Pytorch-yolov3: this repo is good ONLY for INFERENCE with PROVIDED WEIGHTS.

[ScottHoang]

like the title said, this implementation suffers serious issue when trained from scratch with mAP stalling at around 20%. If you are planning to train this on custom data, I suggest go looking at a different PyTorch implementation of yolo.

[tjiagoM]

Hi @voodoopotato do you have a suggestion of a good pytorch implementation? I've found different ones around so was curious to see what you think.

[ScottHoang]

@tjiagoM yes I did.
https://github.com/ultralytics/yolov3. I achieved much much better results using their model.

[Khalifa1997]

@voodoopotato @tjiagoM do you think I can achieve results here training on only 100 images?

[ScottHoang]

No.

[Khalifa1997]

@voodoopotato thanks for the quick reply, I am abit lost here though, what approachs do you think I should look into with dataset of that size? thanks!

[ScottHoang]

@Khalifa1997 maybe I was a bit in haste. One hundred images are very small sample population but can be artificially multiplied with proper data-augmentation. It depends on how many cls you have, how common they are in your samples, etc...
But as I said in my title, this repo is only suitable for inference.