Hi - wanted to test out the models but in trying to run the demo, it's unable to build any of the models (HR, HG2) due to this key error:

I'm working on debugging but if you have any insight, please let me know. Thanks!

Hello, thank you for your excellent code to help my research a lot. I saw that 30 and 300 epochs were used respectively to train HG in the paper. Could you tell me what the training parameters(lr, weight_decay, and Lr_decay_epoch) were set to at 30 epochs？

Env:

• Ubuntu 20.04
• Python 3.8
• PyTorch 1.8.1

CPU:

Architecture:                    x86_64
CPU op-mode(s):                  32-bit, 64-bit
Byte Order:                      Little Endian
Address sizes:                   39 bits physical, 48 bits virtual
CPU(s):                          4
On-line CPU(s) list:             0-3
Thread(s) per core:              1
Core(s) per socket:              4
Socket(s):                       1
NUMA node(s):                    1
Vendor ID:                       GenuineIntel
CPU family:                      6
Model:                           94
Model name:                      Intel(R) Core(TM) i5-6500 CPU @ 3.20GHz
Stepping:                        3
CPU MHz:                         3503.549
CPU max MHz:                     3600.0000
CPU min MHz:                     800.0000

Inference log:

$ CUDA_VISIBLE_DEVICES= python demo.py /data/ --model HG2 --output_dir logs/demo_result --ckpt /fclip_ckpt/ckpt/HG2/checkpoint.pth.tar --display False
Namespace(camid=0, ckpt='/fclip_ckpt/ckpt/HG2/checkpoint.pth.tar', display=True, img_glob='*.png', input='/data/', model='HG2', output_dir='logs/demo_result', skip=1, waitkey=1)
logs/demo_result
==> Loading video.
[ERROR:0] global /tmp/pip-req-build-rcdoave0/opencv/modules/videoio/src/cap.cpp (160) open VIDEOIO(CV_IMAGES): raised OpenCV exception:

OpenCV(4.5.2) /tmp/pip-req-build-rcdoave0/opencv/modules/videoio/src/cap_images.cpp:253: error: (-5:Bad argument) CAP_IMAGES: can't find starting number (in the name of file): /data/ in function 'icvExtractPattern'


==> Processing Image Directory Input.
==> Successfully loaded video.
Using device:  cpu
0-th head, head type raw, head output 2
1-th head, head type raw, head output 2
2-th head, head type raw, head output 1
3-th head, head type raw, head output 1
0-th head, head type raw, head output 2
1-th head, head type raw, head output 2
2-th head, head type raw, head output 1
3-th head, head type raw, head output 1
=> loading model from /fclip_ckpt/ckpt/HG2/checkpoint.pth.tar
Finished constructing model!
==> Running Demo.
Processing: 1 Total time spent:30.598598
Average frame rate:0.032681
==> Finshed Demo.

The origin image:

The output image:

Firstly, thanks for the marvelous work and well written codes.

A little remind : when I was trying to run the code, I found that in the file FClip/models/pose_hrnet.py, at line 525, the path of yaml should be changed to my own path to run correctly.

Hello, I'm trying to use F-Clip on my own dataset. During aligning the anotations, I found the model input includes 'meta' (dict includes 'lpre' and 'lpre_label') from the york-urban dataset, while 'meta' was not mentioned in the paper and i couldn't find how it was used the loss calculations. So, would you mind explaining what is 'meta' and whether the model actually used it.