ziwei-zh / corrpm Goto Github PK

Thank for publish your code,

I try to run ./run_train.sh, but face this error. I cannot find this files in utils folder. Does your class CriterionPoseEdge different from class CriterionAll in CE2P repo?

Traceback (most recent call last):
File "train.py", line 24, in
from utils.criterion import CriterionPoseEdge
ImportError: cannot import name 'CriterionPoseEdge'

It's weird for my PC to train the code, it's very slow, can you figure it out.
In order to use PyTorch:1.4.0, I replace the "InPlaceABNSync" with normal "nn.BatchNorm2d".

CUDA:10.0
PyTorch:1.4.0
RTX 2080ti 11G
Ubuntu 16.04
i7-9700k
RAM：32 GB
iter:0/7616,loss:8.788,lr:1.000e-03,time:8.2 iter:500/7616,loss:3.455,lr:9.997e-04,time:165.6 iter:1000/7616,loss:2.483,lr:9.993e-04,time:166.3 iter:1500/7616,loss:3.580,lr:9.990e-04,time:167.0 iter:2000/7616,loss:2.938,lr:9.987e-04,time:167.5 iter:2500/7616,loss:2.709,lr:9.984e-04,time:166.9 iter:3000/7616,loss:3.379,lr:9.980e-04,time:167.1 iter:3500/7616,loss:2.261,lr:9.977e-04,time:164.4 iter:4000/7616,loss:2.764,lr:9.974e-04,time:164.3 iter:4500/7616,loss:3.147,lr:9.970e-04,time:164.3 iter:5000/7616,loss:3.124,lr:9.967e-04,time:164.3 iter:5500/7616,loss:2.995,lr:9.964e-04,time:164.3 iter:6000/7616,loss:1.715,lr:9.961e-04,time:164.4 iter:6500/7616,loss:2.305,lr:9.957e-04,time:164.0 iter:7000/7616,loss:1.912,lr:9.954e-04,time:165.5 iter:7500/7616,loss:1.704,lr:9.951e-04,time:165.5
Thank you.

Hi,
could you suggest a solution to run the evaluation with pytorch 1? I would like to try it on Colab but installing torch 0.4.1 generates problem with Cuda so it is a bit problematic.

The main problem is related to the libs modules but I can't find a complete solution to it :(

Hi, thanks for your code, here are some problem. I can't find LIP_SP_VAL_annotations.json in your project, but run_eval.sh have the code like:
CS_PATH='/data/zzw/segment/data/lip/images_labels' POSE_ANNO='/data/zzw/segment/data/lip/TrainVal_pose_annotations/LIP_SP_VAL_annotations.json'

I think you have done a great work. Could you tell me, where could download Mask R-CNN that you used in your paper?

Hi you have done a great job
Could you tell me which code you used to generate 16 keypoints like those in Lip.

Hi, can you tell me how to save pose and edge predictions as images? Thank you very much.

dear author ,the dataset link doesnot work ,can you give a new link ? thank you ,my email :[email protected]

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
2. I think the upsampling step is not needed since it may cause misalignment issues.

Thank you very much! Finally able to get it work;)

Originally posted by @Sonseca97 in #8 (comment)

ModuleNotFoundError: No module named 'libs._ext.__ext'

Dear author:
Thanks for shareing the implementation!
I doubt that How could i test on my own images, Since I dont have the pose and edge info in terms of json file? Thank you.

Interested in trying out.

Hi, may I ask if the model is able to generate pose coordinates as output on a test image? I found the model output is a list where you only used seg2. However, when I use the output of pose1, I get the shape of 12x16x96x96 where 12 is the batch size and 16 is the number of keypoints labels. I am not sure how to proceed from this stage. Hope you can help me clarify! Thank you!
return [[seg1, seg2], [edge1], [pose1]]

Dear author ,thanks your code.About 16 pose point ,I have a question,how to get this result.I get this parameter use blew code：
points=outputs[2][0]
points = interp(points).data.cpu().numpy()
points = points.transpose(0, 2, 3, 1)
points_preds[idx:idx + num_images, :, :] = np.asarray(np.argmax(points, axis=3), dtype=np.uint8)
point_pred=np.asarray(np.argmax(points, axis=3), dtype=np.uint8)
but how to map this shape (116 96*96) map orign image,hope yor answer.thank you @ziwei-zh

I also encountered the issue as well as liutinglt/CE2P#34.
However, this issue does not provide a solution.
I do not change the part of weight loading and it does not output any error messages.
How do I fix it?
Note that I referred to the CE2P repository (https://github.com/liutinglt/CE2P) so that exchange ABN for PyTorch ver 0.x to ABN for PyTorch ver 1.x.

The output of the network goes from about -0.02 to 0.03. Is it collect?
The network generates a poor result though I exchanged ABN to BN.
Thanks.

--My environment--
GPU: Tesla V100
PyTorch: 1.6
CUDA: 10.2.89
cuDNN: 8.0.2
ABN: https://github.com/mapillary/inplace_abn
Pre-trained model: LIP_best.pth

ModuleNotFoundError: No module named 'libs._ext.__ext'