Comments (1)
We haven't optimized that aspect, so you might want to look into this, but it's possible that you could do better by moving all the operations to GPU.
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Related Issues (20)
- Evaluation of 3DPW HOT 2
- About the learning rate HOT 1
- Multi gpu training HOT 1
- Visualization of the reconstructed human mesh HOT 2
- Unable to download hmr2_data.tar.gz HOT 2
- A colab error about tracking HOT 2
- The meaning of 'NUM_TRAIN_SAMPLES', 'NUM_TEST_SAMPLES' and the question of the discriminator.
- Can not import expand_bbox_to_aspect_ratio from hmr2.datasets.utills HOT 1
- about the training data,do you use EFT fits or what? HOT 6
- how about using smpl 49 keypoints(like spin did) instead of your smpl 44 keypoints? will the result be worse? HOT 2
- Is it easy to train this work with 4 V100 24G or 8 3090 24G? (no A100) HOT 1
- Error of downloading training dataset HOT 1
- Is there any specific reason for choosing Detectron2 as human detection model? HOT 1
- Using 4 V100-16, and set batchsize=1, torch.cuda.OutOfMemoryError:
- Have you tried to use a smaller backbone? HOT 1
- use SMPLX model with hands and feet? HOT 2
- Pseudo labels generation
- evaluation datasets image HOT 3
- download problem of hmr2.0a_model.tar.gz HOT 4
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