Full Custom YOLO Detection Model

Model Description

This model is a custom-trained YOLO object detection model for multi-class detection tasks on a specialized dataset.

It is trained for fine-grained object detection using bounding box annotations across multiple visual anatomy classes.


Intended Use

  • Object detection on custom anatomical datasets
  • Bounding box classification for fine-grained region detection

Limitations

  • Trained on a custom manually annotated dataset across 7 classes
  • Performance may degrade on unseen domains or different distributions
  • Evaluation is based on a controlled dataset of ~50 images

Evaluation Results

Overall Metrics

  • Precision: 0.987
  • Recall: 0.999
  • mAP@50: 0.995
  • mAP@50-95: 0.794

Per-Class Results

Class Images Instances Precision Recall mAP50 mAP50-95
all 50 253 0.987 0.999 0.995 0.794
face 41 49 0.989 1.000 0.995 0.862
nipple 33 64 0.985 0.995 0.995 0.785
mouth 41 50 0.971 1.000 0.995 0.793
eyes 41 49 0.990 1.000 0.995 0.832
navel 28 30 0.989 1.000 0.995 0.697
anus 11 11 0.995 1.000 0.995 0.792

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