Saved model gives Poor result (TF framework)

[hadizand]

I trained YOLOV4-Tiny model over a custom dataset which had three classes. I used main darknet approach:"https://github.com/AlexeyAB/darknet#yolo-v4-in-other-frameworks" in order to train/test the model, and it detects and predicts very well. In next step, I used this repository (saved_model.py) to convert the xx.weight file to .pb file. While there is no error in converion, but it gives very poor results. I manipulated the iou & score paramteres, but the model does not detect and predict well. For example, it shows many bounding boxes with score 1. Attached is an example of the results of .weight and .pb.

Any comment or suggestion to solve this issue?

Thanks

[Micky-123]

@hadizand : Were you able to figure out the issue with the above?

[hadizand]

@hadizand : Were you able to figure out the issue with the above?

I could not resolve the issue, and I switched to this github code (YOLOv5), it works perfectly. https://github.com/ultralytics/yolov5

[khg2478]

@hadizand Hello. Do you mean you could change the model into tflite format? If solved, please let me know. :)