jackyjsy/cvpr21chal-slr

This repo contains the official code of our work SAM-SLR which won the CVPR 2021 Challenge on Large Scale Signer Independent Isolated Sign Language Recognition.

cvpr21chal-slr's Issues

RuntimeError: DataLoader worker (pid(s) 49) exited unexpectedly when trying to test config files in Conv3D

Greetings. Congratulations on your work. I was trying to run "python Sign_Isolated_Conv3D_clip_test.py" inside /Conv3D/ folder. I ran into the following error, I'm pasting the error traceback.

---Traceback Starts----
Using 2 GPUs
######################Testing Started#######################
ERROR: Unexpected bus error encountered in worker. This might be caused by insufficient shared memory (shm).
Traceback (most recent call last):
File "/home/smilelab_slr/SLR_pytorch/env/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 872, in _try_get_data
data = self._data_queue.get(timeout=timeout)
File "/home/smilelab_slr/SLR_pytorch/env/lib/python3.8/queue.py", line 179, in get
self.not_empty.wait(remaining)
File "/home/smilelab_slr/SLR_pytorch/env/lib/python3.8/threading.py", line 306, in wait
gotit = waiter.acquire(True, timeout)
File "/home/smilelab_slr/SLR_pytorch/env/lib/python3.8/site-packages/torch/utils/data/_utils/signal_handling.py", line 66, in handler
_error_if_any_worker_fails()
RuntimeError: DataLoader worker (pid 49) is killed by signal: Bus error. It is possible that dataloader's workers are out of shared memory. Please try to raise your shared memory limit.

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
File "Sign_Isolated_Conv3D_clip_test.py", line 137, in
val_loss = val_epoch(model, criterion, val_loader, device, 0, logger, writer, phase=phase, exp_name=exp_name)
File "/home/smilelab_slr/Isolated_SLR/CVPR21Chal-SLR/Conv3D/validation_clip.py", line 13, in val_epoch
for batch_idx, data in enumerate(dataloader):
File "/home/smilelab_slr/SLR_pytorch/env/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 435, in next
data = self._next_data()
File "/home/smilelab_slr/SLR_pytorch/env/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1068, in _next_data
idx, data = self._get_data()
File "/home/smilelab_slr/SLR_pytorch/env/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1024, in _get_data
success, data = self._try_get_data()
File "/home/smilelab_slr/SLR_pytorch/env/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 885, in _try_get_data
raise RuntimeError('DataLoader worker (pid(s) {}) exited unexpectedly'.format(pids_str)) from e
RuntimeError: DataLoader worker (pid(s) 49) exited unexpectedly

----Traceback Ends----

Any insights will be appreciated.
Thanks.

How to get correct 'train_val_labels.pkl' ?

Thanks for your project.
I'm very interested in the network you designed. But when goes to 'test_joint.yaml', I can not get the 'train_val_labels.pkl'. The 'train_val_labels.pkl' I merged from 'train_label.pkl' and 'val_gt.pkl' is wrong.
The code is following:

import pickle
with open('/media/lyh/data/AUTSL/Autsl/skeleton_data/train_label.pkl', 'rb') as fr_1:
data_1 = pickle.load(fr_1)
with open('/media/lyh/data/AUTSL/Autsl/skeleton_data/val_gt.pkl', 'rb') as fr_2:
data_2 = pickle.load(fr_2)
data = [data_1, data_2]
with open('/media/lyh/data/AUTSL/Autsl/skeleton_data/train_val_labels.pkl', 'wb') as fr_3:
pickle.dump(data, fr_3)
​###
Would you mind help me to get correct 'train_val_labels.pkl'?
I am looking forward to your reply. Thanks in advance.

Hi ! I'm impressed by your repo. When I try to extract skeleton features. where can I find the file "wholebody_hrnet_w48_384x384.pth" ? Thank you

AUTSL dataset corrupted or in unknown format

Hello thank you so much for your code.

When I downloaded AUSTL datasets from the official website and unpacked it, it showed unknown format or was corrupted. How should I download and unpack correctly? By the way, where should I download CSL and WLASL datasets?

I would appreciate it if you could reply.Thank you very much.

How will I use it on my camera for testing

I want to apply this great model to the camera for testing, what should I do

Reproduce Results on WLASL dataset

Thank you very much for providing the code. I would like to reproduce the results on WLASL dataset. Could you please provide me with details about the pre-processing of the data on WLASL dataset?

Train for bone

Hello!

I run this command for bone's training
python main.py --config config/sign/train/train_bone.yaml

and it gives me this error

Traceback (most recent call last): File "main.py", line 588, in <module> processor = Processor(arg) File "main.py", line 215, in __init__ self.load_data() File "main.py", line 224, in load_data dataset=Feeder(**self.arg.train_feeder_args), File "/home/smilelab_slr/cvpr2021_allcode/GCN/feeders/feeder.py", line 40, in __init__ self.load_data() File "/home/smilelab_slr/cvpr2021_allcode/GCN/feeders/feeder.py", line 59, in load_data self.data = np.load(self.data_path, mmap_mode='r') File "/home/smilelab_slr/SLR_pytorch/env/lib/python3.8/site-packages/numpy/lib/npyio.py", line 417, in load fid = stack.enter_context(open(os_fspath(file), "rb")) FileNotFoundError: [Errno 2] No such file or directory: './data/sign/27_2/train_data_bone.npy'

Any help?
Many thanks
<img width="1077" alt="Screen Shot 1443-08-14 at 3 52 19 PM" src="https://user-images.githubusercontent.com/85832533/158812428-5ccdefa0-2ea3-40e4-9bde-56dca

4f507db.png">

Conv3D for WLASL

Hello thank you so much for your code.

I am trying to train Conv3D for WLASL dataset but the accuracy is too low.
Do you have any idea why this is happening ?

Thank you in advance.

How can i send a videp to test the perfomance?

very excited about ur code, im trying to test this model in a video to test its performance,but i dont konw how to or where to send the vide in, i have read the issue about the webcamera use, it has to record a video,and process, Does it means i have to process my test video by the same method,such as generate .npy file and generate rawframes and extract skeleton features and so on? Thanks for answering.Appreciate!

about joint detector

Why not use openpose, alphapose joint detector？The current joint detector hrnet is slower than alphapose and openpose?

RuntimeError: The size of tensor a (270) must match the size of tensor b (272) at non-singleton dimension 2

Hello
I am trying to fine-tune your model
Currently, I am performing data preprocessing steps, the first step of "Generate whole-body skeleton keypoints and save as npy" throws error when running the demo.py file on my data

Please suggest a way to solve it

Accuracy of V2 paper

I'm sorry to ask question below.
The result of v1 cited in V2 paper is 97.51%. The result of V2 is 98.00%, which reaches 98.53% after adding extra data. However, the results mentioned in the v1 paper have already reached 98.53%.
Then there are two possibilities. Either the improvements mentioned in V2 have no effect at all, or the data have already used the technologies mentioned in V2 when the V1 paper comes out.
/(ㄒoㄒ)/~~
Could you please help me to find out the all_modilities_cc 98.53% in V2 paper?

Problem in directories provided in https://github.com/jackyjsy/CVPR21Chal-SLR/tree/main/SL-GCN

In the instructions for Finetune and Test there is probably a mistake in the paths used for yaml files.
Both test_joint.yaml and train_joint.yaml use the same directory :
config/sign/finetune which is not true.

Could you please let me know which are the correct directories?

Trouble running the Docker image

I loaded the Docker image with

cat cvpr2021cha_code.tar | sudo docker load

When I checked docker ps, I didn't see anything running and Docker logs showed

sudo docker logs 422402c07084b60ace48a6881017f9c2370b67fcd2a877a575fed557e2468db4
Welcome to SMILELAB SLR Code, please enter
source ./setup_env.sh
/bin/sh: 1: nvidia-smi: not found

I'm not sure which nvidia-smi to install, but these are what my system suggested when I tried running nvidia-smi:
sudo apt install nvidia-340 # version 340.108-0ubuntu5.20.04.2, or
sudo apt install nvidia-utils-390 # version 390.157-0ubuntu0.20.04.1
sudo apt install nvidia-utils-450-server # version 450.248.02-0ubuntu0.20.04.1
sudo apt install nvidia-utils-470 # version 470.199.02-0ubuntu0.20.04.1
sudo apt install nvidia-utils-470-server # version 470.199.02-0ubuntu0.20.04.1
sudo apt install nvidia-utils-525 # version 525.125.06-0ubuntu0.20.04.3
sudo apt install nvidia-utils-525-server # version 525.125.06-0ubuntu0.20.04.2
sudo apt install nvidia-utils-535 # version 535.86.05-0ubuntu0.20.04.2
sudo apt install nvidia-utils-535-server # version 535.54.03-0ubuntu0.20.04.1
sudo apt install nvidia-utils-435 # version 435.21-0ubuntu7
sudo apt install nvidia-utils-440 # version 440.82+really.440.64-0ubuntu6
sudo apt install nvidia-utils-418-server # version 418.226.00-0ubuntu0.20.04.2

I installed nvidia-340 from the list above and got

NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running.

Questions:

1. Could someone point me in the right direction for this nvidia-smi issue?
2. Once I get the container running, how do I send videos to the model? Is there a web server in the container that's serving the model? Do I make a HTTP POST request?
3. How do I batch inputs to the model for production?

ERROR "Undefined function 'ordfilt2' for input arguments of type 'double'." when trying to run Depth2HHA.m

Greetings. Congratulations on your work. I was trying to run Depth2HHA.m.
I ran into the following error, I'm pasting the error traceback.

---Traceback Starts----
video = 1 frame = 1 video_name = dataset/test/signer14_sample100_depth.mp4
Unrecognized function or variable 'ordfilt2'.

Error in computeNormalsSquareSupport>filterItChopOff (line 107)
minSP = ordfilt2(sp, 1, B, 'symmetric');

Error in computeNormalsSquareSupport (line 52)
AtA = filterItChopOff(cat(3, AtARaw, AtbRaw), R, superpixels);

Error in processDepthImage (line 19)
[N1 b1] = computeNormalsSquareSupport(z./100, missingMask, normalParam.patchSize(1),...

Error in saveHHA (line 14)
[pc, N, yDir, h, pcRot, NRot] = processDepthImage(D*100, missingMask, C);

Error in CVPR21Chal_convert_HHA (line 30)
hha = saveHHA(['frame', mat2str(frame_loop)], matrix, save_folder, frame_gray, frame_gray);
----Traceback Ends----

Any insights will be appreciated.
Thanks.

Number Parameters

Can i ask how many parameters in this whole model?

Puzzle about HHA representation generation.

Hi, I'm wondering if it's the only way to generate HHA representation using MatLab or some alternative off-the-shelf methods. Appreciation for the answer!

IndexError in forward func of Conv3D/Sign_Isolated_Conv3D_clip.py

After I trained the RGB Conv3D on for one training epoch without modifying anything from the source code, after the first train epoch is finished and I get to the val_epoch, the code behaves like this:

$ python Conv3D/Sign_Isolated_Conv3D_clip.py
...
######################Training Started######################
lr:  0.001
epoch   1 | iteration    80 | Loss 5.711482 | Acc 0.00%
epoch   1 | iteration   160 | Loss 5.423379 | Acc 0.00%
epoch   1 | iteration   240 | Loss 5.502132 | Acc 14.29%
epoch   1 | iteration   320 | Loss 5.452106 | Acc 0.00%
epoch   1 | iteration   400 | Loss 5.348779 | Acc 0.00%
epoch   1 | iteration   480 | Loss 5.369306 | Acc 0.00%
epoch   1 | iteration   560 | Loss 5.412856 | Acc 0.00%
epoch   1 | iteration   640 | Loss 5.431209 | Acc 0.00%
epoch   1 | iteration   720 | Loss 5.376038 | Acc 0.00%
epoch   1 | iteration   800 | Loss 5.504383 | Acc 0.00%
epoch   1 | iteration   880 | Loss 5.414754 | Acc 0.00%
epoch   1 | iteration   960 | Loss 5.481614 | Acc 0.00%
epoch   1 | iteration  1040 | Loss 5.402166 | Acc 0.00%
epoch   1 | iteration  1120 | Loss 5.561030 | Acc 0.00%
epoch   1 | iteration  1200 | Loss 5.304134 | Acc 14.29%
epoch   1 | iteration  1280 | Loss 5.452147 | Acc 0.00%
epoch   1 | iteration  1360 | Loss 5.429211 | Acc 0.00%
epoch   1 | iteration  1440 | Loss 5.503419 | Acc 0.00%
epoch   1 | iteration  1520 | Loss 5.407657 | Acc 0.00%
epoch   1 | iteration  1600 | Loss 5.423106 | Acc 0.00%
epoch   1 | iteration  1680 | Loss 5.427852 | Acc 0.00%
epoch   1 | iteration  1760 | Loss 5.387938 | Acc 0.00%
epoch   1 | iteration  1840 | Loss 5.491746 | Acc 0.00%
epoch   1 | iteration  1920 | Loss 5.375609 | Acc 0.00%
epoch   1 | iteration  2000 | Loss 5.529760 | Acc 0.00%
epoch   1 | iteration  2080 | Loss 5.462255 | Acc 0.00%
epoch   1 | iteration  2160 | Loss 5.383886 | Acc 0.00%
epoch   1 | iteration  2240 | Loss 5.354466 | Acc 0.00%
epoch   1 | iteration  2320 | Loss 5.439829 | Acc 0.00%
epoch   1 | iteration  2400 | Loss 5.484483 | Acc 0.00%
epoch   1 | iteration  2480 | Loss 5.388660 | Acc 0.00%
epoch   1 | iteration  2560 | Loss 5.336263 | Acc 0.00%
epoch   1 | iteration  2640 | Loss 5.511293 | Acc 0.00%
epoch   1 | iteration  2720 | Loss 5.430277 | Acc 0.00%
epoch   1 | iteration  2800 | Loss 5.447950 | Acc 0.00%
epoch   1 | iteration  2880 | Loss 5.434804 | Acc 0.00%
epoch   1 | iteration  2960 | Loss 5.414961 | Acc 0.00%
epoch   1 | iteration  3040 | Loss 5.452834 | Acc 0.00%
epoch   1 | iteration  3120 | Loss 5.405386 | Acc 0.00%
epoch   1 | iteration  3200 | Loss 5.377852 | Acc 0.00%
epoch   1 | iteration  3280 | Loss 5.378382 | Acc 0.00%
epoch   1 | iteration  3360 | Loss 5.481858 | Acc 0.00%
epoch   1 | iteration  3440 | Loss 5.544360 | Acc 0.00%
epoch   1 | iteration  3520 | Loss 5.439571 | Acc 0.00%
epoch   1 | iteration  3600 | Loss 5.497654 | Acc 0.00%
epoch   1 | iteration  3680 | Loss 5.374403 | Acc 0.00%
epoch   1 | iteration  3760 | Loss 5.400540 | Acc 0.00%
epoch   1 | iteration  3840 | Loss 5.482468 | Acc 0.00%
epoch   1 | iteration  3920 | Loss 5.428809 | Acc 0.00%
epoch   1 | iteration  4000 | Loss 5.400549 | Acc 0.00%
Average Training Loss of Epoch 1: 5.445218 | Acc: 0.39%
/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:490: UserWarning: This DataLoader will create 6 worker processes in total. Our suggested max number of worker in current system is 4, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.
  cpuset_checked))
Traceback (most recent call last):
  File "/content/codebase/CVPR21Chal-SLR/Conv3D/Sign_Isolated_Conv3D_clip.py", line 165, in <module>
    logger, writer)
  File "/content/codebase/CVPR21Chal-SLR/Conv3D/validation_clip.py", line 27, in val_epoch
    loss = criterion(outputs, labels.squeeze())
  File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/content/codebase/CVPR21Chal-SLR/Conv3D/Sign_Isolated_Conv3D_clip.py", line 27, in forward
    nll_loss = -logprobs.gather(dim=-1, index=target.unsqueeze(1))
IndexError: Dimension out of range (expected to be in range of [-1, 0], but got 1)

• Do you have any suggestions on what could be wrong here and why does the forward function present such a strange behaviour?
• Even more important, what could be the solution to this problem?

the SL-GCN motion-related data prediction acc very low ?

I download your code and barely not change anything. But the SL-GCN can't recognize the joint-motion and bone-motion very well. below are my result use the train_joint_motion.yaml and train_bone_motion.yaml:

below yaml file I just change the data_path and label_path, and not change other things! If possible, do you know why this result is?

Experiment_name: sign_joint_motion_final_NEU_data

# feeder
feeder: feeders.feeder.Feeder
train_feeder_args:
  data_path: ../../../Datas/TAUSL/AUTSL/skeleton/val_data_joint_motion.npy
  label_path: ../../../Datas/TAUSL/AUTSL/skeleton/val_gt.pkl
  debug: False
  random_choose: True
  random_shift: True
  window_size: 100
  random_mirror: True
  random_mirror_p: 0.5
  normalization: True
  is_vector: True

test_feeder_args:
  data_path: ./data/sign/27_2/train_data_joint_motion.npy
  label_path: ../../../Datas/TAUSL/AUTSL/skeleton/train_label.pkl
  random_mirror: False
  normalization: True
  is_vector: True

# model
model: model.decouple_gcn_attn.Model
model_args:
  num_class: 226
  num_point: 27
  num_person: 1
  graph: graph.sign_27.Graph
  groups: 16
  block_size: 41
  graph_args:
    labeling_mode: 'spatial'

#optim
weight_decay: 0.0001
base_lr: 0.1
step: [150, 200]

# training
device: [0,1]
keep_rate: 0.9
only_train_epoch: 1
batch_size: 64
test_batch_size: 64
num_epoch: 250
nesterov: True
warm_up_epoch: 20

Help from an admirer

Hello, I am from China. I am a graduate student. I am very interested in your work. Can you share the data set of your article? If I post an article, I will quote your article. Thank you!

No such file or directory: 'final_models/val_rgb_final.pth'

First of all, thanks for the project.

I trained 3DCNN model for RGB frames, using Sign_Isolated_Conv3D_clip.py file.
Now, I will run the Sign_Isolated_Conv3D_clip_finetune.py file.
In 88th row of the file, a pretrained model is loading that named val_rgb.pth.
However, this model does not in final_models directory.
How can i find this model?
Or is this model, output of first stage training?
I've tried use checkpoint/rgb_final/sign_resnet2d+1_epoch100.pth file but got error.

Inference time calculation

Hello everyone!

I reproduced all the results and it worked very well for me, but on the side of calculating inference time I tried before with a simple code but I failed.

Any help/advice?

gen_flow.py

Hi there :)
I am trying to replicate your results and am currently on the data prepare steps.
In the Generate flow data from rgb and depth videos section you mention that I must run the docker image.
Is there a way for me to do it without that image? (I am running in an environment which is really strict about loading foreign images).
Thanks in advance,
Amit

Problem in sign_gendata.py

CVPR21Chal-SLR/SL-GCN/data_gen/sign_gendata.py

Line 15 in 892de18

'27_2': np.concatenate(([0,5,6,7,8,9,10],

The '27' and '27_2' info of selected_joints is the same.

Could you please let me know what the idea is?

Loss does not decrease, and the model is not trained(Loss不下降，模型没有得到训练)

Hi, honorable competition winner. I deployed your code locally, but the results of many rounds of training seem to be that the model has not been trained, and the results are still random. The accuracy rate can only reach around 1/226.

For your code, the only modification I made was that batch-size is set to 2 for resource constrain, and the 512512 data was directly resized to 256256 during data preprocessing.

No other changes were made.

If it is possible, do you know the reason for my problem?

（作者您好，我在本地部署了代码，但是多轮训练得到的结果好像模型没有得到训练，结果仍然是随机的。准确率只能达到1/226附近。
对于您的代码，我做的修改仅为资源受限batchsize设为2，数据预处理的时候将512512的数据直接resize成256256.除此之外未作改动。
如果有可能的话请问您知道我遇到问题的原因吗？）

FileNotFoundError when trying to test config files in Conv3D

Greetings. Congratulations on your work. I was trying to reproduce your results in Google Colab using processed datasets and pretrained models. I stored 'test_frames' folder inside /Conv3D/data/ and tried to run "python Sign_Isolated_Conv3D_clip_test.py" inside /Conv3D/ folder. I ran into the following error, I'm pasting the error traceback.

---Traceback Starts----

######################Testing Started#######################
Traceback (most recent call last):
File "Sign_Isolated_Conv3D_clip_test.py", line 138, in
val_loss = val_epoch(model, criterion, val_loader, device, 0, logger, writer, phase=phase, exp_name=exp_name)
File "/content/CVPR21Chal-SLR/Conv3D/validation_clip.py", line 13, in val_epoch
for batch_idx, data in enumerate(dataloader):
File "/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py", line 517, in next
data = self._next_data()
File "/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py", line 1199, in _next_data
return self._process_data(data)
File "/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py", line 1225, in _process_data
data.reraise()
File "/usr/local/lib/python3.7/dist-packages/torch/_utils.py", line 429, in reraise
raise self.exc_type(msg)
FileNotFoundError: Caught FileNotFoundError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/usr/local/lib/python3.7/dist-packages/torch/utils/data/_utils/worker.py", line 202, in _worker_loop
data = fetcher.fetch(index)
File "/usr/local/lib/python3.7/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/usr/local/lib/python3.7/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/content/CVPR21Chal-SLR/Conv3D/dataset_sign_clip.py", line 111, in getitem
images.append(self.read_images(selected_folder, i))
File "/content/CVPR21Chal-SLR/Conv3D/dataset_sign_clip.py", line 75, in read_images
index_list = self.frame_indices_tranform_test(len(os.listdir(folder_path)), self.frames, clip_no)
FileNotFoundError: [Errno 2] No such file or directory: '../data/test_frames/signer34_sample1'

----Traceback Ends----

However, there is a signer34_sample1 inside /Conv3D/data/test_frames/. Any insights will be appreciated.
Thanks.

Running Docker Command

Hello! I have been struggling with getting the docker command to work. I'm working on a Mac with BigSur OS and have downloaded the Docker Desktop. I have been able to get the image to upload to the Docker Desktop but when I run the command in command line, I get the following error:
Error response from daemon: OCI runtime create failed: container_linux.go:380: starting container process caused: process_linux.go:545: container init caused: Running hook #0:: error running hook: exit status 1, stdout: , stderr: nvidia-container-cli: initialization error: driver error: failed to process request: unknown.

I'm unsure if my issue is nvidia based or if I've changed the code incorrectly on the path_to_your_data part, as I put in the path to where I downloaded the docker file from the main github page. Should this be the path to where the container is saved or the path to where the dataset is saved?

Thanks!

CUDA capability is not compatible with the current PyTorch installation

Hello
Initially, I would thank the author for this amazing repository

I following step by step of this instruction [reproduce.md](url)

I'm at > III: Procedues to reproduce our results > A. For RGB track

and I was struggling with this error since yesterday, it happen when I try to run
python main.py --config config/sign/test/test_bone.yaml

UserWarning: 
NVIDIA RTX A5000 with CUDA capability sm_86 is not compatible with the current PyTorch installation.
The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_61 sm_70 sm_75 compute_37.
If you want to use the NVIDIA RTX A5000 GPU with
<img width="970" alt="Screen Shot 1443-08-07 at 12 45 11 PM" src="https://user-images.githubusercontent.com/85832533/157636654-90100cea-ca2d-40e7-ae36-7a243278a6be.png">
 PyTorch, please check the instructions at https://pytorch.org/get-started/locally/

Any help?
Thank you

Wholebody yaml missing

Hi, I get the following error when I try to run the demo.py to extract 2d keypoints

FileNotFoundError: [Errno 2] No such file or directory: 'wholebody_w48_384x288.yaml'

Hi. I have already tried to run and test your code. But at the end, how can I know what the sign means ? ( the model only classifies into class from 0 - 225). I also try to find mapping-label file but I can not. Are there any label files like this ? Thank you !!!

No module named 'utils' when trying to run 'gen_hha.py'

Images' Docker

Hello !

I facing an issue related to the Nvidia docker image, when I run it by using this command

sudo docker run -it --gpus all -v path_to_your_data:/home/smilelab_slr/cvpr2021_allcode/shared_data cvpr2021cha_code /bin/bash

it gives me this error message:

Unable to find image 'cvpr2021cha_code:latest' locally
docker: Error response from daemon: pull access denied for cvpr2021cha_code, repository does not exist or may require 'docker login': denied: requested access to the resource is denied.
See 'docker run --help'.

Any help?