Comments (1)
Sorry I don't have NVIDIA T4.
As I remember, ResNet152-384x288 model is quite heavy that it runs slow (maybe 5fps on GTX1080Ti).
If you use ResNet50-256x192 model, then I think it would be quite fast (maybe faster than 50fps on GTX1080Ti).
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Related Issues (20)
- About how to apply this work on my own data? HOT 17
- calculate miss_prob , jitter_prob and inv_prob on other dataset HOT 1
- demo for a single image HOT 4
- About Fig.5 in your paper HOT 2
- Can we directly implement Posefix on Inference phase or should we have to do it from training itself? HOT 3
- Combining all the three datasets HOT 3
- I can't use my GPU? HOT 1
- Find data HOT 6
- converting model to ONNX for C++ inference with TensorRT HOT 3
- Is there any plan to provide pre-trained weights available? HOT 2
- inefficient heavy-CPU training HOT 7
- input image normalization HOT 4
- the reason behind the usage of render_onehot_heatmap for training target instead of render_gaussian_heatmap HOT 3
- the usage of the softmaxed heatmaps as the keypoint confidence scores
- Format of result.json HOT 1
- Missing modules in requirements
- FileNotFoundError: [Errno 2] No such file or directory: 'tmp_result_0.pkl' and IndexError: list index out of range HOT 3
- tensorflow 2
- I appreciate your work!
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