Comments (5)
Hi, you can select the max value along every channel, like pose1.max(1)
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Hi, you can select the max value along every channel, like pose1.max(1)
Hi, thank you for your reply! So i converted 96x96 back to 384x384 the same way you did for seg2, and selected the pixels with the max values for each of the 16 channels. However, i noticed that 1) for each channel, there are several pixels with the same max values, althouth they are pixels nearby each other 2)when I tried to map the 16 keypoints on the 384x384 test image, the mapping seemed wrong. Is there any steps I am missing? Thank you!
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- First you may have to do NMS or other post-processing. You may refer to simple baseline repo: https://github.com/microsoft/human-pose-estimation.pytorch/blob/18f1d0fa5b5db7fe08de640610f3fdbdbed8fb2f/lib/core/inference.py#L49
- I think the upsampling step is not needed since it may cause misalignment issues.
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- First you may have to do NMS or other post-processing. You may refer to simple baseline repo: https://github.com/microsoft/human-pose-estimation.pytorch/blob/18f1d0fa5b5db7fe08de640610f3fdbdbed8fb2f/lib/core/inference.py#L49
- I think the upsampling step is not needed since it may cause misalignment issues.
Thank you very much! Finally able to get it work;)
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Hello,Can you share test code to output points?I also want to output 16 points @Sonseca97 ,Thanks
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Related Issues (20)
- NO LIP_SP_VAL_annotations.json in the project HOT 7
- Hi Author: about Mask R-CNN HOT 1
- What is the password for the Baidu Drive please? HOT 1
- why can't I find .__ext module?
- can i use widows system to run the code?
- why can't i find the .__ext module in libs?
- Why there is mosaic phenomenon in the results? HOT 2
- Poor result with pre-trained model LIP_best.pth HOT 1
- How to save pose and edge predictions as images? HOT 1
- dataset HOT 1
- Missing files in utils folder? HOT 1
- > 1. First you may have to do NMS or other post-processing. You may refer to simple baseline repo: https://github.com/microsoft/human-pose-estimation.pytorch/blob/18f1d0fa5b5db7fe08de640610f3fdbdbed8fb2f/lib/core/inference.py#L49
- pose point
- About the trainning speed. HOT 3
- How to test my own image if I dont have Human pose and edge info? HOT 2
- which codes are used to generate 16 keypoints in CIHP? HOT 1
- class Edge_Module, In forward function, edge not be used?? HOT 1
- Can you post license info? HOT 2
- Running model with torch 1.x HOT 6
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