Visualize the low-level outputs of YOLOv8 to analyze and understand the areas where our model focuses. Specifically, illustrate which anchor points are activated to predict bounding boxes.
Green points indicate the areas where YOLOv8 focuses, with brighter green representing a higher confidence score.
Green bounding boxes represent those with high confidence scores; these boxes have not been processed with Non-Maximum Suppression (NMS).
Each arrow represents the predicted left, top, right, and bottom (LTRB) distances from the anchor points.
I am aware that my plotting method is not 👍. Feel free to modify the code to enhance the quality of the figure.
pip install ultralytics==8.1.8
git clone https://github.com/developer0hye/Explainable-YOLOv8.git
cd Explainable-YOLOv8python visualize.py --model {your model}.pt --source {your data} --class_id {class id}
Execute the command below to generate the image as shown in this README file
cd Explainable-YOLOv8
python visualize.py --model yolov8m.pt --source ./ --class_id 0
python visualize.py --model yolov8m.pt --source ./ --class_id 27
python visualize.py --model yolov8m.pt --source ./ --class_id 5