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Inference code #2

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cf206cd opened this issue May 19, 2021 · 8 comments
Closed

Inference code #2

cf206cd opened this issue May 19, 2021 · 8 comments

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@cf206cd
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cf206cd commented May 19, 2021

It would be nicer if you can add inference code! And why there is no MobileNet in backbone? Does it not work well for this task?

@Turoad
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Turoad commented May 19, 2021

Thank for your interest.

What is you need in the inference code, e.g., do visualization?
Currently, we support visualization in validate phase by adding --view.

As for MoblieNet, We haven't tested it. We will consider testing it and updating the configs. It may have faster inference speed but relatively low accuracy.

@cf206cd
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cf206cd commented May 19, 2021

Well, not only visualization, some (including me) may need to deploy it on some embedding devices, so maybe we can implement a class to do inference without complicated config and data loader?

@Turoad
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Turoad commented May 19, 2021

OK, I will consider add the inference code. The config cannot be removed. We need the config to define network, preprocess or others.

@cf206cd
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cf206cd commented May 20, 2021

And maybe another advice... It would be better if you can change the input of the model to be only images just like mmdetection. It seems to be a batch with both images and labels now and it`s not convenient for inference. Thank you for your good job!

@Turoad
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Turoad commented May 20, 2021

The input is a dict. If you don't have labels, just get the img, like this: https://github.com/Turoad/lanedet/blob/main/lanedet/models/net/detector.py#L19.
If the dataset don't have any label, we can handle this case. I don't think it's inconvenient.

@Turoad
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Turoad commented May 20, 2021

By the way, we don't have labels during validate in a batch. Do you run the code and get labels?

@Turoad
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Turoad commented May 22, 2021

@cf206cd I have added the MobileNetV2(https://github.com/Turoad/lanedet/blob/main/configs/laneatt/resnet18_culane.py) and the tools/detect.py.

@cf206cd
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cf206cd commented May 24, 2021

Wow! Amazing! Thank you so much!

@Turoad Turoad closed this as completed May 29, 2021
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