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- ---
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- license: apache-2.0
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- task_categories:
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- - object-detection
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- - image-classification
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- tags:
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- - medical
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ### 📊 Dataset Statistics
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+ • Total Images: 1,227 (predominantly .jpg format)
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+ Total Annotations: 1,441 (.txt files in YOLO format)
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+ Total Bounding Boxes: 2,219 (across the matched images)
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+ • Missing Images: There are 214 annotation files (.txt) that do not have a corresponding image file. They should be filtered out before training models.
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+ ### 🏷️ Class Mapping & Distribution (Matched Pairs)
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+ The YOLO annotations map to the following severity classes:
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+ • Class 0 (First-Degree Burn): 872 bounding boxes (39.3%)
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+ • Class 1 (Second-Degree Burn): 992 bounding boxes (44.7%)
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+ • Class 2 (Third-Degree Burn): 355 bounding boxes (16.0%)
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+ ### 🛠️ Key Sections in the README.md
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+ • YOLO Format Reference: Quick explanation of the space-separated coordinates structure.
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+ • Usage Guidance: A Python snippet to automatically clean up/filter out the 214 unmatched .txt files.
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+ • Citation Information: A standard BibTeX entry for the associated paper ("Detection of Different Degrees of Skin Burn using YOLOv3", Baid et al., 2020) for easy reference.