train interface model

[wm901115nwpu]

how to train pretrained_h36m_detectron_coco.bin model? If I want to train myself, how to do it ?

[dariopavllo]

You have to download the detectron_pt_coco detections and run: python run.py -e 80 -k detectron_pt_coco -arc 3,3,3,3,3

In addition, for that model we removed the third detection coordinate (the keypoint probability) since it had a bad effect on predictions in the wild due to the different resolution/aspect ratio. To achieve the same effect, replace this line with kps = normalize_screen_coordinates(kps[..., :2], w=cam['res_w'], h=cam['res_h'])

[wm901115nwpu]

That is that the detectron_pt_coco_detections isn't be trained by myself.

[wm901115nwpu]

I have already got the result, but when I use the video contained speeding action ; such as do gymnastics; some results were bad, Can you give me some advice about it?

[hundanLi]

When I finish training the inference module pretrained_h36m_detectron_coco.bin using:

python run.py -e 40 -k detectron_pt_coco -arc 3,3,3

and then test on a custom .npz predicted by detectron2 following https://github.com/darkAlert/VideoPose3d_with_Detectron2 using:

python run.py -d custom -k myvideos -arc 3,3,3 -c checkpoint --evaluate epoch_40.bin --render --viz-subject detectron2 --viz-action custom --viz-camera 0 --viz-video ./data/pose2d-detectron2/input_video.mp4 --viz-output myvideos_output.mp4 --viz-size 6 --viz-no-ground-truth

it occures a size mismatch error while loading module:

Traceback (most recent call last):
  File "run.py", line 209, in <module>
    model_pos_train.load_state_dict(checkpoint['model_pos'])
  File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 830, in load_state_dict
    self.__class__.__name__, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for TemporalModelOptimized1f:
    size mismatch for expand_conv.weight: copying a param with shape torch.Size([1024, 51, 3]) from checkpoint, the shape in current model is torch.Size([1024, 34, 3]).

How can I address this problem, please?

[hundanLi]

When I finish training the inference module pretrained_h36m_detectron_coco.bin using:

python run.py -e 40 -k detectron_pt_coco -arc 3,3,3

and then test on a custom .npz predicted by detectron2 following https://github.com/darkAlert/VideoPose3d_with_Detectron2 using:

python run.py -d custom -k myvideos -arc 3,3,3 -c checkpoint --evaluate epoch_40.bin --render --viz-subject detectron2 --viz-action custom --viz-camera 0 --viz-video ./data/pose2d-detectron2/input_video.mp4 --viz-output myvideos_output.mp4 --viz-size 6 --viz-no-ground-truth

it occures a size mismatch error while loading module:

Traceback (most recent call last):
  File "run.py", line 209, in <module>
    model_pos_train.load_state_dict(checkpoint['model_pos'])
  File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 830, in load_state_dict
    self.__class__.__name__, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for TemporalModelOptimized1f:
  size mismatch for expand_conv.weight: copying a param with shape torch.Size([1024, 51, 3]) from checkpoint, the shape in current model is torch.Size([1024, 34, 3]).

How can I address this problem, please?

I retrain it replacing the line with

kps = normalize_screen_coordinates(kps[..., :2], w=cam['res_w'], h=cam['res_h'])

and it works well. Thank you for your work!