### 📊 Dataset Statistics • Total Images: 1,227 (predominantly .jpg format) • Total Annotations: 1,441 (.txt files in YOLO format) • Total Bounding Boxes: 2,219 (across the matched images) • Missing Images: There are 214 annotation files (.txt) that do not have a corresponding image file. They should be filtered out before training models. ### 🏷️ Class Mapping & Distribution (Matched Pairs) The YOLO annotations map to the following severity classes: • Class 0 (First-Degree Burn): 872 bounding boxes (39.3%) • Class 1 (Second-Degree Burn): 992 bounding boxes (44.7%) • Class 2 (Third-Degree Burn): 355 bounding boxes (16.0%) ### 🛠️ Key Sections in the README.md • YOLO Format Reference: Quick explanation of the space-separated coordinates structure. • Usage Guidance: A Python snippet to automatically clean up/filter out the 214 unmatched .txt files. • 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.