Comments (3)
Hi @HongwenZhang, thanks for the great work! Do you also mind sharing your training process and data preparation for the AGORA benchmark?
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Hi, sorry for the slow update of this project.
To train the code, the most tedious part is the preparation of the training data.
I have just uploaded the compatible SMPL-X labels, and hope these files could help.
The example script to run the training code:
python -m apps.train --regressor pymaf_net --train_data h36m_coco_itw --pretrained_checkpoint xxxx --misc TRAIN.BATCH_SIZE 64 TRAIN.NUM_WORKERS 8 LOSS.SHAPE_W 0.6 MODEL.PyMAF.BACKBONE hr48
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Hi, @damonchang23, I also wand to train PyMAF-X from scatch, but encounter some issues during training. I was wondering if you train PyMAF-X successfully? Thanks for the help!
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Related Issues (20)
- Flame downsampling HOT 6
- How to save mesh without background?
- I ran into this problem when running a demo with my own video HOT 3
- bug when saveobj
- Training details
- How to read smplx_params output by smplx.SMPLX? HOT 4
- RuntimeError: CUDA out of memory when dealing folder with large amount of pics
- How to use multiple gpus to train PyMAF-X
- Some questions about real-time 3d pose estimation.
- USE_IWP_CAM:False, some error
- Extracting some parameters from the model
- Problem with output video
- model size mismatch
- About body_pose
- Evaluation code release
- Training procedure too slow
- Joint pose
- How to process AGORA dataset?
- Prepare data for training
- openpifpaf installation error HOT 2
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