| --- |
| task_categories: |
| - visual-question-answering |
| - object-detection |
| language: |
| - en |
| tags: |
| - remote-sensing |
| - geospatial |
| - satellite-imagery |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # GeoChat_bench_split Dataset |
|
|
| ## Dataset Description |
|
|
| This dataset is a curated subset of the GeoChat_Bench benchmark from the EarthDial-Dataset, specifically containing samples with multiple ground truth bounding boxes. |
| |
| ### Dataset Summary |
| |
| - **Total Samples:** 1,840 |
| - **Source:** akshaydudhane/EarthDial-Dataset (GeoChat_Bench subset) |
| - **Task:** Visual grounding / object localization in satellite imagery |
| - **Modality:** Image (RGB) + Text |
|
|
| ### Dataset Structure |
|
|
| The dataset contains 4 columns: |
|
|
| 1. **question_id** (string): Unique identifier for each sample |
| 2. **jpg** (Image): RGB satellite/aerial image |
| 3. **question** (string): Question asking for object locations (format: "Give me the location of <ref>object description") |
| 4. **groundtruth** (string): Multiple bounding box coordinates in the format `[[x1,y1,x2,y2,confidence]][[x1,y1,x2,y2,confidence]]...` |
| |
| ### Data Fields |
| |
| - `question_id`: Unique sample identifier |
| - `jpg`: PIL Image object in RGB format |
| - `question`: Natural language question with reference tags |
| - `groundtruth`: Serialized list of bounding boxes |
| |
| ### Example |
| |
| ```python |
| { |
| 'question_id': 'sota_2403', |
| 'jpg': <PIL.Image>, |
| 'question': 'Give me the location of <ref>10 large small-vehicles', |
| 'groundtruth': '[[20, 43, 27, 53, 90]][[5, 38, 11, 47, 90]]...' |
| } |
| ``` |
| |
| ## Dataset Creation |
| |
| ### Curation Process |
| |
| 1. Loaded GeoChat_Bench from EarthDial-Dataset |
| 2. Filtered samples containing multiple bounding boxes in ground truth (>1 list) |
| 3. Sorted by number of bounding boxes in descending order |
| 4. Selected top 1,840 samples (all available samples with multiple boxes) |
| 5. Cleaned question text to remove formatting prefixes and tags |
| |
| ### Source Data |
| |
| Original dataset: [EarthDial-Dataset](https://huggingface.co/datasets/akshaydudhane/EarthDial-Dataset) |
| |
| ## Usage |
| |
| ```python |
| from datasets import load_dataset |
| |
| # Load the dataset |
| dataset = load_dataset("yobro4619/GeoChat_bench_split") |
| |
| # Access samples |
| sample = dataset['train'][0] |
| print(sample['question']) |
| print(sample['groundtruth']) |
| ``` |
| |
| ## License |
| |
| Please refer to the original [EarthDial-Dataset](https://huggingface.co/datasets/akshaydudhane/EarthDial-Dataset) for licensing information. |
| |
| ## Citation |
| |
| If you use this dataset, please cite the original EarthDial-Dataset paper. |
| |
