Datasets:
Tasks:
Object Detection
Modalities:
Text
Formats:
json
Languages:
English
Size:
< 1K
Tags:
object detection
image classification
agricultural detection
quality control
agricultural product grading
License:
Commit ·
a6d7858
verified ·
0
Parent(s):
initial commit
Browse files- .gitattributes +60 -0
- README.md +60 -0
.gitattributes
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# Audio files - uncompressed
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README.md
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---
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tags:
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- object detection
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- image classification
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- agricultural detection
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- quality control
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- agricultural product grading
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license: cc-by-nc-sa-4.0
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task_categories:
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- object-detection
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language:
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- en
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pretty_name: Green Pepper Appearance Quality Detection Dataset
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size_categories:
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- 1B<n<10B
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---
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# Green Pepper Appearance Quality Detection Dataset
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The current agricultural sector faces challenges in the appearance quality detection of agricultural products such as peppers. Traditional manual detection methods are inefficient and lack accuracy, often affected by subjective factors. Existing automated detection technologies largely rely on single image processing algorithms, making them unsuitable for varying environments and diverse quality detection needs. Therefore, the creation of this dataset aims to provide a rich sample repository to support the training of deep learning-based object detection models, enhancing automation and accuracy in detection. The dataset contains 5000 high-quality green pepper images, captured using high-resolution cameras under natural lighting conditions to ensure the authenticity and diversity of the images. Quality control of the data includes multiple rounds of annotation and consistency checks, with all annotations reviewed by experienced experts. The final data is stored in JPG format, organized by category and quality grade for easy subsequent model training and validation.
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## Technical Specifications
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| Field | Type | Description |
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| :--- | :--- | :--- |
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| file_name | string | File name |
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| quality | string | Resolution |
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| defect_type | string | Identifies the type of external defects in the green pepper, such as scratches, spots, etc. |
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| defect_location | string | Indicates the location of defects on the green pepper in the image, such as top, bottom, middle. |
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| defect_severity | string | Describes the severity of the defect on the green pepper, such as mild, moderate, severe. |
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| pepper_color | string | Records the color characteristic of the green pepper, usually shades of green. |
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| surface_texture | string | Describes the surface texture of the green pepper, such as smooth, rough. |
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| pepper_shape | string | Identifies the shape characteristics of the green pepper, such as elongated, round. |
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| size_dimension | string | Specifies the size dimensions of the green pepper, such as the length and width measurements. |
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| occlusion_level | string | Describes the extent to which the green pepper is occluded by other objects in the image. |
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## Compliance Statement
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<table>
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<tr>
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<td>Authorization Type</td>
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<td>CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)</td>
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</tr>
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<tr>
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<td>Commercial Use</td>
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<td>Requires exclusive subscription or authorization contract (monthly or per-invocation charging)</td>
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</tr>
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<tr>
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<td>Privacy and Anonymization</td>
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<td>No PII, no real company names, simulated scenarios follow industry standards</td>
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</tr>
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<tr>
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<td>Compliance System</td>
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<td>Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs</td>
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</tr>
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</table>
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## Source & Contact
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If you need more dataset details, please visit [Mobiusi](https://www.mobiusi.com/datasets/a7107bb3d69edab7a77bcbae9803cd85?utm_source=huggingface&utm_medium=referral). or contact us via contact@mobiusi.com
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