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yhenon / pytorch-retinanet

Pytorch implementation of RetinaNet object detection.
Apache License 2.0
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Evaluation is too slow #176

Open abhiagwl4262 opened 4 years ago

abhiagwl4262 commented 4 years ago

Hey @mimoralea As the evaluation is being sequentially for each image, the process is too slow. Is there any other way for evaluation?

wvalcke commented 3 years ago

At this moment the code for inference is only compatible with batch sizes = 1. The limitation comes from the final NMS processing which would be wrong if the batch size would be > 1. Although it is possible to refactor this code to make it compatible with batch sizes > 1, it would be a good exercise to implement it. Feel free it would say.

bishwarup307 commented 3 years ago

I created an extension of this repo with some added features. One of them is to use batch evaluation using pytorchs batched_nms. You may check it out https://github.com/bishwarup307/pytorch-retinanet

wvalcke commented 3 years ago

Hi @bishwarup307 , your fork looks really promising. As soon i've some time i'll have a look at the code. thanks for sharing. Just a quick question, is the onnx export readable by opencv dnn ?.

bishwarup307 commented 3 years ago

Not really sure about that, it works with onnxruntime though. will check.

wvalcke commented 3 years ago

@bishwarup307 , thanks for your reply, btw, if you're interested in the retinanet version which supports TorchScript, have a look at https://github.com/wvalcke/pytorch-retinanet It's based on the original retinanet master, so it's easy to see the changes.