n\n### Frontend Setup\n1. Install dependencies:\n```bash\nnpm install", + "readme_title": "Bober Stack 🦫", + "releases_count": 0, + "repo": "lauzhack-2024", + "repo_name": "lauzhack-2024", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T12:05:10Z", + "url": "https://github.com/R4oulDuk3/lauzhack-2024", + "watchers": 1 + }, + "https://github.com/ReinBentdal/01_": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'ReinBentdal/01_'.\"}]", + "owner": "ReinBentdal", + "project_foreign_key": "lhp_cfd3d79a6f0cd0fe", + "repo": "01_" + }, + "https://github.com/Sagar-CK/ubs-lauzhack": { + "commit_count_default_branch": 4, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 4, + "html_url": "https://github.com/Sagar-CK", + "login": "Sagar-CK" + } + ], + "created_at": "2024-11-30T17:33:32Z", + "default_branch": "main", + "description": "team andy", + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": "README.md", + "size": 657, + "type": "file" + }, + { + "path": "ubs_lauzhack_andy.ipynb", + "size": 407950, + "type": "file" + } + ], + "files_total_count": 2, + "first_commit_date_default_branch": "2024-12-01T11:00:22Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 407950 + } + ], + "last_commit_date_default_branch": "2024-12-01T11:05:15Z", + "last_commit_oid_default_branch": "b468cb75e08c002b2eb1d3d475d647bc4c9068a1", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "Sagar-CK/ubs-lauzhack", + "owner": "Sagar-CK", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_502fc0b65dda2c29", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T11:05:18Z", + "readme_length": 657, + "readme_text": "# LauzHack - 2024 \n## Team Andy\n> Members: Neel Lodha, Manu Gautam, Sagar Chethan Kumar, Atilla Colak\n\nThis repository contains the solution for the LauzHack 2024 hackathon UBS challenge. We document our exploratory data analysis, model building, and submission process in this repository.\n\nThanks to the challenge organizers for providing us with the opportunity to work on this interesting problem statement!\n\n*Note: The contents of the `data/` directory have been omitted from this repository due to the large file sizes. If trying to replicate, please source the ubs challenge files and place them in the root `data/` directory before running the code.*", + "readme_title": "LauzHack - 2024", + "releases_count": 0, + "repo": "ubs-lauzhack", + "repo_name": "ubs-lauzhack", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T11:05:22Z", + "url": "https://github.com/Sagar-CK/ubs-lauzhack", + "watchers": 1 + }, + "https://github.com/SkinnyPeter/LauzhackBMS": { + "commit_count_default_branch": 4, + "contributors_count": 2, + "contributors_top": [ + { + "contributions": 3, + "html_url": null, + "login": "Matthew Meyer" + }, + { + "contributions": 1, + "html_url": "https://github.com/SkinnyPeter", + "login": "SkinnyPeter" + } + ], + "created_at": "2024-11-30T12:11:07Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": "README.md", + "size": 6, + "type": "file" + }, + { + "path": "components_nav-section.tsx", + "size": 1343, + "type": "file" + }, + { + "path": "components_overview-section.tsx", + "size": 2165, + "type": "file" + }, + { + "path": "components_site-header.tsx", + "size": 1494, + "type": "file" + }, + { + "path": "data_preprocessing.ipynb", + "size": 53251, + "type": "file" + } + ], + "files_total_count": 5, + "first_commit_date_default_branch": "2024-11-30T14:24:55Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 53251 + }, + { + "language": "TypeScript", + "size": 5002 + } + ], + "last_commit_date_default_branch": "2024-12-01T08:25:07Z", + "last_commit_oid_default_branch": "dfe404c2cd390c157ba4e2ff80ef7532f28e8bbd", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "SkinnyPeter/LauzhackBMS", + "owner": "SkinnyPeter", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_57c9ba335272248a", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 1, + "pull_requests_total": 1, + "pushed_at": "2024-12-01T10:46:33Z", + "readme_length": 5, + "readme_text": "Salut", + "readme_title": "Salut", + "releases_count": 0, + "repo": "LauzhackBMS", + "repo_name": "LauzhackBMS", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T08:25:14Z", + "url": "https://github.com/SkinnyPeter/LauzhackBMS", + "watchers": 1 + }, + "https://github.com/SolomonTracker/.github": { + "commit_count_default_branch": 13, + "contributors_count": 2, + "contributors_top": [ + { + "contributions": 12, + "html_url": "https://github.com/eliesgalvira", + "login": "eliesgalvira" + }, + { + "contributions": 1, + "html_url": "https://github.com/D6player", + "login": "D6player" + } + ], + "created_at": "2024-11-30T21:48:04Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 1, + "files_root_entries": [ + { + "path": "README.md", + "size": 10, + "type": "file" + }, + { + "path": "profile", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 4, + "first_commit_date_default_branch": "2024-11-30T21:58:05Z", + "forks": 1, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [], + "last_commit_date_default_branch": "2024-12-01T13:39:36Z", + "last_commit_oid_default_branch": "e4c7dc2c0059544064b8b7c7e15a052836c165b9", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "SolomonTracker/.github", + "owner": "SolomonTracker", + "parent_repo": null, + "parent_url": null, + "primary_language": null, + "project_foreign_key": "lhp_6d847edaaae535e7", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 1, + "pull_requests_total": 1, + "pushed_at": "2024-12-01T13:37:42Z", + "readme_length": 9, + "readme_text": "# .github", + "readme_title": ".github", + "releases_count": 0, + "repo": ".github", + "repo_name": ".github", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T13:37:46Z", + "url": "https://github.com/SolomonTracker/.github", + "watchers": 0 + }, + "https://github.com/SolomonTracker/bobstelemetry": { + "commit_count_default_branch": 1, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 1, + "html_url": "https://github.com/D6player", + "login": "D6player" + } + ], + "created_at": "2024-12-01T10:49:40Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": "final.py", + "size": 1701, + "type": "file" + } + ], + "files_total_count": 1, + "first_commit_date_default_branch": "2024-12-01T10:52:56Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": false, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 1701 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:52:56Z", + "last_commit_oid_default_branch": "657d2dae909dc952b77e01887761ca51843bf837", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "SolomonTracker/bobstelemetry", + "owner": "SolomonTracker", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_6d847edaaae535e7", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:51:07Z", + "readme_length": null, + "readme_text": null, + "readme_title": null, + "releases_count": 0, + "repo": "bobstelemetry", + "repo_name": "bobstelemetry", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T10:51:10Z", + "url": "https://github.com/SolomonTracker/bobstelemetry", + "watchers": 0 + }, + "https://github.com/SolomonTracker/bobstracker": { + "commit_count_default_branch": 19, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 19, + "html_url": "https://github.com/D6player", + "login": "D6player" + } + ], + "created_at": "2024-11-30T17:17:56Z", + "default_branch": "main", + "description": "Coding theory applied to BOBST packaging system LauzHack challenge", + "dirs_total_count": 154, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 17, + "type": "file" + }, + { + "path": "demo.fish", + "size": 370, + "type": "file" + }, + { + "path": "demo.sh", + "size": 367, + "type": "file" + }, + { + "path": "demo", + "size": 0, + "type": "dir" + }, + { + "path": "execute.py", + "size": 6156, + "type": "file" + }, + { + "path": "execute_bk.py", + "size": 2646, + "type": "file" + }, + { + "path": "out_test.png", + "size": 45844, + "type": "file" + }, + { + "path": "out_toy_ex.png", + "size": 123, + "type": "file" + }, + { + "path": "processing.py", + "size": 2643, + "type": "file" + }, + { + "path": "requirements.txt", + "size": 3048, + "type": "file" + }, + { + "path": "test.png", + "size": 46894, + "type": "file" + }, + { + "path": "test_orig.png", + "size": 111126, + "type": "file" + }, + { + "path": "toy_ex.png", + "size": 4256, + "type": "file" + }, + { + "path": "venv", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 1484, + "first_commit_date_default_branch": "2024-11-30T13:54:22Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": false, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 14941455 + }, + { + "language": "C", + "size": 377276 + }, + { + "language": "Cython", + "size": 103847 + }, + { + "language": "C++", + "size": 85980 + }, + { + "language": "Fortran", + "size": 37029 + }, + { + "language": "PowerShell", + "size": 9033 + }, + { + "language": "Meson", + "size": 4589 + }, + { + "language": "Shell", + "size": 3878 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:30:32Z", + "last_commit_oid_default_branch": "b5bd9f5e704db69a6d86bcdcc99c45b2e4b80b8c", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "SolomonTracker/bobstracker", + "owner": "SolomonTracker", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_6d847edaaae535e7", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:28:50Z", + "readme_length": null, + "readme_text": null, + "readme_title": null, + "releases_count": 0, + "repo": "bobstracker", + "repo_name": "bobstracker", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T10:28:59Z", + "url": "https://github.com/SolomonTracker/bobstracker", + "watchers": 0 + }, + "https://github.com/SpaceMercury/LauzHawkathon": { + "commit_count_default_branch": 83, + "contributors_count": 4, + "contributors_top": [ + { + "contributions": 31, + "html_url": "https://github.com/SpaceMercury", + "login": "SpaceMercury" + }, + { + "contributions": 24, + "html_url": "https://github.com/NFont0", + "login": "NFont0" + }, + { + "contributions": 21, + "html_url": "https://github.com/JeremyJGut", + "login": "JeremyJGut" + }, + { + "contributions": 7, + "html_url": "https://github.com/MishkaNastia", + "login": "MishkaNastia" + } + ], + "created_at": "2024-11-30T12:30:07Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 6, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 3183, + "type": "file" + }, + { + "path": "README.md", + "size": 2994, + "type": "file" + }, + { + "path": "app.py", + "size": 2211, + "type": "file" + }, + { + "path": "models", + "size": 0, + "type": "dir" + }, + { + "path": "notebooks", + "size": 0, + "type": "dir" + }, + { + "path": "requirements.txt", + "size": 23, + "type": "file" + }, + { + "path": "static", + "size": 0, + "type": "dir" + }, + { + "path": "templates", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 26, + "first_commit_date_default_branch": "2024-11-30T12:30:08Z", + "forks": 1, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 2911841 + }, + { + "language": "JavaScript", + "size": 15398 + }, + { + "language": "CSS", + "size": 8013 + }, + { + "language": "HTML", + "size": 4753 + }, + { + "language": "Python", + "size": 2211 + } + ], + "last_commit_date_default_branch": "2024-12-01T07:03:58Z", + "last_commit_oid_default_branch": "0f33d56fa632dc373000111ffc8431ea8969ee0b", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "SpaceMercury/LauzHawkathon", + "owner": "SpaceMercury", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_dbb20f15cf0822af", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T07:04:05Z", + "readme_length": 2994, + "readme_text": "# LauzHawkathon\n\n\n\n# LauzHawkathon\n\nThis project will be for time series forecasting. It aims to develop models and algorithms to predict future values based on historical data.# LauzHawkathon\n\n## Tasks\n\n- [ ] **Define the Problem Statement**\n - [x] Clearly outline the objectives and goals of the forecasting project.\n - [ ] Identify the key metrics for evaluation.\n\n- [x] **Data Collection**\n - [x] Gather historical data relevant to the forecasting problem.\n - [x] Ensure data quality and completeness.\n\n- [x] **Data Preprocessing**\n - [x] Handle missing values and outliers.\n - [x] Normalize or standardize the data if necessary.\n - [x] Split the data into training and testing sets.\n\n- [x] **Exploratory Data Analysis (EDA)**\n - [x] Visualize the data to understand trends, seasonality, and patterns.\n - [x] Perform statistical analysis to gain insights.\n\n- [x] **Feature Engineering**\n - [x] Create new features that may help improve the model's performance.\n - [x] Select the most relevant features for the model.\n\n- [] **Model Selection**\n - [ ] Choose appropriate time series forecasting models (e.g., ARIMA, LSTM, Prophet).\n - [ ] Justify the choice of models based on the problem and data characteristics.\n\n- [ ] **Model Training**\n - [ ] Train the selected models on the training data.\n - [ ] Tune hyperparameters to optimize model performance.\n\n- [ ] **Model Evaluation**\n - [ ] Evaluate the models using the testing data.\n - [ ] Compare model performance using metrics such as MAE, RMSE, and MAPE.\n\n- [ ] **Model Deployment**\n - [ ] Deploy the best-performing model to a production environment.\n - [ ] Set up a pipeline for continuous monitoring and updating of the model.\nComprehensive User Interface (UI):\n\n- [x] **Intuitive UI**\n - [x]Includes visualization features for historical data, trends, and exploratory analysis.\n - [x]Responsive design for seamless use across various devices.\n - [x]Code Clarity and Maintainability:\n\n- [x] **Maintainability**\n - [x]Well-documented functions and modules for ease of understanding and collaboration.\n - [x]Modular architecture to enable scalability and ease of updates.\n - [x]Test-Driven Development (TDD):\n\n- [x] **Code reliability**\n - [x] High test coverage achieved across key modules.\n - [x] Continuous integration pipeline set up for automated testing and error detection.\n - [x] Data Quality and Integrity: Comprehensive preprocessing pipeline to handle missing values, outliers, and data inconsistencies. Statistical and visual checks integrated to ensure data completeness and readiness for modeling.\n \n- [x] **Documentation**\n - [x] Document the entire process, including data sources, preprocessing steps, model selection, and evaluation results.\n - [x] Update the `README.md` file with relevant information and instructions.\n\n- [ ] **Maintenance**\n - [ ] Monitor the model's performance over time.\n - [ ] Update the model as new data becomes available or as the underlying patterns change.", + "readme_title": "LauzHawkathon", + "releases_count": 0, + "repo": "LauzHawkathon", + "repo_name": "LauzHawkathon", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T07:04:09Z", + "url": "https://github.com/SpaceMercury/LauzHawkathon", + "watchers": 1 + }, + "https://github.com/Stargix/UBS-LauzHack": { + "commit_count_default_branch": 73, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 29, + "html_url": "https://github.com/gallego-c", + "login": "gallego-c" + }, + { + "contributions": 26, + "html_url": "https://github.com/paulaa2", + "login": "paulaa2" + }, + { + "contributions": 18, + "html_url": "https://github.com/Stargix", + "login": "Stargix" + } + ], + "created_at": "2024-11-30T13:12:34Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 3, + "files_root_entries": [ + { + "path": "FINAL.ipynb", + "size": 316911, + "type": "file" + }, + { + "path": "Graphs", + "size": 0, + "type": "dir" + }, + { + "path": "README.md", + "size": 2420, + "type": "file" + }, + { + "path": "Similituds_nom.py", + "size": 6031, + "type": "file" + }, + { + "path": "__pycache__", + "size": 0, + "type": "dir" + }, + { + "path": "data", + "size": 0, + "type": "dir" + }, + { + "path": "filtered_clusters.xlsx", + "size": 208452, + "type": "file" + }, + { + "path": "main sergi.ipynb", + "size": 1342326, + "type": "file" + }, + { + "path": "web.py", + "size": 985, + "type": "file" + } + ], + "files_total_count": 560, + "first_commit_date_default_branch": "2024-11-30T13:15:36Z", + "forks": 1, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 1659237 + }, + { + "language": "Python", + "size": 7016 + } + ], + "last_commit_date_default_branch": "2025-04-23T20:45:50Z", + "last_commit_oid_default_branch": "929f69ffc20ab642a43ebe7083cc953f223cf8a4", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "Stargix/UBS-LauzHack", + "owner": "Stargix", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_f83f4b12fdd04201", + "pull_requests_closed": 0, + "pull_requests_merged": 1, + "pull_requests_open": 0, + "pull_requests_total": 1, + "pushed_at": "2025-04-23T20:45:51Z", + "readme_length": 2418, + "readme_text": "# Entity Resolution System\n\n## Transaction Identity Matching for Financial Services\n\nAn advanced entity resolution model developed during LauzHack 2024 in Switzerland that identifies and groups transactions belonging to the same external entities, even when their true identities are obscured.\n\n## Project Overview\n\nThis project was created in response to UBS's challenge at LauzHack 2024. Our system employs sophisticated modeling techniques to uncover hidden relationships between financial transactions, allowing for accurate entity mapping despite identity obfuscation.\n\n## Key Features\n\n- **Identity Matching**: Identifies when seemingly separate transactions belong to the same external entity\n- **Transaction Clustering**: Groups related transactions to reveal patterns and relationships\n- **Entity Resolution**: Uncovers true identities of external parties across multiple transactions\n- **Pattern Recognition**: Detects common signatures that indicate same-entity origin\n\n## Technical Challenge\n\nThe project presented several complex technical hurdles:\n1. Working with obfuscated identity data\n2. Creating reliable matching algorithms despite limited identifiers\n3. Balancing precision and recall in entity resolution\n4. Processing and analyzing large transaction datasets efficiently\n\n## Development Process\n\nOur team tackled this ambitious challenge by:\n- Analyzing transaction patterns to identify potential identity markers\n- Developing algorithmic approaches to match entities across different transactions\n- Creating clustering methods to group transactions by probable entity\n- Testing and refining our models under tight hackathon constraints\n\n## Applications\n\nThis entity resolution system has potential applications in:\n- Anti-money laundering (AML) operations\n- Fraud detection\n- Customer relationship management\n- Regulatory compliance\n- Risk assessment\n\n## Team Members\n\n- Paula Esteve\n- Sergi Flores\n- Clàudia Gallego\n\n## Acknowledgements\n\nSpecial thanks to UBS for presenting such a challenging and educational problem, and to the LauzHack 2024 organizers for creating an outstanding event environment that fostered innovation and collaboration.\n\n## Learning Outcomes\n\nThe project provided valuable experience in:\n- Advanced modeling techniques\n- Problem-solving under pressure\n- Cross-functional team collaboration\n- Handling complex financial data structures\n- Entity resolution methodologies", + "readme_title": "Entity Resolution System", + "releases_count": 0, + "repo": "UBS-LauzHack", + "repo_name": "UBS-LauzHack", + "stars": 1, + "topics": [], + "updated_at": "2025-12-12T23:16:25Z", + "url": "https://github.com/Stargix/UBS-LauzHack", + "watchers": 1 + }, + "https://github.com/StefanPetersTM/LauzHack2024": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'StefanPetersTM/LauzHack2024'.\"}]", + "owner": "StefanPetersTM", + "project_foreign_key": "lhp_9a0b4bc57ca6655b", + "repo": "LauzHack2024" + }, + "https://github.com/TheCrew-lh24/analysis": { + "commit_count_default_branch": 4, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 4, + "html_url": "https://github.com/AryanAhadinia", + "login": "AryanAhadinia" + } + ], + "created_at": "2024-11-30T21:54:42Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 12, + "type": "file" + }, + { + "path": "main.ipynb", + "size": 119268, + "type": "file" + }, + { + "path": "mini_challenge.ipynb", + "size": 79075, + "type": "file" + }, + { + "path": "run.sh", + "size": 1796, + "type": "file" + }, + { + "path": "stage_1.py", + "size": 9327, + "type": "file" + } + ], + "files_total_count": 5, + "first_commit_date_default_branch": "2024-11-30T21:55:31Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": false, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 198343 + }, + { + "language": "Python", + "size": 9327 + }, + { + "language": "Shell", + "size": 1796 + } + ], + "last_commit_date_default_branch": "2024-12-01T06:06:55Z", + "last_commit_oid_default_branch": "74724c899d242c17c91a1a1f2dd2d39441f7dd4e", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "TheCrew-lh24/analysis", + "owner": "TheCrew-lh24", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_09436c552d4833ad", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T06:06:57Z", + "readme_length": null, + "readme_text": null, + "readme_title": null, + "releases_count": 0, + "repo": "analysis", + "repo_name": "analysis", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T10:58:37Z", + "url": "https://github.com/TheCrew-lh24/analysis", + "watchers": 0 + }, + "https://github.com/TheCrew-lh24/data-parser": { + "commit_count_default_branch": 7, + "contributors_count": 2, + "contributors_top": [ + { + "contributions": 4, + "html_url": "https://github.com/Manaf941", + "login": "Manaf941" + }, + { + "contributions": 3, + "html_url": "https://github.com/phorcys420", + "login": "phorcys420" + } + ], + "created_at": "2024-11-30T13:37:15Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 4, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 58, + "type": "file" + }, + { + "path": ".prettierrc", + "size": 40, + "type": "file" + }, + { + "path": "README.md", + "size": 230, + "type": "file" + }, + { + "path": "data", + "size": 0, + "type": "dir" + }, + { + "path": "jsconfig.json", + "size": 635, + "type": "file" + }, + { + "path": "package.json", + "size": 159, + "type": "file" + }, + { + "path": "pnpm-lock.yaml", + "size": 635, + "type": "file" + }, + { + "path": "src", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 10, + "first_commit_date_default_branch": "2024-11-30T18:45:49Z", + "forks": 1, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "JavaScript", + "size": 6576 + } + ], + "last_commit_date_default_branch": "2024-11-30T23:27:23Z", + "last_commit_oid_default_branch": "f69573ea3663a1501accc2c79fb820fc3bb94624", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "TheCrew-lh24/data-parser", + "owner": "TheCrew-lh24", + "parent_repo": null, + "parent_url": null, + "primary_language": "JavaScript", + "project_foreign_key": "lhp_09436c552d4833ad", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-11-30T23:31:37Z", + "readme_length": 229, + "readme_text": "# data-parser\n\nTo install dependencies:\n\n```bash\nbun install\n```\n\nTo run:\n\n```bash\nbun run src/index.js\n```\n\nThis project was created using `bun init` in bun v1.1.38. [Bun](https://bun.sh) is a fast all-in-one JavaScript runtime.", + "readme_title": "data-parser", + "releases_count": 0, + "repo": "data-parser", + "repo_name": "data-parser", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T10:58:53Z", + "url": "https://github.com/TheCrew-lh24/data-parser", + "watchers": 0 + }, + "https://github.com/TheCrew-lh24/data-parser2": { + "commit_count_default_branch": 4, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 4, + "html_url": "https://github.com/Manaf941", + "login": "Manaf941" + } + ], + "created_at": "2024-12-01T01:58:58Z", + "default_branch": "master", + "description": "asd", + "dirs_total_count": 4, + "files_root_entries": [ + { + "path": ".eslintignore", + "size": 17, + "type": "file" + }, + { + "path": ".eslintrc.cjs", + "size": 952, + "type": "file" + }, + { + "path": ".github", + "size": 0, + "type": "dir" + }, + { + "path": ".gitignore", + "size": 33, + "type": "file" + }, + { + "path": "README.md", + "size": 0, + "type": "file" + }, + { + "path": "out", + "size": 323, + "type": "file" + }, + { + "path": "package.json", + "size": 885, + "type": "file" + }, + { + "path": "pnpm-lock.yaml", + "size": 65052, + "type": "file" + }, + { + "path": "src", + "size": 0, + "type": "dir" + }, + { + "path": "tsconfig.json", + "size": 435, + "type": "file" + } + ], + "files_total_count": 19, + "first_commit_date_default_branch": "2024-12-01T01:59:00Z", + "forks": 0, + "has_ci": true, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "TypeScript", + "size": 22424 + }, + { + "language": "JavaScript", + "size": 952 + } + ], + "last_commit_date_default_branch": "2024-12-01T08:38:25Z", + "last_commit_oid_default_branch": "8385d63e7772489a10fc80e09382112455a64e2d", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "TheCrew-lh24/data-parser2", + "owner": "TheCrew-lh24", + "parent_repo": null, + "parent_url": null, + "primary_language": "TypeScript", + "project_foreign_key": "lhp_09436c552d4833ad", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T08:38:31Z", + "readme_length": null, + "readme_text": null, + "readme_title": null, + "releases_count": 0, + "repo": "data-parser2", + "repo_name": "data-parser2", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T10:58:02Z", + "url": "https://github.com/TheCrew-lh24/data-parser2", + "watchers": 1 + }, + "https://github.com/TomasGadea/lauzhack2024": { + "commit_count_default_branch": 71, + "contributors_count": 4, + "contributors_top": [ + { + "contributions": 29, + "html_url": "https://github.com/marcfranquesa", + "login": "marcfranquesa" + }, + { + "contributions": 23, + "html_url": "https://github.com/puigde", + "login": "puigde" + }, + { + "contributions": 10, + "html_url": "https://github.com/PauMatas", + "login": "PauMatas" + }, + { + "contributions": 9, + "html_url": "https://github.com/TomasGadea", + "login": "TomasGadea" + } + ], + "created_at": "2024-11-30T10:55:06Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 12, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 408, + "type": "file" + }, + { + "path": ".prettierrc", + "size": 88, + "type": "file" + }, + { + "path": "README.md", + "size": 3519, + "type": "file" + }, + { + "path": "app.json", + "size": 2132, + "type": "file" + }, + { + "path": "app", + "size": 0, + "type": "dir" + }, + { + "path": "assets", + "size": 0, + "type": "dir" + }, + { + "path": "components", + "size": 0, + "type": "dir" + }, + { + "path": "constants", + "size": 0, + "type": "dir" + }, + { + "path": "hooks", + "size": 0, + "type": "dir" + }, + { + "path": "package-lock.json", + "size": 723366, + "type": "file" + }, + { + "path": "package.json", + "size": 2269, + "type": "file" + }, + { + "path": "scripts", + "size": 0, + "type": "dir" + }, + { + "path": "tsconfig.json", + "size": 232, + "type": "file" + } + ], + "files_total_count": 52, + "first_commit_date_default_branch": "2024-11-30T10:59:01Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": true, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "TypeScript", + "size": 36784 + }, + { + "language": "JavaScript", + "size": 2855 + } + ], + "last_commit_date_default_branch": "2024-12-01T11:15:03Z", + "last_commit_oid_default_branch": "af120499f91aeceab1e690eee92fd08aff58d6e3", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "TomasGadea/lauzhack2024", + "owner": "TomasGadea", + "parent_repo": null, + "parent_url": null, + "primary_language": "TypeScript", + "project_foreign_key": "lhp_0bded93db67df1f7", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-04T16:58:17Z", + "readme_length": 3474, + "readme_text": "![lirica](./assets/images/lirica.png)\n\n# Lirica: Teleprompter for Influencers\n\n## _Stay on script, shine on screen—use Lirica!_\n\n### 🏆 **Project Pitch**\n\nIn a world where video content dominates social media, influencers are constantly crafting perfect, engaging scripts to capture their audience's attention. But keeping track of those scripts while recording? That’s a challenge.\n\n**Use Lirica**: a mobile app tailored for influencers who create scripted video content. \nWith Lirica, your phone becomes your personal teleprompter, seamlessly scrolling through your script while you record. No more fumbling with papers, forgetting lines, or losing focus. Lirica ensures you stay confident, professional, and connected with your audience.\n\nWhether you’re filming a product ad, storytelling, or delivering a heartfelt message, Lirica takes the stress out of memorization, so you can focus on creating and being yourself.\n\n---\n\n### 🚀 **Getting Started**\n\nFollow these steps to run the demo for Lirica:\n\n1. **Prerequisites**:\n\n - Make sure you have Node.js and Expo installed on your system.\n\n2. **Clone the Repository**:\n\n ```bash\n git clone https://github.com/your-username/lirica.git\n cd lirica\n ```\n\n3. **Install dependencies**:\n\n ```bash\n npm install\n ```\n\n4. **Simulate it on iOS**:\n ```bash\n npx expo run:ios\n ```\n\n---\n\n### 🛠️ Features\n- Script Sync: Type or paste your script directly in the app. Lirica will scroll it automatically at your preferred pace.\n- Seamless Recording: Record high-quality videos while following the script.\n- User-Friendly Interface: A clean, intuitive UI designed for effortless navigation.\n- Quick share: Create you video and share it on any social media app instantly.\n- Customizable Display: Adjust scrolling speed to suit your needs.\n\n---\n\n### 📚 Technical Overview\n\n- Framework: Built using Expo for a smooth cross-platform experience.\n Core Technologies: React Native and Expo CLI.\n- Video Integration: Leverages native camera capabilities to ensure flawless recordings.\n- Audio Speaking detector model:\n - Extract features from original signal:\n - RMS of signal window.\n - Zero-crossing rate: Number of time-domain zero-crossings per secind.\n - Difference in amplitude between maximum peak and previous minimum peak within an audio frame.\n - Difference in amplitude between maximum peak and following minimum peak within an audio frame.\n > Samouelian, Ara et al. “Speech, silence, music and noise classification of TV broadcast material.” 5th International Conference on Spoken Language Processing (ICSLP 1998) (1998): n. pag.\n\n---\n\n### 🎯 Future Scope\n\nWhile Lirica is designed for influencers, the potential applications are limitless:\n\n- Public speakers practicing for events.\n- Educators recording lessons or tutorials.\n- Marketers creating dynamic, scripted ad campaigns.\n\nUpcoming features include:\n\n- Integration with cloud storage for scripts.\n- AI-assisted script generation, optimization and evaluation.\n\n### 👥 Meet the Team\n\n- Pol Puigdemont i Plana\n- Marc Franquesa i Monés\n- Tomás Gadea Alcaide\n- Pau Matas i Albiol\n\n---\n\n### 📬 Feedback & Contributions\n\nWe’d love to hear your thoughts! For feedback, suggestions, or contributions:\n\nEmail: [contact@lirica.app](mailto:contact@marcfranquesa.com)\n\n---\n\nLet’s revolutionize video creation, one script at a time.\n\nThank you for considering Lirica for this hackathon. Together, we make advertising simple. 🎥✨", + "readme_title": "Lirica: Teleprompter for Influencers", + "releases_count": 0, + "repo": "lauzhack2024", + "repo_name": "lauzhack2024", + "stars": 2, + "topics": [], + "updated_at": "2025-05-01T21:27:15Z", + "url": "https://github.com/TomasGadea/lauzhack2024", + "watchers": 1 + }, + "https://github.com/VictorDeLamo/lh-bobst-challenge": { + "commit_count_default_branch": 21, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 15, + "html_url": "https://github.com/masep01", + "login": "masep01" + }, + { + "contributions": 4, + "html_url": null, + "login": "Victor de Lamo" + }, + { + "contributions": 2, + "html_url": "https://github.com/surinyach", + "login": "surinyach" + } + ], + "created_at": "2024-11-30T16:25:42Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 7, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 13, + "type": "file" + }, + { + "path": "README.md", + "size": 73, + "type": "file" + }, + { + "path": "main.py", + "size": 10175, + "type": "file" + }, + { + "path": "webapp", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 27, + "first_commit_date_default_branch": "2024-11-30T16:52:59Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 10175 + }, + { + "language": "JavaScript", + "size": 8956 + }, + { + "language": "CSS", + "size": 2178 + }, + { + "language": "HTML", + "size": 1721 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:55:43Z", + "last_commit_oid_default_branch": "002bc5d508a6c63a70ee9f5fd36db7448f2e0621", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "VictorDeLamo/lh-bobst-challenge", + "owner": "VictorDeLamo", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_a1133885c17b3740", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:55:53Z", + "readme_length": 72, + "readme_text": "# Lauzhack 2024\n\nBobst Challenge\n\nTeam:\n- Isaac\n- Santi\n- Victor\n- Josep", + "readme_title": "Lauzhack 2024", + "releases_count": 0, + "repo": "lh-bobst-challenge", + "repo_name": "lh-bobst-challenge", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T10:55:56Z", + "url": "https://github.com/VictorDeLamo/lh-bobst-challenge", + "watchers": 1 + }, + "https://github.com/VictorPaniello/bms-lauzhack-2024": { + "commit_count_default_branch": 12, + "contributors_count": 2, + "contributors_top": [ + { + "contributions": 9, + "html_url": "https://github.com/VictorPaniello", + "login": "VictorPaniello" + }, + { + "contributions": 3, + "html_url": "https://github.com/gerardm27", + "login": "gerardm27" + } + ], + "created_at": "2024-11-30T13:20:30Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 6, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 622, + "type": "file" + }, + { + "path": "README.md", + "size": 2797, + "type": "file" + }, + { + "path": "app", + "size": 0, + "type": "dir" + }, + { + "path": "jsconfig.json", + "size": 73, + "type": "file" + }, + { + "path": "next.config.mjs", + "size": 92, + "type": "file" + }, + { + "path": "package-lock.json", + "size": 213382, + "type": "file" + }, + { + "path": "package.json", + "size": 705, + "type": "file" + }, + { + "path": "postcss.config.mjs", + "size": 135, + "type": "file" + }, + { + "path": "public", + "size": 0, + "type": "dir" + }, + { + "path": "server.js", + "size": 1020, + "type": "file" + }, + { + "path": "tailwind.config.js", + "size": 366, + "type": "file" + } + ], + "files_total_count": 29, + "first_commit_date_default_branch": "2024-11-30T13:20:30Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "JavaScript", + "size": 15518 + }, + { + "language": "Python", + "size": 7768 + }, + { + "language": "CSS", + "size": 7076 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:53:14Z", + "last_commit_oid_default_branch": "b6de60588597284fe2b719e3db0a4ac86ca63441", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "VictorPaniello/bms-lauzhack-2024", + "owner": "VictorPaniello", + "parent_repo": null, + "parent_url": null, + "primary_language": "JavaScript", + "project_foreign_key": "lhp_3631a2b20419f296", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:53:15Z", + "readme_length": 2796, + "readme_text": "This project is a Next.js application developed to display interactive time series forecasting for the sales data of Bristol Myers Squibb. The primary dataset used for this analysis is INNOVIX_Floresland.xlsx.\n\nFirst of all, we have made an intense preprocessing with Python in order to have all the data in one sheet, instead of having one variable per sheet. With this preprocessing, we have used a KNN in order to impute missing values. Then, three distinct models were explored to forecast the time series:\n\n- Long Short-Term Memory (LSTM): A neural network-based approach suited for sequential data.\n- Exponential Smoothing State Space Model (ETS): A robust statistical method for time series analysis.\n- Autoregressive Integrated Moving Average (ARIMA): A widely-used statistical model for forecasting time-dependent data.\n\nAfter evaluating the performance of these models, ARIMA emerged as the most accurate model. It was subsequently chosen for forecasting the sales data.\n\nWe also have made a webpage in Next.js in where we can upload our data and it will forecast it automatically by connecting to a Node.js backend. You can also change data interactively in the page, and arrange some parameters. It is visually attractive and simple. \n\nIt is a user-friendly interface, designed to be visually attraactive and straightforward.\n\nThis is a [Next.js](https://nextjs.org) project bootstrapped with [`create-next-app`](https://github.com/vercel/next.js/tree/canary/packages/create-next-app).\n\n## Getting Started\n\nFirst, run the development server:\n\n```bash\nnpm run dev\n# or\nyarn dev\n# or\npnpm dev\n# or\nbun dev\n```\n\nOpen [http://localhost:3000](http://localhost:3000) with your browser to see the result.\n\nYou can start editing the page by modifying `app/page.js`. The page auto-updates as you edit the file.\n\nThis project uses [`next/font`](https://nextjs.org/docs/app/building-your-application/optimizing/fonts) to automatically optimize and load [Geist](https://vercel.com/font), a new font family for Vercel.\n\n## Learn More\n\nTo learn more about Next.js, take a look at the following resources:\n\n- [Next.js Documentation](https://nextjs.org/docs) - learn about Next.js features and API.\n- [Learn Next.js](https://nextjs.org/learn) - an interactive Next.js tutorial.\n\nYou can check out [the Next.js GitHub repository](https://github.com/vercel/next.js) - your feedback and contributions are welcome!\n\n## Deploy on Vercel\n\nThe easiest way to deploy your Next.js app is to use the [Vercel Platform](https://vercel.com/new?utm_medium=default-template&filter=next.js&utm_source=create-next-app&utm_campaign=create-next-app-readme) from the creators of Next.js.\n\nCheck out our [Next.js deployment documentation](https://nextjs.org/docs/app/building-your-application/deploying) for more details.", + "readme_title": "or", + "releases_count": 0, + "repo": "bms-lauzhack-2024", + "repo_name": "bms-lauzhack-2024", + "stars": 1, + "topics": [], + "updated_at": "2024-12-09T23:42:32Z", + "url": "https://github.com/VictorPaniello/bms-lauzhack-2024", + "watchers": 1 + }, + "https://github.com/YannickDetrois/UBS_LauzHack": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'YannickDetrois/UBS_LauzHack'.\"}]", + "owner": "YannickDetrois", + "project_foreign_key": "lhp_8395727a913a5db1", + "repo": "UBS_LauzHack" + }, + "https://github.com/Zakhurf/Smoles": { + "commit_count_default_branch": 10, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 10, + "html_url": "https://github.com/bogdan-boucher", + "login": "bogdan-boucher" + } + ], + "created_at": "2024-11-30T18:38:59Z", + "default_branch": "main", + "description": "Smart insole connected to an app", + "dirs_total_count": 65, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 709, + "type": "file" + }, + { + "path": "README.md", + "size": 246, + "type": "file" + }, + { + "path": "smoles", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 138, + "first_commit_date_default_branch": "2024-11-30T18:38:59Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "C++", + "size": 23759 + }, + { + "language": "CMake", + "size": 19408 + }, + { + "language": "Dart", + "size": 14088 + }, + { + "language": "Swift", + "size": 1702 + }, + { + "language": "C", + "size": 1425 + }, + { + "language": "HTML", + "size": 1216 + }, + { + "language": "Kotlin", + "size": 119 + }, + { + "language": "Objective-C", + "size": 38 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:06:06Z", + "last_commit_oid_default_branch": "de1b5e0fbdf57d90cb6f975cb207b327026a5ff4", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "bogdan-boucher/Smoles", + "owner": "Zakhurf", + "parent_repo": null, + "parent_url": null, + "primary_language": "C++", + "project_foreign_key": "lhp_cec2f81973a6f19a", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:36:36Z", + "readme_length": 245, + "readme_text": "# Smoles\nSmart insole connected to an app for a Hackathon.\nIn developpement (things should be added later)\n\nA preview of the thing so far :\n\n", + "readme_title": "Smoles", + "releases_count": 0, + "repo": "Smoles", + "repo_name": "Smoles", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T10:06:10Z", + "url": "https://github.com/bogdan-boucher/Smoles", + "watchers": 1 + }, + "https://github.com/Zpidero/lauzhack2024-v2": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'Zpidero/lauzhack2024-v2'.\"}]", + "owner": "Zpidero", + "project_foreign_key": "lhp_639c9f2716de3ba1", + "repo": "lauzhack2024-v2" + }, + "https://github.com/acanadil/LauzRaspberry": { + "commit_count_default_branch": 22, + "contributors_count": 4, + "contributors_top": [ + { + "contributions": 9, + "html_url": "https://github.com/acanadil", + "login": "acanadil" + }, + { + "contributions": 6, + "html_url": "https://github.com/cucu48", + "login": "cucu48" + }, + { + "contributions": 4, + "html_url": "https://github.com/bystepii", + "login": "bystepii" + }, + { + "contributions": 3, + "html_url": null, + "login": "Claudia Altadill" + } + ], + "created_at": "2024-11-30T14:13:03Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 63, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 5, + "type": "file" + }, + { + "path": "App", + "size": 0, + "type": "dir" + }, + { + "path": "Backend", + "size": 0, + "type": "dir" + }, + { + "path": "README.md", + "size": 391, + "type": "file" + } + ], + "files_total_count": 142, + "first_commit_date_default_branch": "2024-11-30T15:50:08Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "C++", + "size": 23070 + }, + { + "language": "CMake", + "size": 18778 + }, + { + "language": "Jupyter Notebook", + "size": 17992 + }, + { + "language": "Python", + "size": 16135 + }, + { + "language": "Dart", + "size": 8114 + }, + { + "language": "HTML", + "size": 1859 + }, + { + "language": "Swift", + "size": 1728 + }, + { + "language": "C", + "size": 1425 + }, + { + "language": "Kotlin", + "size": 133 + }, + { + "language": "Objective-C", + "size": 38 + } + ], + "last_commit_date_default_branch": "2024-12-09T11:34:59Z", + "last_commit_oid_default_branch": "ca617fe57084e1fda3ad22fed9db9f463a319c13", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "acanadil/LauzRaspberry", + "owner": "acanadil", + "parent_repo": null, + "parent_url": null, + "primary_language": "C++", + "project_foreign_key": "lhp_86fc1f7eca26e147", + "pull_requests_closed": 1, + "pull_requests_merged": 1, + "pull_requests_open": 0, + "pull_requests_total": 2, + "pushed_at": "2024-12-09T11:37:24Z", + "readme_length": 390, + "readme_text": "# LauzBerry\n\n## Backend\n\nTo exectute the backend code, you need to have the following libraries installed: HOLA\n\n- gpiozero\n- rpi-lgpio\n- ina219\n- azure-iot-device\n- flask\n\nRun the following command to start the backend server:\n\n```bash\ncd Backend && python3 main.py\n```\n\n## Frontend\n\nThe frontend is built using Dart and Flutter. Use any IDE that supports Flutter to run the frontend code.", + "readme_title": "LauzBerry", + "releases_count": 0, + "repo": "LauzRaspberry", + "repo_name": "LauzRaspberry", + "stars": 0, + "topics": [], + "updated_at": "2024-12-09T11:35:03Z", + "url": "https://github.com/acanadil/LauzRaspberry", + "watchers": 2 + }, + "https://github.com/alexcaldarone/lauzhack-2024": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'alexcaldarone/lauzhack-2024'.\"}]", + "owner": "alexcaldarone", + "project_foreign_key": "lhp_32ec6aa87783f726", + "repo": "lauzhack-2024" + }, + "https://github.com/aminecheikh/UBSChallengeLauzHack24": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'aminecheikh/UBSChallengeLauzHack24'.\"}]", + "owner": "aminecheikh", + "project_foreign_key": "lhp_581474b5bdc82b31", + "repo": "UBSChallengeLauzHack24" + }, + "https://github.com/anirudhhramesh/vitol-python-backend": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'anirudhhramesh/vitol-python-backend'.\"}]", + "owner": "anirudhhramesh", + "project_foreign_key": "lhp_f98712a88129ad92", + "repo": "vitol-python-backend" + }, + "https://github.com/arnau-m/OutBoxers": { + "commit_count_default_branch": 11, + "contributors_count": 2, + "contributors_top": [ + { + "contributions": 7, + "html_url": "https://github.com/JSantosSP", + "login": "JSantosSP" + }, + { + "contributions": 4, + "html_url": "https://github.com/arnau-m", + "login": "arnau-m" + } + ], + "created_at": "2024-11-30T16:41:38Z", + "default_branch": "main", + "description": "Thinking outside the box to avoid surprises inside the box", + "dirs_total_count": 10, + "files_root_entries": [ + { + "path": "README.md", + "size": 4287, + "type": "file" + }, + { + "path": "appOutBoxers", + "size": 0, + "type": "dir" + }, + { + "path": "classes", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 31, + "first_commit_date_default_branch": "2024-11-30T16:41:38Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 30892 + }, + { + "language": "JavaScript", + "size": 13338 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:57:10Z", + "last_commit_oid_default_branch": "9f248d4fa819d73b3d37b5aad1d9b9e46891c992", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "arnau-m/OutBoxers", + "owner": "arnau-m", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_06b7539d57b5babc", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:57:18Z", + "readme_length": 4274, + "readme_text": "# OutBoxers - Smart Conveyor Belt System \n\nWelcome to **OutBoxers**, our innovative solution developed during the Lauzhack hackathon for BOBST. This project combines hardware, software, and cloud integration to create an intelligent conveyor belt system capable of detecting, sorting, and analyzing box production in real time. \n\n---\n\n## System Overview \n\n### Hardware Functionality \n\n- **Adjustable Conveyor Belt Speed** \n The conveyor belt's speed is regulated using a rotary encoder, allowing dynamic adjustment to match production requirements. \n\n- **Defect Detection at the Start of the Conveyor** \n An **ultrasonic sensor** is positioned at the start of the belt to detect any irregularities in the boxes, such as incorrect dimensions or improper placement. \n\n- **Error Detection at the End of the Conveyor** \n An **infrared sensor** at the end of the conveyor identifies potential issues during transportation, such as misaligned or stuck boxes. \n\n- **Defective Box Diverter** \n If a box is identified as defective by the sensors, a **box diverter mechanism** reroutes it to a separate path at the end of the conveyor, ensuring smooth operation for non-defective boxes. \n\n- **Current Consumption Monitoring** \n A **current sensor** monitors the power consumption of the conveyor system, enabling real-time insights into energy efficiency and operational costs. \n\n---\n\n## Software Functionality \n\n- **Multithreading for Sensor and Motor Management** \n The software uses **multithreading** to manage sensors and motors in parallel, ensuring real-time control and responsiveness. \n\n- **Data Collection and Transmission** \n Key operational data—such as power consumption, production rate, and conveyor speed—are collected and sent to **Microsoft Azure** for storage and analysis. \n\n- **Mobile Application** \n A **mobile application** allows users to manage shifts, monitor system status, and interact with key performance indicators (KPIs). \n\n- **Automated Jobs Integration** \n Integration with **BOBST Connect** enables the execution of automated tasks, streamlining productivity and reducing manual intervention. \n\n---\n\n## Technical Highlights \n\n- **Hardware:** Rotary encoder, ultrasonic sensor, infrared sensor, current sensor, servo-controlled diverter. \n- **Software:** Python-based multithreading for real-time control, Azure integration for data logging, mobile app for management. \n- **Cloud Integration:** Microsoft Azure for storing and analyzing system metrics. \n- **Application Scope:** Operational insights, defect management, production reporting, and energy monitoring. \n\n---\n\n## Future Enhancements \n\nWhile we are proud of what we accomplished during the hackathon, there were additional ideas we could not implement due to time constraints: \n\n1. **Predictive Maintenance** \n - Using sensor and motor data to anticipate mechanical failures or identify wear and tear early. \n\n2. **Enhanced Connectivity with Mobile Application** \n - Real-time control of the conveyor belt and alert management directly from the mobile application. \n\n3. **Advanced Alarm System** \n - Integration of a robust alert system with the mobile app for instant notifications and quick issue resolution. \n\n---\n\n## How It Works \n\n1. Boxes enter the conveyor belt, and their dimensions and positioning are analyzed by the ultrasonic sensor. \n2. Boxes with detected defects are flagged for redirection. \n3. As the box progresses, an infrared sensor checks for additional errors at the end of the line. \n4. If the box is marked as defective, the diverter mechanism separates it from the normal production flow. \n5. The system continuously tracks speed, energy usage, and defect counts, sending this data to the cloud. \n6. The mobile app and automated job scheduler provide additional layers of control and operational insight. \n\n---\n\n## Future Potential \n\nThe OutBoxers system is scalable and modular, making it an ideal solution for modern industrial applications. With additional sensors or advanced AI integration, it can adapt to more complex scenarios and higher production volumes. \n\nWe hope this project inspires further innovation in smart manufacturing! \n\n---\n\n🎉 **Thank you for supporting our hackathon journey!** 🎉", + "readme_title": "OutBoxers - Smart Conveyor Belt System", + "releases_count": 0, + "repo": "OutBoxers", + "repo_name": "OutBoxers", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T10:57:21Z", + "url": "https://github.com/arnau-m/OutBoxers", + "watchers": 1 + }, + "https://github.com/batikanor/MX-Focus": { + "commit_count_default_branch": 16, + "contributors_count": 2, + "contributors_top": [ + { + "contributions": 9, + "html_url": "https://github.com/yangezheng", + "login": "yangezheng" + }, + { + "contributions": 7, + "html_url": "https://github.com/batikanor", + "login": "batikanor" + } + ], + "created_at": "2024-11-30T16:54:05Z", + "default_branch": "main", + "description": "Learn to retain your focus whilst writing an exam.", + "dirs_total_count": 57, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 44, + "type": "file" + }, + { + "path": "MX_Focus_Unity", + "size": 0, + "type": "dir" + }, + { + "path": "README.md", + "size": 5861, + "type": "file" + }, + { + "path": "muse", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 817, + "first_commit_date_default_branch": "2024-11-30T20:54:47Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "C#", + "size": 52239 + }, + { + "language": "Python", + "size": 7949 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:52:37Z", + "last_commit_oid_default_branch": "8a51a6a06b07ddea2936a92c0af52f18d5bd02a6", + "latest_release_date": "2024-12-01T10:51:06Z", + "latest_release_tag": "PoC", + "license_name": null, + "license_spdx": null, + "name_with_owner": "batikanor/MX-Focus", + "owner": "batikanor", + "parent_repo": null, + "parent_url": null, + "primary_language": "C#", + "project_foreign_key": "lhp_cff45dcc8a2d3ff3", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:52:43Z", + "readme_length": 5861, + "readme_text": "## MX Focus Reader\n\nIn this project, we aim to teach students how to maintain focus while performing tasks such as taking an exam. We have developed a VR application that simulates an exam environment. In this setup, the teacher can create and update questions in real-time through a Google Sheet, which is synchronized with the VR environment. The student must stay focused to answer the questions. If the student loses focus, their writing within the VR environment will become shaky and inaccurate. This dynamic helps train students to maintain focus while completing tasks.\n\n---\n\n![eeg_headband](muse/calmness_model.png)\n\n---\n\n## Project Components\n\nThe project consists of the following key components:\n\n1. **VR Environment**: A virtual reality application where students take an exam, simulating a living exam-writing context. In the VR environment, students are required to maintain focus to answer questions accurately.\n\n2. **Teacher's Google Sheet**: The teacher uses a Google Sheet to create and update exam questions. The sheet is synced in real-time with the VR environment, so any changes made by the teacher are immediately reflected in the exam.\n\n3. **Focus Tracking**: A system that tracks the student's focus through EEG signals. If the student becomes distracted, their writing in the VR environment starts to become shaky and inaccurate, providing immediate feedback.\n\n4. **Muse Headband**: A wearable EEG device that captures real-time brainwave signals from the student, used to monitor their focus during the exam.\n\n5. **MuseLSL (Muse Labs Streamer)**: Software that streams the EEG data from the Muse Headband to the cloud in real-time using the Lab Streaming Layer (LSL) protocol.\n\n6. **AWS IoT Core**: A cloud service used to securely transmit EEG data from MuseLSL to the cloud for further processing.\n\n7. **Scikit-learn Model**: A machine learning model that processes the EEG data to assess the student's level of focus based on brainwave frequency bands.\n\n8. **API Gateway**: AWS API Gateway is used to expose the focus score as a REST API, making it accessible for external applications to retrieve and display the student's focus level.\n\n---\n\n## High-Level Workflow\n\nThe process flows as follows:\n\n1. The **Student** wears the **Muse Headband** to capture real-time EEG signals during the exam.\n\n2. The **MuseLSL** software streams the EEG data to **AWS IoT Core** in real-time for processing.\n\n3. **AWS IoT Core** transmits the data to a **Scikit-learn model** running in the cloud, which processes the EEG signals to evaluate the student's focus level.\n\n4. The model generates a **focus score**, which indicates how focused the student is while answering the exam questions. If the student loses focus, the VR environment will simulate shaky, inaccurate writing.\n\n5. The focus score is exposed via **AWS API Gateway** and can be retrieved by the VR application or any external system, giving immediate feedback to both the student and the teacher.\n\n---\n\n## How It Works\n\n### 1. Muse Headband\n- **Muse Headband** is a wearable EEG device that records brainwave signals in real-time.\n- It measures various brainwave frequencies like Alpha, Beta, Theta, and Gamma waves.\n\n### 2. MuseLSL (Muse Labs Streamer)\n- **MuseLSL** is a tool that facilitates the streaming of EEG data from the Muse Headband via the **Lab Streaming Layer (LSL)** protocol.\n- It allows real-time data collection and transmission to external systems or cloud services like AWS.\n\n### 3. AWS IoT Core\n- **AWS IoT Core** is used to securely handle and transmit the EEG data from MuseLSL to the cloud.\n- Data from MuseLSL is sent via **MQTT protocol** to AWS IoT Core for real-time processing and analysis.\n\n### 4. Calmness Model (Scikit-learn)\n- **Scikit-learn** is used to process the EEG data and generate the calmness score.\n- The model classifies brainwave activity into categories (calm vs. not calm) based on the frequency bands.\n- It uses machine learning models trained on EEG data to predict calmness.\n\n### 5. Calmness Score API\n- The calmness score is made available through a RESTful API, exposed via **AWS API Gateway**.\n- External applications (e.g., mobile apps or web apps) can make HTTP requests to this API to retrieve the calmness score in real-time.\n\n---\n\n## Technologies Used\n\n- **Muse Headband**: Wearable EEG device\n- **MuseLSL**: Streaming EEG data via LSL protocol\n- **AWS IoT Core**: Cloud service for IoT data ingestion\n- **Scikit-learn**: Machine learning library used to analyze EEG data\n- **AWS Lambda**: Serverless compute for model inference\n- **AWS API Gateway**: REST API to expose the calmness score\n- **MQTT Protocol**: Communication protocol for real-time data transmission\n\n---\n\n## Setup Instructions\n\n### 1. Muse Headband Setup\n- Pair the Muse Headband with your computer using Bluetooth.\n- Install MuseLSL on your system to enable data streaming from the Muse Headband.\n\n### 2. Install MuseLSL\nFollow the installation instructions in the [MuseLSL repository](https://github.com/muse-lsl/MuseLSL) to stream data from the Muse Headband. Ensure that the EEG data is streaming to a local server or cloud destination.\n\n### 3. AWS IoT Core Setup\n- Set up an **AWS IoT Core** instance to securely handle incoming data.\n- Configure AWS IoT Core to receive and process the EEG data stream via MQTT.\n- Create and manage **Things** (representing the Muse Headband) within AWS IoT Core.\n\n### 4. Model Training & Inference\n- Train a machine learning model using **Scikit-learn** on a dataset of EEG signals to classify calmness based on brainwave frequencies.\n- Deploy the trained model on **AWS Lambda** or an **EC2 instance** for inference.\n\n### 5. Exposing Calmness Score via API\n- Set up **AWS API Gateway** to expose the calmness score as a REST API.\n- Integrate AWS Lambda with API Gateway to generate and serve the calmness score.", + "readme_title": "## MX Focus Reader", + "releases_count": 1, + "repo": "MX-Focus", + "repo_name": "MX-Focus", + "stars": 2, + "topics": [], + "updated_at": "2026-01-11T19:47:58Z", + "url": "https://github.com/batikanor/MX-Focus", + "watchers": 2 + }, + "https://github.com/bpb02/dreamteam_bms_lauzhack": { + "commit_count_default_branch": 5, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 5, + "html_url": "https://github.com/BFactorEnergia", + "login": "BFactorEnergia" + } + ], + "created_at": "2024-12-01T09:39:31Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 6, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 71, + "type": "file" + }, + { + "path": "BMS challenge.pdf", + "size": 802471, + "type": "file" + }, + { + "path": "FRONTEND", + "size": 0, + "type": "dir" + }, + { + "path": "README.md", + "size": 376, + "type": "file" + }, + { + "path": "correlation.py", + "size": 1371, + "type": "file" + }, + { + "path": "feature_importance.png", + "size": 40557, + "type": "file" + }, + { + "path": "main.py", + "size": 2500, + "type": "file" + }, + { + "path": "plots", + "size": 0, + "type": "dir" + }, + { + "path": "preprocess2.py", + "size": 1477, + "type": "file" + }, + { + "path": "preprocess_data.py", + "size": 1511, + "type": "file" + }, + { + "path": "preprocess_innovix_floresland.py", + "size": 8163, + "type": "file" + }, + { + "path": "preprocess_innovix_floresland_lstm.py", + "size": 6559, + "type": "file" + }, + { + "path": "process_innovix_floresland.py", + "size": 6328, + "type": "file" + }, + { + "path": "process_zegoland.py", + "size": 6337, + "type": "file" + }, + { + "path": "requirements.txt", + "size": 66, + "type": "file" + }, + { + "path": "test1.py", + "size": 2575, + "type": "file" + } + ], + "files_total_count": 22, + "first_commit_date_default_branch": "2024-12-01T09:43:06Z", + "forks": 1, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 41898 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:07:49Z", + "last_commit_oid_default_branch": "1aa40c42e446a608dd8e5602b93326a9825b13ba", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "bpb02/dreamteam_bms_lauzhack", + "owner": "bpb02", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_6d09ac77d036a73e", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:08:45Z", + "readme_length": 367, + "readme_text": "# 🇨🇭 LauzHack 2023 - BMS Data Analysis Project\n\nProject developed during LauzHack 2024 at EPFL (École Polytechnique Fédérale de Lausanne).\n\nThis repository contains code for preprocessing and analyzing BMS (Bristol Myers Squibb) pharmaceutical data, including:\n\n- Data preprocessing and standardization\n- Time series analysis\n- Demand forecasting\n- Volume predictions", + "readme_title": "🇨🇭 LauzHack 2023 - BMS Data Analysis Project", + "releases_count": 0, + "repo": "dreamteam_bms_lauzhack", + "repo_name": "dreamteam_bms_lauzhack", + "stars": 1, + "topics": [], + "updated_at": "2024-12-07T13:00:21Z", + "url": "https://github.com/bpb02/dreamteam_bms_lauzhack", + "watchers": 1 + }, + "https://github.com/cheems277/Genesix": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'cheems277/Genesix'.\"}]", + "owner": "cheems277", + "project_foreign_key": "lhp_251728fbde5b4d54", + "repo": "Genesix" + }, + "https://github.com/converge-ai-lh/converge": { + "commit_count_default_branch": 54, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 24, + "html_url": "https://github.com/omarelmalki", + "login": "omarelmalki" + }, + { + "contributions": 17, + "html_url": "https://github.com/nicolas-cuveillier", + "login": "nicolas-cuveillier" + }, + { + "contributions": 13, + "html_url": "https://github.com/gillesdewaha", + "login": "gillesdewaha" + } + ], + "created_at": "2024-11-30T13:19:40Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 1, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 46, + "type": "file" + }, + { + "path": "README.md", + "size": 2306, + "type": "file" + }, + { + "path": "agents.py", + "size": 5884, + "type": "file" + }, + { + "path": "app.py", + "size": 13336, + "type": "file" + }, + { + "path": "kylian_bezos_internship_review.pdf", + "size": 54753, + "type": "file" + }, + { + "path": "leader_discussion.py", + "size": 4810, + "type": "file" + }, + { + "path": "requirements.txt", + "size": 128, + "type": "file" + }, + { + "path": "team_member_discussion.py", + "size": 5435, + "type": "file" + }, + { + "path": "utils", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 10, + "first_commit_date_default_branch": "2024-11-30T13:20:26Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 32004 + } + ], + "last_commit_date_default_branch": "2024-12-01T11:23:27Z", + "last_commit_oid_default_branch": "9e38e2b710f7b84bd1dc4564d869fff4bf2b6131", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "converge-ai-lh/converge", + "owner": "converge-ai-lh", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_41d8e7122dc587e8", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T11:23:42Z", + "readme_length": 2305, + "readme_text": "# Converge - AI-Powered Meeting Assistant\n\nConverge is a Slack bot that helps facilitate better meetings by:\n- Collecting and analyzing input from team members\n- Facilitating AI-powered discussions between virtual agents representing team members\n- Generating comprehensive reports and summaries\n- Providing personalized preparation guidance to individual team members\n\n## Features\n- Voice message transcription\n- PDF document analysis\n- Multi-agent discussions\n- Personalized meeting preparation\n- Automated report generation\n\n## Demo\n\nVideo coming soon\n\n## Setup\n1. Install dependencies:\n\n```\npip install -r requirements.txt\n```\n\n2. Create a .env file with:\n\n```\nOPENAI_API_KEY=your_key\nSLACK_BOT_TOKEN=your_token\nSLACK_SIGNING_SECRET=your_secret\nLLAMA_CLOUD_API_KEY=your_key\n```\n\n3. Run the Flask server:\n\n```\npython app.py\n```\n\n4. Connect this Slack app to your Slack workspace\n\n4.1 Set Up Bot Token and Permissions\nGo to the OAuth & Permissions section in the left-hand menu. Under the Scopes section, add the following bot token scopes:\n- app_mentions:read\n- channels:history\n- chat:write\n- im:history\n- users:read\n- Click Save Changes.\n\n4.2 Install the App\nNavigate to the Install App section in the left-hand menu. Click Install to Workspace and authorize the app for your workspace. Copy the Bot User OAuth Token provided after installation.\n\n4.3 Configure the Signing Secret\nIn the Basic Information section, locate the Signing Secret under App Credentials. Copy this value for use in your environment variables.\n\n4.4 Set Up Event Subscriptions\nGo to the Event Subscriptions section and toggle the Enable Events button to On. Under Request URL, enter the public URL of your server (e.g., from ngrok). The URL should end with the route that handles Slack requests, e.g., https://your-public-url.com/. Ensure your server is running to verify the request. Subscribe to events like app_mention or message.im under the Subscribe to Bot Events section.\n\n## Architecture\n\n- app.py - Main Slack bot application\n- agents.py - AI agent implementation\n- leader_discussion.py - Leadership discussion handler\n- team_member_discussion.py - Team member discussion handler\n- generate_final_report.py - Final report generation\n- Support utilities: \n - transcribe_voice_input.py \n - extract_text_from_pdf.py", + "readme_title": "Converge - AI-Powered Meeting Assistant", + "releases_count": 0, + "repo": "converge", + "repo_name": "converge", + "stars": 3, + "topics": [], + "updated_at": "2025-11-10T00:45:29Z", + "url": "https://github.com/converge-ai-lh/converge", + "watchers": 0 + }, + "https://github.com/cyril87885/lauzHack": { + "commit_count_default_branch": 29, + "contributors_count": 4, + "contributors_top": [ + { + "contributions": 12, + "html_url": "https://github.com/Arlakhian", + "login": "Arlakhian" + }, + { + "contributions": 10, + "html_url": "https://github.com/ahmedc3ca", + "login": "ahmedc3ca" + }, + { + "contributions": 4, + "html_url": "https://github.com/CyrilDeloince", + "login": "CyrilDeloince" + }, + { + "contributions": 3, + "html_url": "https://github.com/danaedanycan", + "login": "danaedanycan" + } + ], + "created_at": "2024-11-30T08:52:41Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 334, + "files_root_entries": [ + { + "path": ".DS_Store", + "size": 6148, + "type": "file" + }, + { + "path": "README.md", + "size": 1498, + "type": "file" + }, + { + "path": "fusion-stickynotes-meta-ssa-colocation-2", + "size": 0, + "type": "dir" + }, + { + "path": "toto.txt", + "size": 5, + "type": "file" + } + ], + "files_total_count": 2386, + "first_commit_date_default_branch": "2024-11-30T08:52:41Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "C#", + "size": 3650470 + }, + { + "language": "ShaderLab", + "size": 88111 + }, + { + "language": "JavaScript", + "size": 33264 + }, + { + "language": "Objective-C++", + "size": 27576 + }, + { + "language": "Mathematica", + "size": 16133 + }, + { + "language": "HLSL", + "size": 14421 + }, + { + "language": "Objective-C", + "size": 1196 + }, + { + "language": "C", + "size": 1148 + } + ], + "last_commit_date_default_branch": "2024-12-01T12:20:21Z", + "last_commit_oid_default_branch": "b9130d2fa0617ce17b0a33d8b9d7974086bb3af8", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "CyrilDeloince/lauzHack", + "owner": "cyril87885", + "parent_repo": null, + "parent_url": null, + "primary_language": "C#", + "project_foreign_key": "lhp_bcb2c30ad48ddc78", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T12:20:21Z", + "readme_length": 1471, + "readme_text": "# **VRtuoso** 🎶 \n*Master Music in Virtual Reality*\n\n---\n\n## **Overview**\n**VRtuoso** is a Unity-powered VR game that merges music, rhythm, and immersive technology. \nSimply **plug in your VR headset**, launch the game, and experience the thrill of reading and playing music in real-time! \nNo setup, no complexity—just music and fun.\n\n---\n\n## **Features**\n- 🎵 **Effortless Setup**: Plug in your VR headset, launch the game, and start playing. \n- 🎼 **Interactive Music Scores**: Follow a glowing line to strike notes in perfect time. \n- 🧠 **Educational & Fun**: Improve sight-reading and rhythm skills while having fun. \n- 🌟 **Immersive Gameplay**: Dive into an intuitive, visually stunning VR environment. \n\n---\n\n## **How It Works**\n1. **Start VRtuoso**: \n - Launch the game from your VR headset. \n\n2. **Follow the Timeline**: \n - Strike notes as they align with the glowing timeline. \n\n3. **Score Points**: \n - Play accurately to rack up points and improve your skills. \n\n4. **Enjoy the Music**: \n - Let the rhythm guide you through an unforgettable VR experience. \n\n---\n\n## **Requirements**\n- **VR Headset**: Oculus, HTC Vive, or any VR-compatible device. \n- **PC**: VR-ready system for optimal performance. \n\n---\n\n## **Quick Setup**\n1. **Download VRtuoso**. \n2. **Connect your VR headset**. \n3. **Launch and play**—no extra configuration required! \n\n---\n\n> **🎻 Become the VRtuoso you’ve always dreamed of and master the art of music in VR!**", + "readme_title": "**VRtuoso** 🎶", + "releases_count": 0, + "repo": "lauzHack", + "repo_name": "lauzHack", + "stars": 1, + "topics": [], + "updated_at": "2024-12-09T23:42:12Z", + "url": "https://github.com/CyrilDeloince/lauzHack", + "watchers": 1 + }, + "https://github.com/dominikglandorf/Podcastify": { + "commit_count_default_branch": 17, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 15, + "html_url": "https://github.com/dominikglandorf", + "login": "dominikglandorf" + }, + { + "contributions": 1, + "html_url": "https://github.com/spneshaei", + "login": "spneshaei" + }, + { + "contributions": 1, + "html_url": "https://github.com/faresfawzi", + "login": "faresfawzi" + } + ], + "created_at": "2024-11-30T13:39:02Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": ".env.example", + "size": 83, + "type": "file" + }, + { + "path": ".gitignore", + "size": 27, + "type": "file" + }, + { + "path": "generator.py", + "size": 4342, + "type": "file" + }, + { + "path": "readme.md", + "size": 1120, + "type": "file" + }, + { + "path": "requirements.txt", + "size": 48, + "type": "file" + }, + { + "path": "server.py", + "size": 3740, + "type": "file" + } + ], + "files_total_count": 6, + "first_commit_date_default_branch": "2024-11-30T12:05:19Z", + "forks": 1, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 8082 + } + ], + "last_commit_date_default_branch": "2024-12-01T08:42:55Z", + "last_commit_oid_default_branch": "08fe1c761305eabc4726bdc024f6ab3e03ca458f", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "dominikglandorf/Podcastify", + "owner": "dominikglandorf", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_d5ccafb7fdd62ccf", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T08:42:57Z", + "readme_length": 1120, + "readme_text": "# French podcast generation with GPT4o\n\n\n## Installation\n\n1. Clone the repository or install the package using pip:\n ```bash\n pip install -r requirements.txt\n ```\n\n2. Ensure you have the necessary environment variables set up (if applicable). Use a `.env` file for secure configuration:\n ```plaintext\n OPENAI_API_KEY=your_api_key_here\n ```\n\n---\n\n## Features\n\n- **Language Level Configuration**: Customize responses for different levels of proficiency (e.g., A1, B2).\n- **Vocabulary Integration**: Provide specific terms or phrases to be used in the output.\n- **Session History Management**: Retain the context across multiple interactions using unique session IDs.\n- **Chunked Responses**: Control whether the response is delivered in one go or in smaller chunks.\n\n---\n\n## Usage\n\nYou can either use the `generator.py` module stand-alone or the `server.py` to serve functions in a Flask server.\n\n### Functions\n\n- generate(language, language_level, topic, history, new_words): Create or continue a podcast with or without preferred words.\n- define(word, context): Get the definition of a word within a context.", + "readme_title": "French podcast generation with GPT4o", + "releases_count": 0, + "repo": "Podcastify", + "repo_name": "Podcastify", + "stars": 1, + "topics": [], + "updated_at": "2024-12-09T23:03:02Z", + "url": "https://github.com/dominikglandorf/Podcastify", + "watchers": 0 + }, + "https://github.com/doncamilom/watchmen": { + "commit_count_default_branch": 47, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 31, + "html_url": "https://github.com/doncamilom", + "login": "doncamilom" + }, + { + "contributions": 8, + "html_url": "https://github.com/CyberVitamin", + "login": "CyberVitamin" + }, + { + "contributions": 8, + "html_url": "https://github.com/AndreaSalati", + "login": "AndreaSalati" + } + ], + "created_at": "2024-11-30T15:56:09Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 14, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 26, + "type": "file" + }, + { + "path": "README.md", + "size": 1576, + "type": "file" + }, + { + "path": "agent.ipynb", + "size": 5149, + "type": "file" + }, + { + "path": "boat.png", + "size": 1218165, + "type": "file" + }, + { + "path": "claude.py", + "size": 1409, + "type": "file" + }, + { + "path": "dpt.py", + "size": 1519, + "type": "file" + }, + { + "path": "frames_platjeoost", + "size": 0, + "type": "dir" + }, + { + "path": "gather_frames.py", + "size": 4452, + "type": "file" + }, + { + "path": "imgs", + "size": 0, + "type": "dir" + }, + { + "path": "maritime-livefeed-app", + "size": 0, + "type": "dir" + }, + { + "path": "owlvit.ipynb", + "size": 332400, + "type": "file" + }, + { + "path": "requirements.txt", + "size": 676, + "type": "file" + }, + { + "path": "setup.py", + "size": 830, + "type": "file" + }, + { + "path": "viz.ipynb", + "size": 1094754, + "type": "file" + }, + { + "path": "watchmen", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 66, + "first_commit_date_default_branch": "2024-11-30T15:56:49Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 1432303 + }, + { + "language": "JavaScript", + "size": 55565 + }, + { + "language": "Python", + "size": 29496 + }, + { + "language": "HTML", + "size": 1801 + }, + { + "language": "CSS", + "size": 930 + } + ], + "last_commit_date_default_branch": "2024-12-01T13:48:42Z", + "last_commit_oid_default_branch": "ae560b8a88ab935244c7ce909170cfd72b7293b4", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "doncamilom/watchmen", + "owner": "doncamilom", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_33346942e9251f0b", + "pull_requests_closed": 0, + "pull_requests_merged": 7, + "pull_requests_open": 0, + "pull_requests_total": 7, + "pushed_at": "2024-12-01T13:48:42Z", + "readme_length": 1572, + "readme_text": "# Seas the Day\n\n![Seas the Day Demo](imgs/tiny.png)\n\n\n**Seas the Day** transforms maritime tracking and analysis, making port data interactive, insightful, and accessible.\n\n## Key Features\n\n### 1. Interactive Global Map\n- **Global View**: Explore major ports worldwide with an interactive map.\n- **Detailed Dashboards**: Click on a port (e.g., Rotterdam) for real-time and historical data.\n\n### 2. Descriptive Analysis\n- **Summarized Insights**: Access key statistics from the past day:\n - Vessel types docked.\n - Estimated cargo throughput.\n - Average ship speed in port.\n- **AI-Driven Visualization**: Automatically process and visualize complex data for clarity.\n\n### 3. Interactive Image Analysis\n- **Live Port Imagery**: View the latest images of selected ports.\n- **Ask the Image**:\n - \"How many ships are in this frame?\"\n - \"What’s the name of the ship closest to the dock?\"\n - \"Are there any empty berths?\"\n- **Instant AI Insights**: Transform static visuals into actionable intelligence.\n\n## Why Choose Seas the Day?\n- **Simplified Data**: Skip hours of footage and dense datasets—click, explore, and ask.\n- **Enhanced Efficiency**: Boost port management and logistics with AI-powered tools.\n- **User-Friendly**: Designed for port authorities, logistics companies, and curious users alike.\n\n## Revolutionizing Maritime Intelligence\nWith **Seas the Day**, port tracking and analysis become seamless and interactive. Dive into the future of maritime logistics today!\n\n---\n**Ready to get started?** Explore **Seas the Day** and revolutionize port intelligence.", + "readme_title": "Seas the Day", + "releases_count": 0, + "repo": "watchmen", + "repo_name": "watchmen", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T13:48:46Z", + "url": "https://github.com/doncamilom/watchmen", + "watchers": 1 + }, + "https://github.com/edouardmichelin/fred": { + "commit_count_default_branch": 55, + "contributors_count": 2, + "contributors_top": [ + { + "contributions": 31, + "html_url": "https://github.com/edouardmichelin", + "login": "edouardmichelin" + }, + { + "contributions": 24, + "html_url": "https://github.com/Bozu1206", + "login": "Bozu1206" + } + ], + "created_at": "2024-11-30T15:19:30Z", + "default_branch": "master", + "description": "LauzHack 2024 - 24 hours - 2 people", + "dirs_total_count": 62, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 3353, + "type": "file" + }, + { + "path": "README.md", + "size": 1153, + "type": "file" + }, + { + "path": "app-logo.png", + "size": 369969, + "type": "file" + }, + { + "path": "app", + "size": 0, + "type": "dir" + }, + { + "path": "build.gradle.kts", + "size": 235, + "type": "file" + }, + { + "path": "gradle.properties", + "size": 1358, + "type": "file" + }, + { + "path": "gradle", + "size": 0, + "type": "dir" + }, + { + "path": "gradlew", + "size": 8762, + "type": "file" + }, + { + "path": "gradlew.bat", + "size": 2966, + "type": "file" + }, + { + "path": "screenshot.png", + "size": 866711, + "type": "file" + }, + { + "path": "settings.gradle", + "size": 408, + "type": "file" + } + ], + "files_total_count": 150, + "first_commit_date_default_branch": "2024-11-30T15:41:09Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Kotlin", + "size": 179153 + } + ], + "last_commit_date_default_branch": "2024-12-01T21:05:39Z", + "last_commit_oid_default_branch": "e6ac993965a986752299a45f60f65ce7831b67ce", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "edouardmichelin/fred", + "owner": "edouardmichelin", + "parent_repo": null, + "parent_url": null, + "primary_language": "Kotlin", + "project_foreign_key": "lhp_38fb4a8ab6e06c46", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T21:05:42Z", + "readme_length": 1151, + "readme_text": "# Fred: Your Personal Carbon **F**ootprint **Red**ucer\n\n\"App\n\n---\n\n## Authors\n\n- [François Dumoncel](https://github.com/Bozu1206)\n- [Edouard Michelin](https://github.com/edouardmichelin)\n\n## Context\n\nFred was developed by a **team of two** during the **24-hour** LauzHack hackathon, which took place at the EPFL BC building in November 2024.\n\n## The app\n\n### Short description\n\nFred is your AI-powered companion for a greener lifestyle, guiding you to reduce your carbon footprint with ease and insight. It helps you:\n1. Log activities that either reward sustainable habits or track areas for improvement.\n2. Receive personalized daily tips to reduce your carbon footprint based on your habits and recent activities.\n\n### Technical details\n\nFred is an Android application developed in Kotlin using Jetpack Compose. It follows the MVVM architecture and leverages:\n- **Firebase** for cloud services such as authentication and data storage.\n- **OpenAI's GPT-3.5** for generating tailored recommendations.\n- **Nominatim** for geocoding.\n\n\"Home", + "readme_title": "Fred: Your Personal Carbon **F**ootprint **Red**ucer", + "releases_count": 0, + "repo": "fred", + "repo_name": "fred", + "stars": 3, + "topics": [ + "ai", + "android", + "android-application", + "carbon-footprint", + "firebase", + "gamification", + "hackathon", + "hackathon-project", + "lauzhack", + "mvvm", + "mvvm-android", + "mvvm-architecture", + "jetpack-compose", + "kotlin", + "kotlin-android", + "llm" + ], + "updated_at": "2025-08-06T09:47:58Z", + "url": "https://github.com/edouardmichelin/fred", + "watchers": 1 + }, + "https://github.com/fenfyp/lauzHack": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'fenfyp/lauzHack'.\"}]", + "owner": "fenfyp", + "project_foreign_key": "lhp_697052fffefdcbf3", + "repo": "lauzHack" + }, + "https://github.com/flawnn/mapalyst": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'flawnn/mapalyst'.\"}]", + "owner": "flawnn", + "project_foreign_key": "lhp_f98712a88129ad92", + "repo": "mapalyst" + }, + "https://github.com/francesco-gramegna/lauehack2024team": { + "commit_count_default_branch": 21, + "contributors_count": 4, + "contributors_top": [ + { + "contributions": 10, + "html_url": "https://github.com/NotXia", + "login": "NotXia" + }, + { + "contributions": 7, + "html_url": "https://github.com/liuktc", + "login": "liuktc" + }, + { + "contributions": 2, + "html_url": null, + "login": "francesco" + }, + { + "contributions": 1, + "html_url": "https://github.com/francesco-gramegna", + "login": "francesco-gramegna" + } + ], + "created_at": "2024-11-30T13:09:38Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 4, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 40, + "type": "file" + }, + { + "path": "NeuroProbModels.ipynb", + "size": 33300, + "type": "file" + }, + { + "path": "README.md", + "size": 326, + "type": "file" + }, + { + "path": "cleaning.ipynb", + "size": 107353, + "type": "file" + }, + { + "path": "cleaning_Luca.ipynb", + "size": 677683, + "type": "file" + }, + { + "path": "src", + "size": 0, + "type": "dir" + }, + { + "path": "web", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 14, + "first_commit_date_default_branch": "2024-11-30T23:35:53Z", + "forks": 1, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 1470900 + }, + { + "language": "Python", + "size": 23335 + }, + { + "language": "HTML", + "size": 13055 + } + ], + "last_commit_date_default_branch": "2024-12-01T12:15:23Z", + "last_commit_oid_default_branch": "92cfeefe6d3e6a4c79a6dbac7db4f737bbc2739f", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "francesco-gramegna/lauehack2024team", + "owner": "francesco-gramegna", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_e9cba92462d1b311", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T12:15:26Z", + "readme_length": 326, + "readme_text": "# TheCatIsForecatting\n\n\nSubmission for the LauzHack 2024 hackathon.\n\nTime series forecasting for medicine demand.\n\n\n## Approach\n\nWe solve the task using Gaussian processes for forecasting and SHAP for determining feature importance.\n\n\n## Team members\n- Luca Domeniconi \n- Francesco Gramegna\n- Claudia Maiolino\n- Tian Cheng Xia", + "readme_title": "TheCatIsForecatting", + "releases_count": 0, + "repo": "lauehack2024team", + "repo_name": "lauehack2024team", + "stars": 1, + "topics": [], + "updated_at": "2024-12-02T22:40:53Z", + "url": "https://github.com/francesco-gramegna/lauehack2024team", + "watchers": 1 + }, + "https://github.com/jofremosegui/lauzhack": { + "commit_count_default_branch": 11, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 9, + "html_url": "https://github.com/elenaalegret", + "login": "elenaalegret" + }, + { + "contributions": 1, + "html_url": null, + "login": "Jofre Moseguí" + }, + { + "contributions": 1, + "html_url": "https://github.com/jofremosegui", + "login": "jofremosegui" + } + ], + "created_at": "2024-11-30T12:21:21Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 3139, + "type": "file" + }, + { + "path": "README.md", + "size": 1544, + "type": "file" + }, + { + "path": "exploration.ipynb", + "size": 46038, + "type": "file" + } + ], + "files_total_count": 3, + "first_commit_date_default_branch": "2024-11-30T12:21:22Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 46038 + } + ], + "last_commit_date_default_branch": "2024-12-01T11:00:43Z", + "last_commit_oid_default_branch": "ba3c3953a933ed34732747200d1767693b2287ac", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "jofremosegui/lauzhack", + "owner": "jofremosegui", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_07466aba9f05c3be", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T11:00:43Z", + "readme_length": 1541, + "readme_text": "

LauzHack - EPFL
\n\n

UBS Efficient Entity Resolution: Clustering and Embedding-Based Matching

\n\n
\nDaniela Álvarez, Elena Alegret, Jofre Moseguí, Andrea Quiroz\n
\n\n
\nThis project focuses on resolving external counterparties efficiently by combining clustering, embeddings, and similarity-based classification. Instead of comparing all entities exhaustively, we use clustering and embedding-based techniques to narrow down potential matches, significantly improving computational efficiency and scalability.\n
\n\n###### The Challenge\nComparing 1.4 million entities directly is computationally prohibitive, leading to billions of pairwise comparisons. Our approach minimizes this complexity by:\n1. Pre-clustering entities into ~1400 groups using K-Means.\n2. Embedding new entries to find their nearest cluster centroid.\n3. Resolving entities within clusters based on similarity measures.\n\n#### Workflow overview\n\n

\n \"Screenshot\n \"Screenshot\n\n

\n\n

\n Figure 1: K-Means Structure Overview       \n Figure 2: New Entry Structure Overview \n\n

", + "readme_title": "
LauzHack - EPFL
", + "releases_count": 0, + "repo": "lauzhack", + "repo_name": "lauzhack", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T11:00:47Z", + "url": "https://github.com/jofremosegui/lauzhack", + "watchers": 1 + }, + "https://github.com/joriba/lauzhack-2024": { + "commit_count_default_branch": 47, + "contributors_count": 4, + "contributors_top": [ + { + "contributions": 27, + "html_url": "https://github.com/Alone2", + "login": "Alone2" + }, + { + "contributions": 18, + "html_url": "https://github.com/joriba", + "login": "joriba" + }, + { + "contributions": 1, + "html_url": null, + "login": "Babineca Darja" + }, + { + "contributions": 1, + "html_url": "https://github.com/mirosch", + "login": "mirosch" + } + ], + "created_at": "2024-11-30T12:50:43Z", + "default_branch": "main", + "description": "VR Unity Project using the MX-Ink pen", + "dirs_total_count": 9, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 1503, + "type": "file" + }, + { + "path": "LICENSE", + "size": 1070, + "type": "file" + }, + { + "path": "README.md", + "size": 525, + "type": "file" + }, + { + "path": "TODO.md", + "size": 159, + "type": "file" + }, + { + "path": "compose.yaml", + "size": 485, + "type": "file" + }, + { + "path": "dockerfiles", + "size": 0, + "type": "dir" + }, + { + "path": "nginx_config", + "size": 0, + "type": "dir" + }, + { + "path": "package-lock.json", + "size": 33826, + "type": "file" + }, + { + "path": "package.json", + "size": 446, + "type": "file" + }, + { + "path": "server", + "size": 0, + "type": "dir" + }, + { + "path": "src", + "size": 0, + "type": "dir" + }, + { + "path": "static", + "size": 0, + "type": "dir" + }, + { + "path": "tools", + "size": 0, + "type": "dir" + }, + { + "path": "vite.config.js", + "size": 819, + "type": "file" + } + ], + "files_total_count": 32, + "first_commit_date_default_branch": "2024-11-30T12:50:44Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": true, + "has_docs": false, + "has_license_file": true, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "JavaScript", + "size": 18410 + }, + { + "language": "Python", + "size": 2000 + }, + { + "language": "Dockerfile", + "size": 1187 + }, + { + "language": "HTML", + "size": 486 + }, + { + "language": "Shell", + "size": 385 + }, + { + "language": "CSS", + "size": 138 + } + ], + "last_commit_date_default_branch": "2024-12-01T11:44:22Z", + "last_commit_oid_default_branch": "b738263307ce9ea65a0ed3632977f50015f65d23", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": "MIT License", + "license_spdx": "MIT", + "name_with_owner": "joriba/lauzhack-2024", + "owner": "joriba", + "parent_repo": null, + "parent_url": null, + "primary_language": "JavaScript", + "project_foreign_key": "lhp_970a7e05d6c00d65", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T11:44:32Z", + "readme_length": 522, + "readme_text": "# LauzHack 2024 Project\n\n_Wizard Battles_\nWe are battling with magic sticks\n\n## Upload to test\n```\n./tools/upload.sh testinstancename\n```\n* Will be available under `https://spellz.a1n.ch/testinstancename`\n\n## Upload to prod\n```\nnpm run build\n./tools/upload.sh\n```\n* Will be available under `https://spellz.a1n.ch/`\n\n## Upload to test\n\nName your test-instance, here (as an example `testinstanename`)\n```\nnpm run build\n./tools/upload.sh testinstancename\n```\n* Will be available under `https://spellz.a1n.ch/testinstancename`", + "readme_title": "LauzHack 2024 Project", + "releases_count": 0, + "repo": "lauzhack-2024", + "repo_name": "lauzhack-2024", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T11:44:37Z", + "url": "https://github.com/joriba/lauzhack-2024", + "watchers": 2 + }, + "https://github.com/kalil0321/lauzhack-2024": { + "commit_count_default_branch": 28, + "contributors_count": 4, + "contributors_top": [ + { + "contributions": 15, + "html_url": null, + "login": "YL2407" + }, + { + "contributions": 10, + "html_url": "https://github.com/YL2407", + "login": "YL2407" + }, + { + "contributions": 2, + "html_url": "https://github.com/zak-2213", + "login": "zak-2213" + }, + { + "contributions": 1, + "html_url": "https://github.com/kalil0321", + "login": "kalil0321" + } + ], + "created_at": "2024-11-30T10:46:36Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 173, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 1317, + "type": "file" + }, + { + "path": ".vscode", + "size": 0, + "type": "dir" + }, + { + "path": "Assets", + "size": 0, + "type": "dir" + }, + { + "path": "Packages", + "size": 0, + "type": "dir" + }, + { + "path": "ProjectSettings", + "size": 0, + "type": "dir" + }, + { + "path": "README.md", + "size": 15, + "type": "file" + }, + { + "path": "UpgradeLog.htm", + "size": 37418, + "type": "file" + } + ], + "files_total_count": 1448, + "first_commit_date_default_branch": "2024-11-30T10:46:36Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "C#", + "size": 3195173 + }, + { + "language": "HTML", + "size": 37418 + }, + { + "language": "ShaderLab", + "size": 4306 + }, + { + "language": "JavaScript", + "size": 3306 + } + ], + "last_commit_date_default_branch": "2024-12-01T11:48:06Z", + "last_commit_oid_default_branch": "0fa9ab6da863bf63b08d79ecb0794acacc8b50d8", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "Mimar-VR/lauzhack-2024", + "owner": "kalil0321", + "parent_repo": null, + "parent_url": null, + "primary_language": "C#", + "project_foreign_key": "lhp_178c7b0699cf6dbd", + "pull_requests_closed": 0, + "pull_requests_merged": 14, + "pull_requests_open": 1, + "pull_requests_total": 15, + "pushed_at": "2024-12-02T22:33:27Z", + "readme_length": 15, + "readme_text": "# lauzhack-2024", + "readme_title": "lauzhack-2024", + "releases_count": 0, + "repo": "lauzhack-2024", + "repo_name": "lauzhack-2024", + "stars": 0, + "topics": [], + "updated_at": "2025-09-10T15:49:17Z", + "url": "https://github.com/Mimar-VR/lauzhack-2024", + "watchers": 1 + }, + "https://github.com/kotleta2007/NearestNeighbors": { + "commit_count_default_branch": 18, + "contributors_count": 5, + "contributors_top": [ + { + "contributions": 10, + "html_url": "https://github.com/kotleta2007", + "login": "kotleta2007" + }, + { + "contributions": 3, + "html_url": null, + "login": "AnnaKelmanson" + }, + { + "contributions": 2, + "html_url": "https://github.com/WiZeYAR", + "login": "WiZeYAR" + }, + { + "contributions": 2, + "html_url": "https://github.com/marcelmmc", + "login": "marcelmmc" + }, + { + "contributions": 1, + "html_url": null, + "login": "Anna Kelmanson" + } + ], + "created_at": "2024-11-30T11:59:35Z", + "default_branch": "main", + "description": "LauzHack 2024. BMS Time Series Challenge.", + "dirs_total_count": 7, + "files_root_entries": [ + { + "path": ".devcontainer", + "size": 0, + "type": "dir" + }, + { + "path": ".gitignore", + "size": 3194, + "type": "file" + }, + { + "path": "README.md", + "size": 149, + "type": "file" + }, + { + "path": "chat_app", + "size": 0, + "type": "dir" + }, + { + "path": "pyproject.toml", + "size": 716, + "type": "file" + }, + { + "path": "src", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 20, + "first_commit_date_default_branch": "2024-11-30T11:59:35Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 104193 + }, + { + "language": "Python", + "size": 17252 + }, + { + "language": "Dockerfile", + "size": 1184 + }, + { + "language": "Shell", + "size": 94 + }, + { + "language": "Batchfile", + "size": 94 + } + ], + "last_commit_date_default_branch": "2024-12-01T17:10:28Z", + "last_commit_oid_default_branch": "da44995e12be2422d66ef903bc5a4334049c367c", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "kotleta2007/NearestNeighbors", + "owner": "kotleta2007", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_dab8cea364046913", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T17:10:32Z", + "readme_length": 148, + "readme_text": "# NearestNeighbors\nLauzHack 2024. BMS Time Series Challenge.\n\n# get the data\n```bash\nmkdir files\ncp .../INNOVIX_* files/\ncp .../BRISTOR_* files/\n```", + "readme_title": "NearestNeighbors", + "releases_count": 0, + "repo": "NearestNeighbors", + "repo_name": "NearestNeighbors", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T17:10:36Z", + "url": "https://github.com/kotleta2007/NearestNeighbors", + "watchers": 1 + }, + "https://github.com/lars-quaedvlieg/chronica": { + "commit_count_default_branch": 56, + "contributors_count": 4, + "contributors_top": [ + { + "contributions": 38, + "html_url": "https://github.com/lars-quaedvlieg", + "login": "lars-quaedvlieg" + }, + { + "contributions": 8, + "html_url": "https://github.com/smehra34", + "login": "smehra34" + }, + { + "contributions": 5, + "html_url": "https://github.com/AleHD", + "login": "AleHD" + }, + { + "contributions": 5, + "html_url": "https://github.com/arvind6599", + "login": "arvind6599" + } + ], + "created_at": "2024-11-30T13:32:57Z", + "default_branch": "main", + "description": "on-device Flask-based web application designed to help you create, manage, and visualize notes effectively and securely", + "dirs_total_count": 11, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 3181, + "type": "file" + }, + { + "path": "LICENSE.md", + "size": 14657, + "type": "file" + }, + { + "path": "README.md", + "size": 4282, + "type": "file" + }, + { + "path": "app", + "size": 0, + "type": "dir" + }, + { + "path": "backup_shh.py", + "size": 628, + "type": "file" + }, + { + "path": "newwhisper", + "size": 0, + "type": "dir" + }, + { + "path": "requirements.txt", + "size": 123, + "type": "file" + }, + { + "path": "res", + "size": 0, + "type": "dir" + }, + { + "path": "run.py", + "size": 103, + "type": "file" + }, + { + "path": "run_docker.sh", + "size": 105, + "type": "file" + }, + { + "path": "run_server.py", + "size": 2168, + "type": "file" + }, + { + "path": "shh.py", + "size": 5827, + "type": "file" + } + ], + "files_total_count": 46, + "first_commit_date_default_branch": "2024-11-30T13:32:57Z", + "forks": 1, + "has_ci": false, + "has_contributing": false, + "has_docker": true, + "has_docs": false, + "has_license_file": true, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 112323 + }, + { + "language": "JavaScript", + "size": 20532 + }, + { + "language": "HTML", + "size": 16580 + }, + { + "language": "CSS", + "size": 7296 + }, + { + "language": "Shell", + "size": 105 + } + ], + "last_commit_date_default_branch": "2024-12-04T00:59:39Z", + "last_commit_oid_default_branch": "6957ef4b0763f7d979c0681f7d97fdc3395c7988", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": "Other", + "license_spdx": "NOASSERTION", + "name_with_owner": "lars-quaedvlieg/chronica", + "owner": "lars-quaedvlieg", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_e5529cf66a914baa", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-04T00:59:47Z", + "readme_length": 4280, + "readme_text": "# Chronica\n\n\"drawing\"\n\nChronica is a completely on-device Flask-based web application designed to help you create, manage, and visualize notes effectively and securely. It features an intuitive and interactive UI that allows you to log your unstructured thoughts, automatically transcribe and structure your notes, explore saved notes in a gallery, and even perform semantic searches and ask for insights about your entries.\n\n## Features\n\n- **Note Creation**: Record audio, transcribe it, and create new notes easily.\n- **Note Gallery**: View your notes in a well-organized, visually appealing gallery, categorized by month, week, or year.\n- **Semantic Search**: Search through your notes with advanced semantic matching.\n- **Statistics Overview**: Visualize insights from your notes, such as word clouds of note summaries.\n- **Beautiful and Interactive UI**: Colors are used to represent tags, and cards have dynamic effects to enhance the user experience.\n\n## Screenshots\n\n### 1. Home Page\n![Home Page](res/home.png)\n\n### 2. Create a New Note\n![New Note Page](res/record.png)\n\n### 3. View Notes in the Gallery\n![Gallery Page](res/gallery.png)\n\n### 4. View Note Entry\n![View Entry Page](res/view_entry.png)\n\n## Prerequisites\n\nEnsure that you have the following installed on your machine:\n\n- **Python 3.10.12**\n- **pip** (Python package manager)\n- **Docker**\n\n## Installation\n\nTo set up and run Chronica locally, follow these steps:\n\n1. **Clone the Repository**:\n\n ```sh\n git clone git@github.com:lars-quaedvlieg/chronica.git\n cd chronica\n ```\n\n2. **Install Required Packages**:\n\n ```sh\n pip install -r requirements.txt\n sudo apt install ffmpeg\n sudo apt install portaudio19-dev\n ```\n\n3. **[Install the Required CUDA Version](https://stackoverflow.com/questions/66977227/could-not-load-dynamic-library-libcudnn-so-8-when-running-tensorflow-on-ubun)**:\n\n ```sh\n wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin\n sudo mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600\n export last_public_key=3bf863cc\n sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/${last_public_key}.pub\n sudo add-apt-repository \"deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/ /\"\n sudo apt-get update\n sudo apt-get install libcudnn8\n sudo apt-get install libcudnn8-dev\n ```\n\n## Running the Application\n\nAfter installing the dependencies, you can run the application using the following steps:\n\n1. **Install Ollama** (Linux example):\n\n ```sh\n curl -fsSL https://ollama.com/install.sh | sh\n ```\n\n2. **Pull the Docker Container for Qdrant**:\n\n ```sh\n docker pull qdrant/qdrant\n ```\n\n3. **Run the Application**:\n\n Run `./run_docker.sh`\n \n In a seperate window, run `python run.py`\n \n Open your web browser and navigate to `http://127.0.0.1:5000` to use Chronica.\n\n## Key Features and Usage\n\n### 1. Creating New Notes\n- Navigate to the **New Entry** page using the \"Add Note\" button on the homepage.\n- Record audio using the big record button, and save the entry.\n- Once saved, the entry will appear in the **Note Gallery**.\n\n### 2. Viewing Notes in the Gallery\n- Use the **Note Gallery** to browse through notes by selecting different time-based filters (month, week, year).\n- Each card in the gallery represents a note, with its **tags** color-coded and its creation time displayed.\n\n### 3. Semantic Search and Statistics\n- Use the **search bar** to find relevant notes. The system uses **semantic search** to match queries with note content.\n- You can also use the search bar to generate and extrapolate given the notes that you have created.\n- You can also view a **statistics overview**, including a word cloud of note summaries.\n\n## License\n\nThis project is licensed under the Creative Commons License. See the **LICENSE** file for details.\n\n## Acknowledgments\n\n- The **Flask** and **Bootstrap** frameworks were used to develop this application.\n- Semantic search and audio transcription functionality use **Ollama** and other LLM models.\n\n## Issues\n\nIf you encounter any issues while using the application, please create an issue.", + "readme_title": "Chronica", + "releases_count": 0, + "repo": "chronica", + "repo_name": "chronica", + "stars": 8, + "topics": [ + "journal", + "llm", + "open-source", + "rag" + ], + "updated_at": "2025-09-29T06:14:59Z", + "url": "https://github.com/lars-quaedvlieg/chronica", + "watchers": 1 + }, + "https://github.com/leonielc/Lauzhack": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'leonielc/Lauzhack'.\"}]", + "owner": "leonielc", + "project_foreign_key": "lhp_8c101cf3d613ee84", + "repo": "Lauzhack" + }, + "https://github.com/lola-monroy/AXA_LauzHack": { + "commit_count_default_branch": 75, + "contributors_count": 4, + "contributors_top": [ + { + "contributions": 28, + "html_url": "https://github.com/lola-monroy", + "login": "lola-monroy" + }, + { + "contributions": 20, + "html_url": "https://github.com/mgil4", + "login": "mgil4" + }, + { + "contributions": 18, + "html_url": "https://github.com/nmayol", + "login": "nmayol" + }, + { + "contributions": 9, + "html_url": "https://github.com/alvarodr21", + "login": "alvarodr21" + } + ], + "created_at": "2024-11-30T12:29:52Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 16, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 19, + "type": "file" + }, + { + "path": "README.md", + "size": 2930, + "type": "file" + }, + { + "path": "annotated_pill_image.png", + "size": 133207, + "type": "file" + }, + { + "path": "appill", + "size": 0, + "type": "dir" + }, + { + "path": "count_point_pills", + "size": 0, + "type": "dir" + }, + { + "path": "data", + "size": 0, + "type": "dir" + }, + { + "path": "package-lock.json", + "size": 91, + "type": "file" + }, + { + "path": "pill_count_results.json", + "size": 126, + "type": "file" + }, + { + "path": "scaler.save", + "size": 677, + "type": "file" + }, + { + "path": "tension", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 66, + "first_commit_date_default_branch": "2024-11-30T15:42:46Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "TypeScript", + "size": 42145 + }, + { + "language": "Python", + "size": 11569 + }, + { + "language": "MATLAB", + "size": 5160 + }, + { + "language": "JavaScript", + "size": 2700 + } + ], + "last_commit_date_default_branch": "2024-12-01T12:48:43Z", + "last_commit_oid_default_branch": "4ebdb640268c687b13c6bddfc5f06497ce885cee", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "lola-monroy/hypertension_appill", + "owner": "lola-monroy", + "parent_repo": null, + "parent_url": null, + "primary_language": "TypeScript", + "project_foreign_key": "lhp_f7ef105e9556588d", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T12:48:52Z", + "readme_length": 2918, + "readme_text": "# APPILL\n# Medication and Tension Monitoring App\nThis project is designed to assist elderly users in managing their medication and monitoring health data through a cross-platform mobile app. It integrates pill shape detection, hypertension prediction, and smartwatch data simulation.\n## Key Features\n- **Add Medication Information**: Users can add basic information like dosage, and schedule.\n- **Verify Medication Taken**: By taking a picture of the pill, the app will apply computer vision operations to ensure that the correct pill has been taken.\n- **Secure Data Storage**: We store user data in a secure way, localy, to ensure privacy.\n- **Hypertension Risk Prediction**: Machine learning model predicts the likelihood of hypertension using health metrics, keeping them simple without doing overkill.\n- **Smartwatch Data Simulation**: Generates simulated health data, including heart rate, variability, and steps, for health tracking and alerts.\n\n## Technologies Used\n- **React Native:** For building a cross-platform mobile app with a simple and intuitive interface, designed for elderly users.\n- **MATLAB (Image Processing):** Used to prototype pill recognition algorithms based on basic morphological operations like erosions and contour detection. Later converted to a python script for better manipulation. \n- **Python:** Backend implementation of image processing algorithms, transitioning from MATLAB for better integration with the app and scalability.\n\n## File structure\n### Main Project\n- apill/: app, components, assets, hooks, scripts: Mobile app code written in React Native.\n package.json & package-lock.json: Dependency management for the mobile app​\n- tsconfig.json: TypeScript configuration for the app.\n- README.md: Documentation for the project\n\n### Counting pills\n- count_python.py: Script for detecting and counting pills using OpenCV and scikit-image​\n- pillX.jpeg: Sample pill images for testing.\n- count_matlab.m & count_matlab_note.mlx: MATLAB scripts for prototyping pill recognition algorithms.\n\n### Hypertension prediction\n- data_hypertension/hypertension_data.csv: Dataset for training the hypertension prediction model.\ntension/:\n- hypertension_model.h5: Saved trained model.\n- model_training.py: Model training script using TensorFlow/Keras​\n- prediccions.py: Flask API for making predictions​\n- scaler.save: Scaler object for data normalization.\n\n### Smartwatch simulation \n- smartwatch.py: Simulates smartwatch data for health metrics like heart rate and steps​.\n\n## Future Improvements\n- **Accessibility Features**: Provide audio instructions for better accessibility.\n- **Take the photo on the spot**: Instead of having to upload it from computer.\n\n\n## Contributing\nIf you want to contribute, please fork the repository, make your changes, and submit a pull request. We welcome all improvements and suggestions!\n\n## License\nThis project is licensed under the MIT License.", + "readme_title": "APPILL", + "releases_count": 0, + "repo": "AXA_LauzHack", + "repo_name": "hypertension_appill", + "stars": 2, + "topics": [], + "updated_at": "2024-12-09T23:42:22Z", + "url": "https://github.com/lola-monroy/hypertension_appill", + "watchers": 1 + }, + "https://github.com/lucat1/ubs-lauz": { + "commit_count_default_branch": 23, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 18, + "html_url": "https://github.com/lucat1", + "login": "lucat1" + }, + { + "contributions": 3, + "html_url": "https://github.com/faguccio", + "login": "faguccio" + }, + { + "contributions": 2, + "html_url": null, + "login": "geno" + } + ], + "created_at": "2024-11-30T12:54:37Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": ".gitattributes", + "size": 42, + "type": "file" + }, + { + "path": ".gitignore", + "size": 15, + "type": "file" + }, + { + "path": "README.md", + "size": 46, + "type": "file" + }, + { + "path": "account_booking_test.csv", + "size": 134, + "type": "file" + }, + { + "path": "account_booking_train.csv", + "size": 131, + "type": "file" + }, + { + "path": "boilerplate.ipynb", + "size": 1024, + "type": "file" + }, + { + "path": "cache.ipynb", + "size": 1983, + "type": "file" + }, + { + "path": "coarse_filter.ipynb", + "size": 23028, + "type": "file" + }, + { + "path": "d_city.pkl", + "size": 38735526, + "type": "file" + }, + { + "path": "d_name.pkl", + "size": 43262635, + "type": "file" + }, + { + "path": "external_parties_test.csv", + "size": 134, + "type": "file" + }, + { + "path": "external_parties_train.csv", + "size": 132, + "type": "file" + }, + { + "path": "fg-notebook.ipynb", + "size": 3870, + "type": "file" + }, + { + "path": "poetry.lock", + "size": 193885, + "type": "file" + }, + { + "path": "pyproject.toml", + "size": 409, + "type": "file" + }, + { + "path": "shell.nix", + "size": 280, + "type": "file" + } + ], + "files_total_count": 16, + "first_commit_date_default_branch": "2024-11-30T12:54:22Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 29905 + }, + { + "language": "Nix", + "size": 280 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:51:56Z", + "last_commit_oid_default_branch": "6cb799b348e2fa66a6e1ff7cb796d48340b9151a", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "lucat1/ubs-lauz", + "owner": "lucat1", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_cbbd89f32e171b76", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:52:06Z", + "readme_length": 46, + "readme_text": "# Development\n\n```\n$ poetry shell\n$ code .\n```", + "readme_title": "Development", + "releases_count": 0, + "repo": "ubs-lauz", + "repo_name": "ubs-lauz", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T12:05:08Z", + "url": "https://github.com/lucat1/ubs-lauz", + "watchers": 1 + }, + "https://github.com/martina-ignacia-hernandez/LauzHack": { + "commit_count_default_branch": 9, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 4, + "html_url": "https://github.com/martina-ignacia-hernandez", + "login": "martina-ignacia-hernandez" + }, + { + "contributions": 3, + "html_url": "https://github.com/m4riiona", + "login": "m4riiona" + }, + { + "contributions": 2, + "html_url": "https://github.com/joanriera13", + "login": "joanriera13" + } + ], + "created_at": "2024-11-30T17:38:59Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 3, + "files_root_entries": [ + { + "path": "Business_Webb", + "size": 0, + "type": "dir" + }, + { + "path": "FAID", + "size": 0, + "type": "dir" + }, + { + "path": "Fraud_AI_Detector.ipynb", + "size": 1065582, + "type": "file" + }, + { + "path": "README.md", + "size": 1824, + "type": "file" + } + ], + "files_total_count": 14, + "first_commit_date_default_branch": "2024-11-30T17:39:00Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 1065582 + }, + { + "language": "HTML", + "size": 54742 + }, + { + "language": "JavaScript", + "size": 10781 + }, + { + "language": "CSS", + "size": 5069 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:54:45Z", + "last_commit_oid_default_branch": "bf175fce915f50b948db58614b4e29a44b79cbbe", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "martina-ignacia-hernandez/LauzHack", + "owner": "martina-ignacia-hernandez", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_fb9c58fbfabdea35", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:54:45Z", + "readme_length": 1823, + "readme_text": "# Fraud AI Detector\n\nThis project is an AI-Generated Fake Audio Detector designed to identify fraudulent or synthetic audio content, particularly in the context of phone calls. Its primary goal is to enhance communication security by detecting AI-generated audios that could be used in scams or fraudulent schemes.\n\nThe system processes 5-second audio segments from phone calls, extracts critical audio features, and uses machine learning or deep learning models to determine if the audio is real or generated by AI. This is especially useful for organizations or individuals looking to protect themselves against the growing threats of voice spoofing and synthetic speech technologies.\n\nKey capabilities of the project include:\n\nDetection of AI-generated audio: Uses advanced analysis techniques to differentiate between real and synthetic speech.\nEfficient processing: Operates on small audio segments, enabling rapid evaluation of phone call content.\nFeature extraction: Employs state-of-the-art methods to capture distinctive characteristics of speech, such as MFCCs (Mel Frequency Cepstral Coefficients), Chroma features, and Mel spectrograms.\nModel-based classification: Implements trained models for real-time classification, which can be adapted for specific use cases with new data.\n\nOther applications could be:\n\nVerification systems: Ensuring the authenticity of voice-based transactions or communications.\nVoice security: Detecting and mitigating vulnerabilities in systems reliant on voice interactions.\n\nThe repository includes tools for preprocessing audio, extracting features, training classification models, and making predictions on unseen data. It is built with scalability and ease of use in mind, allowing organizations to integrate the solution into their communication workflows or security systems.", + "readme_title": "Fraud AI Detector", + "releases_count": 0, + "repo": "LauzHack", + "repo_name": "LauzHack", + "stars": 3, + "topics": [], + "updated_at": "2026-03-09T14:44:47Z", + "url": "https://github.com/martina-ignacia-hernandez/LauzHack", + "watchers": 1 + }, + "https://github.com/mpoupet/LauzHack_Vitol": { + "commit_count_default_branch": 1, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 1, + "html_url": "https://github.com/mpoupet", + "login": "mpoupet" + } + ], + "created_at": "2024-10-13T08:11:39Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": "README.md", + "size": 16, + "type": "file" + } + ], + "files_total_count": 1, + "first_commit_date_default_branch": "2024-10-13T08:11:39Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [], + "last_commit_date_default_branch": "2024-10-13T08:11:39Z", + "last_commit_oid_default_branch": "c34c74f592b3c7c7a5e21e868ee922463b8b3f84", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "mpoupet/LauzHack_Vitol", + "owner": "mpoupet", + "parent_repo": null, + "parent_url": null, + "primary_language": null, + "project_foreign_key": "lhp_3dd46def47d11cc3", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-10-13T08:11:39Z", + "readme_length": 16, + "readme_text": "# LauzHack_Vitol", + "readme_title": "LauzHack_Vitol", + "releases_count": 0, + "repo": "LauzHack_Vitol", + "repo_name": "LauzHack_Vitol", + "stars": 0, + "topics": [], + "updated_at": "2024-10-13T08:11:43Z", + "url": "https://github.com/mpoupet/LauzHack_Vitol", + "watchers": 1 + }, + "https://github.com/nastiapetrovych/UBS_Lauzhack": { + "commit_count_default_branch": 4, + "contributors_count": 2, + "contributors_top": [ + { + "contributions": 3, + "html_url": "https://github.com/nastiapetrovych", + "login": "nastiapetrovych" + }, + { + "contributions": 1, + "html_url": "https://github.com/mowachab", + "login": "mowachab" + } + ], + "created_at": "2024-11-30T17:12:29Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": "Final_solution.ipynb", + "size": 20228906, + "type": "file" + }, + { + "path": "README.md", + "size": 81, + "type": "file" + } + ], + "files_total_count": 2, + "first_commit_date_default_branch": "2024-12-01T10:56:52Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 20228906 + } + ], + "last_commit_date_default_branch": "2024-12-01T11:03:13Z", + "last_commit_oid_default_branch": "9cb72a3d5b522c04a41dd44128d5b80ee6c5e0b2", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "nastiapetrovych/UBS_Lauzhack", + "owner": "nastiapetrovych", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_5d131c61a8f359b3", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T11:03:14Z", + "readme_length": 80, + "readme_text": "Team members: Anastasiia Petrovych, Anna Polova, Abhijeet Sharma, Wafiq Chahboun", + "readme_title": "Team members: Anastasiia Petrovych, Anna Polova, Abhijeet Sharma, Wafiq Chahboun", + "releases_count": 0, + "repo": "UBS_Lauzhack", + "repo_name": "UBS_Lauzhack", + "stars": 3, + "topics": [], + "updated_at": "2024-12-15T15:28:32Z", + "url": "https://github.com/nastiapetrovych/UBS_Lauzhack", + "watchers": 1 + }, + "https://github.com/robertobendi/Hackaton2024": { + "commit_count_default_branch": 1, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 1, + "html_url": "https://github.com/robertobendi", + "login": "robertobendi" + } + ], + "created_at": "2024-11-30T16:49:46Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": ".gitattributes", + "size": 66, + "type": "file" + }, + { + "path": ".gitignore", + "size": 1284, + "type": "file" + } + ], + "files_total_count": 2, + "first_commit_date_default_branch": "2024-11-30T16:46:20Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": false, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [], + "last_commit_date_default_branch": "2024-11-30T16:46:20Z", + "last_commit_oid_default_branch": "18d8e14e825acfab6fde6d3883c8538af27db27b", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "robertobendi/Hackaton2024", + "owner": "robertobendi", + "parent_repo": null, + "parent_url": null, + "primary_language": null, + "project_foreign_key": "lhp_281c8becb5304c80", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-11-30T16:49:48Z", + "readme_length": null, + "readme_text": null, + "readme_title": null, + "releases_count": 0, + "repo": "Hackaton2024", + "repo_name": "Hackaton2024", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T14:07:51Z", + "url": "https://github.com/robertobendi/Hackaton2024", + "watchers": 1 + }, + "https://github.com/rogerbaiges/LauzHack2024": { + "commit_count_default_branch": 89, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 31, + "html_url": "https://github.com/pauhidalgoo", + "login": "pauhidalgoo" + }, + { + "contributions": 30, + "html_url": "https://github.com/rogerbaiges", + "login": "rogerbaiges" + }, + { + "contributions": 28, + "html_url": "https://github.com/caiselvas", + "login": "caiselvas" + } + ], + "created_at": "2024-11-30T15:12:39Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 7, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 61, + "type": "file" + }, + { + "path": ".streamlit", + "size": 0, + "type": "dir" + }, + { + "path": "GroundingDINO", + "size": 0, + "type": "file" + }, + { + "path": "Images", + "size": 0, + "type": "dir" + }, + { + "path": "README.md", + "size": 14, + "type": "file" + }, + { + "path": "app.py", + "size": 8031, + "type": "file" + }, + { + "path": "controller.py", + "size": 7448, + "type": "file" + }, + { + "path": "faces", + "size": 0, + "type": "dir" + }, + { + "path": "functions.py", + "size": 402, + "type": "file" + }, + { + "path": "gpt_old_interface", + "size": 0, + "type": "dir" + }, + { + "path": "image_color_changed.png", + "size": 2407399, + "type": "file" + }, + { + "path": "image_segmented.png", + "size": 114320, + "type": "file" + }, + { + "path": "llm.py", + "size": 2749, + "type": "file" + }, + { + "path": "other_functions.py", + "size": 608, + "type": "file" + }, + { + "path": "prompts", + "size": 0, + "type": "dir" + }, + { + "path": "samsam", + "size": 0, + "type": "file" + }, + { + "path": "satelite.png", + "size": 2431965, + "type": "file" + }, + { + "path": "satelite_similar_features.png", + "size": 2257610, + "type": "file" + }, + { + "path": "segmentor.py", + "size": 40852, + "type": "file" + }, + { + "path": "static", + "size": 0, + "type": "dir" + }, + { + "path": "streamlit_app.py", + "size": 5521, + "type": "file" + }, + { + "path": "templates", + "size": 0, + "type": "dir" + }, + { + "path": "test.py", + "size": 165, + "type": "file" + }, + { + "path": "test_groundino.py", + "size": 705, + "type": "file" + }, + { + "path": "test_sam.py", + "size": 2996, + "type": "file" + }, + { + "path": "test_similar.py", + "size": 5376, + "type": "file" + }, + { + "path": "testing.ipynb", + "size": 34156025, + "type": "file" + } + ], + "files_total_count": 56, + "first_commit_date_default_branch": "2024-11-30T15:12:39Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 34156025 + }, + { + "language": "Python", + "size": 77427 + }, + { + "language": "JavaScript", + "size": 27147 + }, + { + "language": "CSS", + "size": 10336 + }, + { + "language": "HTML", + "size": 4970 + } + ], + "last_commit_date_default_branch": "2024-12-01T13:42:55Z", + "last_commit_oid_default_branch": "5a256959c57964f81831784e7dc61eb33fef0a0e", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "rogerbaiges/LauzHack2024", + "owner": "rogerbaiges", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_ba9a76236dfd1062", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T13:43:02Z", + "readme_length": 14, + "readme_text": "# LauzHack2024", + "readme_title": "LauzHack2024", + "releases_count": 0, + "repo": "LauzHack2024", + "repo_name": "LauzHack2024", + "stars": 2, + "topics": [], + "updated_at": "2024-12-01T13:43:22Z", + "url": "https://github.com/rogerbaiges/LauzHack2024", + "watchers": 1 + }, + "https://github.com/sid030sid/self-sovereign-ecolens": { + "commit_count_default_branch": 8, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 8, + "html_url": "https://github.com/sid030sid", + "login": "sid030sid" + } + ], + "created_at": "2024-11-30T11:33:48Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 20, + "files_root_entries": [ + { + "path": ".gitattributes", + "size": 66, + "type": "file" + }, + { + "path": ".gitignore", + "size": 17, + "type": "file" + }, + { + "path": "README.md", + "size": 2628, + "type": "file" + }, + { + "path": "issuer", + "size": 0, + "type": "dir" + }, + { + "path": "verifier", + "size": 0, + "type": "dir" + } + ], + "files_total_count": 55, + "first_commit_date_default_branch": "2024-11-30T10:20:25Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "JavaScript", + "size": 41759 + }, + { + "language": "HTML", + "size": 3171 + }, + { + "language": "CSS", + "size": 792 + } + ], + "last_commit_date_default_branch": "2024-12-01T09:54:21Z", + "last_commit_oid_default_branch": "285ef98d12d8ddfbdb387f87f4c8a707a7d78c7f", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "sid030sid/self-sovereign-ecolens", + "owner": "sid030sid", + "parent_repo": null, + "parent_url": null, + "primary_language": "JavaScript", + "project_foreign_key": "lhp_1082270700a8d521", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:23:46Z", + "readme_length": 2627, + "readme_text": "# Self-sovereign Ecolens\n\n## About\nEcolens is a mobile app for students to gain points for chosing environmentally friendly meals offered on-campus. These ``eco-points`` can be used for rewards, such as discounts for the next meals or little prices. Besides, this financial incentive, Ecolens uses gamification to additionally motivate students to chose the environemntally for facilitating (Read more on the Ecolens Project [here](https://zeroemission.group/ecolens/)). This repo provides the technical infrastructure to issue and verify eco-points using the Self-Sovereign Identiy paradigm that guranteeis the sovereignity of students over their private data while guranteeing the functionality of the ecolens application.\n\n## Repo overview\n- Branch `issuer-web-app` contains a web app that issuers of eco-points can use during the conduct of their ordinary business. issuers of eco-points are restaurants or food stands on-campus that sell meals to students and use Ecolens to reward them for chosing their ecologically friendly meal choices. \n- Branch `verfifier-web-app` contains an examplary web app that can be used by verifiers of eco-points. In general, verifiers of eco-points are legal entities that accept eco-points to give out discounts, prizes, or any other financial incentives. The examplary web app is for restaurants that allow their customers to buy meals with eco-points, thus incentivising environmentally friendly food consumption.+\n- **NOTE**: the code in the folders `issuer` and `verifier` should be ignored!\n\n## How to...\n### ... set up?\nTBA\n\n### ... start web app for issuer and verifier of eco-point Verifiable Credentials?\nTBA\n\n## FAQ\n### Why use Ecolens as a student?\nGet Eco-points which can be used to get financial rewards for eating ecofriendly meals on-campus. Share your sustainable eating habit to your fellow students to encourage them to eat ecofriendly as well...without comprising your privacy thanks to Ecolen's usage of Zero Knowledge Proofs.\n\n### Why use Ecolens as a restaurant?\nBrandy your restaurant to be eco-friendly and an advocate of a sustainable future.\n\n### Why accept eco-points awarded through Ecolens for discounts, prices, and other financial incentives?\nBy accepting eco-points, their owners have more options to use their eco-points for financial rewards, motivating them to continue eating ecofriendly. Moreover, the more options there are to use eco-points in daily business processes, the more people will join Ecolens and thus the movement of eating stustainbly. Therefore, legal entities accepting eco-points for discounts, prices, or other financial incentives", + "readme_title": "Self-sovereign Ecolens", + "releases_count": 0, + "repo": "self-sovereign-ecolens", + "repo_name": "self-sovereign-ecolens", + "stars": 1, + "topics": [], + "updated_at": "2024-12-30T13:00:56Z", + "url": "https://github.com/sid030sid/self-sovereign-ecolens", + "watchers": 1 + }, + "https://github.com/soohyukkkkkkkkkkk/vitol-gojo": { + "commit_count_default_branch": 1, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 1, + "html_url": "https://github.com/soohyukkkkkkkkkkk", + "login": "soohyukkkkkkkkkkk" + } + ], + "created_at": "2024-11-30T17:50:29Z", + "default_branch": "main", + "description": "Image segmentation based on YOLO for live-streaming frames, identifying types and structures.", + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": "live_stream.ipynb", + "size": 21185, + "type": "file" + } + ], + "files_total_count": 1, + "first_commit_date_default_branch": "2024-11-30T18:01:00Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": false, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 21185 + } + ], + "last_commit_date_default_branch": "2024-11-30T18:01:00Z", + "last_commit_oid_default_branch": "a5a97fbfa98683105b4d391088445a754a26261e", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "soohyukkkkkkkkkkk/vitol-gojo", + "owner": "soohyukkkkkkkkkkk", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_a3279557c82f27b3", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-11-30T18:01:01Z", + "readme_length": null, + "readme_text": null, + "readme_title": null, + "releases_count": 0, + "repo": "vitol-gojo", + "repo_name": "vitol-gojo", + "stars": 0, + "topics": [], + "updated_at": "2024-11-30T18:01:04Z", + "url": "https://github.com/soohyukkkkkkkkkkk/vitol-gojo", + "watchers": 1 + }, + "https://github.com/stefanoviel/ubsChallenge": { + "commit_count_default_branch": 4, + "contributors_count": 2, + "contributors_top": [ + { + "contributions": 3, + "html_url": "https://github.com/alessandrodalbesio", + "login": "alessandrodalbesio" + }, + { + "contributions": 1, + "html_url": "https://github.com/stefanoviel", + "login": "stefanoviel" + } + ], + "created_at": "2024-11-30T17:42:36Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": ".DS_Store", + "size": 6148, + "type": "file" + }, + { + "path": ".gitignore", + "size": 5, + "type": "file" + }, + { + "path": "README.md", + "size": 1969, + "type": "file" + }, + { + "path": "main.ipynb", + "size": 69257, + "type": "file" + } + ], + "files_total_count": 4, + "first_commit_date_default_branch": "2024-12-01T06:36:02Z", + "forks": 1, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 69257 + } + ], + "last_commit_date_default_branch": "2024-12-01T11:08:52Z", + "last_commit_oid_default_branch": "49fac953f7fcd8f8f52316dcc1f82b141d34fd4b", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "stefanoviel/ubsChallenge", + "owner": "stefanoviel", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_9a6246b40320fe27", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T11:08:53Z", + "readme_length": 1969, + "readme_text": "# UBSolver\nIn this challenge we have tried to solve the problem proposed by UBS about the Entity Resolution Challenge.
\nOur solution is very time efficient and has a very good performance on the test dataset provided (we got a F-score of 0.87).\n\n## Code structure\nThe code can be is in the main.ipynb file and it includes:\n- A cleaning section: we have used some rules to clean the data and reduce the number of samples.\n- A processing section: we compute some similarity metrics that we are then going to use to match the samples.\n- A matching section: we match together similar samples with a graph-based approach.\n\n## The idea\nThe main ideas that we have used are:\n- Since we are in a case with lots of data (bilions!) we need to reduce them to avoid too high computational costs. For this reason we matched together samples that are clearly the same (i.e. IBAN, name, address, etc.). This was inspired by the observatin that almost all the transaction from a common entity matched on at least one of the features.
\n- For every pair of matched elements we compute the Levenshtein similarity (all the features are strings) is computed for every feature.
\n- We trained a Neural Network to predict if two samples are the same or not based on the similarity scores computed before. This neural network is very simple since it's a multi-layer perceptron with 2 hidden layers (100 - 50 neurons).
\n- Finally we created a graph on the test set and we used the trained Neural Network to match together samples that are similar. Another important observation which allowed us to efficiently create the set was to discard the values which appeared too often as they weren't significant to match the entities.
\n- Each strongly connected component of the graph is an entity representing a person or a company.\n\n## The team\nOur team:\n- Matteo Santelmo matteo.santelmo@epfl.ch\n- Alessandro Dalbesio alessandro.dalbesio@epfl.ch\n- Stefano Viel stefano.viel@epfl.ch", + "readme_title": "UBSolver", + "releases_count": 0, + "repo": "ubsChallenge", + "repo_name": "ubsChallenge", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T11:08:56Z", + "url": "https://github.com/stefanoviel/ubsChallenge", + "watchers": 1 + }, + "https://github.com/tferracina/agriviewer": { + "commit_count_default_branch": 45, + "contributors_count": 4, + "contributors_top": [ + { + "contributions": 32, + "html_url": "https://github.com/tferracina", + "login": "tferracina" + }, + { + "contributions": 7, + "html_url": "https://github.com/Gmo23", + "login": "Gmo23" + }, + { + "contributions": 5, + "html_url": "https://github.com/1uc0s", + "login": "1uc0s" + }, + { + "contributions": 1, + "html_url": "https://github.com/Thuna-Cing", + "login": "Thuna-Cing" + } + ], + "created_at": "2024-11-30T17:41:16Z", + "default_branch": "main", + "description": "LauzHack 2024 Submission", + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 114, + "type": "file" + }, + { + "path": "README.md", + "size": 2267, + "type": "file" + }, + { + "path": "SegandAnalysis.ipynb", + "size": 3146950, + "type": "file" + }, + { + "path": "config.py", + "size": 590, + "type": "file" + }, + { + "path": "cv_analyzer.py", + "size": 4058, + "type": "file" + }, + { + "path": "llm_engine.py", + "size": 8240, + "type": "file" + }, + { + "path": "llme_instructions.py", + "size": 3072, + "type": "file" + }, + { + "path": "main.py", + "size": 6079, + "type": "file" + }, + { + "path": "ph_instructions.py", + "size": 953, + "type": "file" + }, + { + "path": "prompt_handler.py", + "size": 4136, + "type": "file" + }, + { + "path": "req.txt", + "size": 2100, + "type": "file" + }, + { + "path": "results_parser.py", + "size": 2987, + "type": "file" + }, + { + "path": "satelliteload.ipynb", + "size": 4055729, + "type": "file" + }, + { + "path": "streamlit_app.py", + "size": 10528, + "type": "file" + }, + { + "path": "streamlit_visualizer.py", + "size": 1805, + "type": "file" + }, + { + "path": "visualizer.py", + "size": 3919, + "type": "file" + } + ], + "files_total_count": 16, + "first_commit_date_default_branch": "2024-11-30T17:45:25Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 7202679 + }, + { + "language": "Python", + "size": 46367 + } + ], + "last_commit_date_default_branch": "2024-12-02T15:58:38Z", + "last_commit_oid_default_branch": "cabb95cdef69a07b18c1fa3c3e8eb564c66adc20", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "tferracina/agriviewer", + "owner": "tferracina", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_8561683283ce19f5", + "pull_requests_closed": 1, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 1, + "pushed_at": "2024-12-02T15:58:41Z", + "readme_length": 2264, + "readme_text": "# Agriview\n\n## The intersection of computer vision and LLM's. A chatbot designed to convey information on fields using semantic segmentation on satelite imagery. \n\nAgriview is an agricultural intelligence platform that leverages satellite imagery, computer vision, and large language models to provide actionable insights for farmers, traders or land surveyors.\n\n### Problem Statement\n\nAgricultural decision-making requires complex data analysis from satellite imagery. Agriview simplifies this process by translating complex satellite data into understandable, actionable insights.\n\n\n### Technologies\n\n - Satellite Data Acquisition: Copernicus Browser (Sentinel-2)\n - Segmentation model: Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks (https://github.com/VSainteuf/utae-paps?tab=readme-ov-file)\n - Image Processing: Rasterio\n - AI Interaction: LlamaIndex\n - Computer Vision: Custom crop field segmentation model\n - Language Model: LLAMA 8B Instruct\n\n### Key Features\n- Intelligent Data Parsing\n- Converts plain text instructions into computational variables\n- Uses LLAMA 8B Instruct model for precise instruction parsing\n\n#### Satellite Image Analysis\n\n- Segments crop fields from satellite time series data\n- Identifies and masks different crop types\n- Calculates agricultural metrics (e.g., moisture index)\n\n#### Retrieval-Augmented Generation (RAG)\n\n- Stores and references previous query information\n- Enables multi-year comparative analysis\n\n### Workflow\n\n- Input: User provides a natural language query\n- Parsing: LLAMA model transforms query into actionable variables\n- Image Processing: Computer vision model analyzes satellite imagery\n- Metric Calculation: Extracts relevant agricultural metrics\n- Insight Generation: LLM provides contextualized, actionable insights\n\n#### Example Use Case\nQuery: \"What's the agricultural outlook for wheat in Kentucky this season?\"\n\nResponse: \"The average moisture NDMI of wheat fields at this time of year in Kentucky is [X], indicating a high yield compared to previous years where it was [Y].\"\n\n\n### Future Roadmap\n\n - Enhanced segmentation models\n - Expanded crop and region coverage\n - More advanced predictive analytics\n - Time series data for historic analysis", + "readme_title": "Agriview", + "releases_count": 0, + "repo": "agriviewer", + "repo_name": "agriviewer", + "stars": 2, + "topics": [], + "updated_at": "2024-12-10T10:00:43Z", + "url": "https://github.com/tferracina/agriviewer", + "watchers": 1 + }, + "https://github.com/theChopix/lauzhack24": { + "commit_count_default_branch": 4, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 2, + "html_url": "https://github.com/Sayantan0013", + "login": "Sayantan0013" + }, + { + "contributions": 1, + "html_url": "https://github.com/clandolt", + "login": "clandolt" + }, + { + "contributions": 1, + "html_url": "https://github.com/theChopix", + "login": "theChopix" + } + ], + "created_at": "2024-11-30T17:46:03Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": "README.md", + "size": 12, + "type": "file" + }, + { + "path": "elastic.ipynb", + "size": 35245, + "type": "file" + }, + { + "path": "test_predictions.py", + "size": 1765, + "type": "file" + } + ], + "files_total_count": 3, + "first_commit_date_default_branch": "2024-11-30T18:59:21Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": true, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Jupyter Notebook", + "size": 35245 + }, + { + "language": "Python", + "size": 1765 + } + ], + "last_commit_date_default_branch": "2024-12-01T09:00:22Z", + "last_commit_oid_default_branch": "1fce46e0b6fffa55e5bd5f7f2a99629f6947b6e1", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "theChopix/lauzhack24", + "owner": "theChopix", + "parent_repo": null, + "parent_url": null, + "primary_language": "Jupyter Notebook", + "project_foreign_key": "lhp_ce5f6decdc8e86ac", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T11:03:35Z", + "readme_length": 12, + "readme_text": "# lauzhack24", + "readme_title": "lauzhack24", + "releases_count": 0, + "repo": "lauzhack24", + "repo_name": "lauzhack24", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T09:00:29Z", + "url": "https://github.com/theChopix/lauzhack24", + "watchers": 1 + }, + "https://github.com/tulga-rdn/b-helper": { + "commit_count_default_branch": 5, + "contributors_count": 1, + "contributors_top": [ + { + "contributions": 5, + "html_url": "https://github.com/tulga-rdn", + "login": "tulga-rdn" + } + ], + "created_at": "2024-12-01T10:40:23Z", + "default_branch": "main", + "description": "B-Helper is an app that helps supervisors control production line data and sends important (really urgent and thus very rare) info to supervisors when they are off-duty", + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": ".gitignore", + "size": 3139, + "type": "file" + }, + { + "path": "README.md", + "size": 3424, + "type": "file" + }, + { + "path": "main.py", + "size": 5595, + "type": "file" + }, + { + "path": "test_bigmotor.py", + "size": 540, + "type": "file" + }, + { + "path": "test_curr.py", + "size": 433, + "type": "file" + }, + { + "path": "test_discord.py", + "size": 1241, + "type": "file" + }, + { + "path": "test_error.py", + "size": 1230, + "type": "file" + }, + { + "path": "test_iot.py", + "size": 3423, + "type": "file" + }, + { + "path": "test_ir.py", + "size": 750, + "type": "file" + }, + { + "path": "test_irus.py", + "size": 3293, + "type": "file" + }, + { + "path": "test_us.py", + "size": 1433, + "type": "file" + } + ], + "files_total_count": 11, + "first_commit_date_default_branch": "2024-12-01T10:40:23Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 17938 + } + ], + "last_commit_date_default_branch": "2024-12-01T13:50:07Z", + "last_commit_oid_default_branch": "034803139858dfee3482cfd626f7b8968958d459", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "tulga-rdn/b-helper", + "owner": "tulga-rdn", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_cfff3ecb9175d1e8", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T13:50:07Z", + "readme_length": 3423, + "readme_text": "# B-Helper\n\n**B-Helper** is a production line monitoring app designed for supervisors. It allows them to track and control production line data efficiently and ensures critical alerts are sent to supervisors, even when they are off-duty. This helps streamline production processes, monitor machine health, and handle rare yet urgent issues without delay.\n\n---\n\n## Features\n\n- **Real-Time Telemetry**: Sends live telemetry data about production, including machine state, speed, and output counts, via Azure IoT Hub.\n- **Error Handling and Alerts**:\n - Detects production line errors (e.g., oversized boxes, sensor mismatches) and sends alerts via Discord.\n - Handles unexpected machine stoppages and informs supervisors immediately.\n- **Production Control**:\n - Monitors object detection and box sizes using IR and ultrasonic sensors.\n - Controls motor speeds and manages machine start/stop operations programmatically.\n- **Hardware Integration**:\n - Utilizes GPIO, PWM, and current sensors (INA219) for physical production line monitoring.\n - Sends detailed telemetry to Azure IoT Hub for further analysis.\n\n---\n\n## Architecture\n\n1. **IoT Communication**: Data is sent to Azure IoT Hub using the `IoTHubDeviceClient` library.\n2. **Alerts System**: Alerts are sent via Discord using Webhooks for both telemetry updates and critical errors.\n3. **Sensor Systems**:\n - **IR Sensors**: Tracks object detection and logs production output.\n - **Ultrasonic Sensors**: Monitors object proximity to ensure size compliance.\n - **Current Sensors**: INA219-based current monitoring for machine health.\n\n---\n\n## Installation\n\n### Prerequisites\n\n1. Python 3.8+\n2. Required libraries:\n - `azure.iot.device`\n - `lgpio`\n - `requests`\n - `adafruit-ina219` (for current sensing)\n3. IoT Hub Connection String and Discord Webhook URL.\n\n### Setup\n\n1. Clone the repository:\n ```bash\n git clone https://github.com/tulga-rdn/b-helper/\n cd b-helper\n ```\n\n2. Install dependencies.\n\n3. Configure your connection settings:\n - Update the `CONNECTION_STRING` and `DISCORD_WEBHOOK_URL` placeholders in `main.py`.\n\n4. Run the application:\n ```bash\n python main.py\n ```\n\n---\n\n## Usage\n\n- **Starting the Application**: Running `main.py` starts the motor and enables the IR and ultrasonic sensors to monitor production.\n- **Alerts**:\n - Alerts are sent via Discord when:\n - Machine starts/stops unexpectedly.\n - Errors such as oversized boxes or sensor mismatches are detected.\n - Alerts are configured in `test_discord.py` and `test_error.py`.\n\n---\n\n## Key Modules\n\n1. **`main.py`**: Core logic for telemetry, sensor integration, and IoT Hub communication.\n2. **`test_ir.py`**: Handles IR sensor-based object detection.\n3. **`test_us.py`**: Manages ultrasonic sensor operations for proximity monitoring.\n4. **`test_irus.py`**: Integrates both IR and ultrasonic sensors for comprehensive monitoring.\n5. **`test_iot.py`**: Tests IoT Hub communication and telemetry functions.\n6. **`test_curr.py`**: Reads current measurements from the INA219 sensor.\n7. **`test_bigmotor.py`**: Manages motor control operations for production.\n\n---\n\n## Future Enhancements\n\n- Improved analytics and dashboards via Azure IoT Central.\n- Machine learning models for predictive maintenance and anomaly detection.\n- Additional notification channels (e.g., SMS or email).\n\n## Contributors\n\n- Tulga-Erdene Sodjargal\n- Fakhriyya Mammadova\n\n---", + "readme_title": "B-Helper", + "releases_count": 0, + "repo": "b-helper", + "repo_name": "b-helper", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T13:50:10Z", + "url": "https://github.com/tulga-rdn/b-helper", + "watchers": 1 + }, + "https://github.com/verooo0/Lauzhack_pack": { + "commit_count_default_branch": 7, + "contributors_count": 3, + "contributors_top": [ + { + "contributions": 5, + "html_url": "https://github.com/marinatlj", + "login": "marinatlj" + }, + { + "contributions": 1, + "html_url": "https://github.com/verooo0", + "login": "verooo0" + }, + { + "contributions": 1, + "html_url": "https://github.com/jowi2033", + "login": "jowi2033" + } + ], + "created_at": "2024-11-30T16:49:07Z", + "default_branch": "main", + "description": null, + "dirs_total_count": 0, + "files_root_entries": [ + { + "path": "README.md", + "size": 303, + "type": "file" + }, + { + "path": "mini_smart_factory_main.py", + "size": 4702, + "type": "file" + } + ], + "files_total_count": 2, + "first_commit_date_default_branch": "2024-11-30T16:49:08Z", + "forks": 0, + "has_ci": false, + "has_contributing": false, + "has_docker": false, + "has_docs": false, + "has_license_file": false, + "has_notebooks": false, + "has_readme_file": true, + "has_tests": false, + "homepage_url": null, + "is_archived": false, + "is_fork": false, + "is_private": false, + "issues_closed": 0, + "issues_open": 0, + "issues_total": 0, + "languages_top": [ + { + "language": "Python", + "size": 4702 + } + ], + "last_commit_date_default_branch": "2024-12-01T10:51:13Z", + "last_commit_oid_default_branch": "a39b65868268e1a6f46942d60150084196bc927b", + "latest_release_date": null, + "latest_release_tag": null, + "license_name": null, + "license_spdx": null, + "name_with_owner": "verooo0/Lauzhack_pack", + "owner": "verooo0", + "parent_repo": null, + "parent_url": null, + "primary_language": "Python", + "project_foreign_key": "lhp_c49fec6035a7da25", + "pull_requests_closed": 0, + "pull_requests_merged": 0, + "pull_requests_open": 0, + "pull_requests_total": 0, + "pushed_at": "2024-12-01T10:51:13Z", + "readme_length": 302, + "readme_text": "# Lauzhack_pack\n\nThis project for the LauzHack 2024 from the sponsor BOBST consists in a 'Mini Smart Factory' that controls the production and the quality of the product itself.\n\nIt's based on a Raspberry pi 5 and it uses an IR sensor, ultrasound sensor and a Servo motor to simulate a production line.", + "readme_title": "Lauzhack_pack", + "releases_count": 0, + "repo": "Lauzhack_pack", + "repo_name": "Lauzhack_pack", + "stars": 0, + "topics": [], + "updated_at": "2024-12-01T10:51:17Z", + "url": "https://github.com/verooo0/Lauzhack_pack", + "watchers": 1 + }, + "https://github.com/wesleymth/Lauzhack-2024-Counting-Stuff": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'wesleymth/Lauzhack-2024-Counting-Stuff'.\"}]", + "owner": "wesleymth", + "project_foreign_key": "lhp_e22a02bbb31ca4cf", + "repo": "Lauzhack-2024-Counting-Stuff" + }, + "https://github.com/youssefouru/LauzHack": { + "error": "[{'type': 'NOT_FOUND', 'path': ['repository'], 'locations': [{'line': 3, 'column': 3}], 'message': \"Could not resolve to a Repository with the name 'youssefouru/LauzHack'.\"}]", + "owner": "youssefouru", + "project_foreign_key": "lhp_0cd2785898f6a20c", + "repo": "LauzHack" + } +} \ No newline at end of file