Comments (6)
Hi, I had a quick look at the code you provided and I think that the problem might be in the order of colors. Cv2 imread
returns a BGR image array while the face verification model works with RGB. Try to change the order of channels in your test_torch
tensors using the rgb2bgr
function from facetorch.utils
module (it also works for bgr2rgb) and let me know if that provides the correct results.
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Thank you for your response.
I have tried to change the order of channels. But it didn't help.
Here is the new results:
tensor(0.1691) result of analyzer
tensor(0.6214) result of predictor
Result of analyzer is different, because i have picked different photos.
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Alright, thanks for trying to change the order of colors. I have some additional questions that could help me say what the issue is:
Which result makes more sense to you? Are the faces from the two images one person or different people?
Do the images contain single cropped-out faces? What's the resolution of these images?
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FaceAnalyzer resizes the input images to 1080 x 1080 resolution using the ImageReader. The results might be different if your input image is much smaller, which might be true for cropped-out faces.
Change the size of the ImageReader Resize transform in /conf/analyzer/reader/default.yaml
to the length of the longer side of the specific input image.
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path_config="gpu.config.yml"
Hello, how did you write this config file? Could you please tell me about it? Thank you very much!
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path_config="gpu.config.yml"
Hello, how did you write this config file? Could you please tell me about it? Thank you very much!
You can use the merged config file or its GPU version located in the same directory.
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Related Issues (20)
- Questions about the AU detection HOT 1
- Unable to add packages HOT 2
- Is it possible to delete predictors? HOT 4
- Dev Containers in VScode HOT 1
- fix_img_size HOT 1
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- Running example.py without docker HOT 6
- Output of AU detector HOT 1
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- Stack on AU inference when `return_img_data=True` HOT 5
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- Feature Request: Add a valnece-arousal model HOT 3
- Feature Request: Add the MediaPipe's Face Mesh model
- Feed image as tensor HOT 1
- Stuck at "Reading Image" HOT 1
- Running on specified GPU HOT 1
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