YOLOv5 Source: https://github.com/ultralytics/yolov5
Grad-CAM Source: https://github.com/jacobgil/pytorch-grad-cam

• Check 'yolov5' folder, read usage first
• Structure your files as yolov5's input
• Run train.py for training
• and detect.py to save detection results (if you're not interesting at interpreting results, you can skip from here.)

• We're interpreting classification results only, not including detection
• Run train.py for training yolo_classifier: submodel of yolov5 with detecting architecture removed
• Make sure you use the same structure as yolov5.
• Classification results will be SAME between original yolo and yolo_classifier

• In 'pytorch-grad-cam' folder
• Modify 'model' to the same model as you used before
• Modify 'ckpt' to your own trained weight
• Run script(check pytorch-grad-cam usage)