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uricamic avatar uricamic commented on July 21, 2024

Hi @guo253,

could you please provide some output images?

The resolution is usually not a problem, there is just a systematic error introduced by re-scaling the input image to a working image (normalized frame).

However, there could be other problem with the compatibility of the models and the detection method used. We have made some speed ups for features computation, which results in a different scheme of computations and therefore the model has to be learned in the same way. It will be described on the webpages soon.

All multi-view models are using the new optimized way of feature computation, and therefore they require featuresPool class as well.

flandmark_model.xml is old model, which does not use this optimization. It was learned on near-frontal images only, so it works meaningfully only for faces with yaw in range around (-30, 30).

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scdeng avatar scdeng commented on July 21, 2024

Hi @guo253 and @uricamic
I had the same precision problem, I ran the example with command "./static_input ./ ./flandmark_model.xml ./face.jpg face_result.jpg", the result seems not accurate as flandmark did. is there something wrong with the model in clandmark example?

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uricamic avatar uricamic commented on July 21, 2024

Hi @scdeng,

yep, the flandmark_model.xml which is in the package now is not compatible with that example. I will prepare new model identical to the uricamic/flandmark but compatible with the new scheme of features computation.

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futurely avatar futurely commented on July 21, 2024

The test results on the 300-W IBUG dataset using the provided jointly learned models for multi-view facial landmark detection are completely inaccurate. Two of the best ones are shown below. Could you add some examples to train the models?

image_006

image_078_1

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futurely avatar futurely commented on July 21, 2024

The individually learned multi-view models are even worse.

image_006

image_078_1

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uricamic avatar uricamic commented on July 21, 2024

Hi @futurely,

I think the problem is that you use incompatible models for your code. Please send me the images without detections so I can check it out.

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futurely avatar futurely commented on July 21, 2024

The test images are the IBUG database downloaded from here.

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uricamic avatar uricamic commented on July 21, 2024

I meant just these two images you posted here. Or at least their file names.

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uricamic avatar uricamic commented on July 21, 2024

Hi @futurely,

here are the results when the correct code is used:

out3

When in-plane rotation is returned by the face detector:

out2

For the first image my face detector missed the face.

I will soon update both webpages and the repository with examples covering the multi-view scenario (as well as some new stuff).

Sorry for the inconvenience caused by the compatibility issues between old and new models. I will try to clarify this on the webpages as well.

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karlhugle avatar karlhugle commented on July 21, 2024

Hi @uricamic the same issue, can't run as you showed above, it is more like the old landmark version. What is fd con:56.613 mean? is it a build-in function?

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uricamic avatar uricamic commented on July 21, 2024

Hi @karlhugle,

the fd conf: is a confidence of our face detector, nothing in connection to clandmark itself. As for the precision issues, there was some update of the code snippets and also there is another thread here: #21

The update of the webpages will happen next week, I will also include more self-contained examples.

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karlhugle avatar karlhugle commented on July 21, 2024

@uricamic Many thanks!

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