Open KamiCalcium opened 3 years ago
Is the input image contain a single person? This algorithm requires a single person input. And I guess 1024 and 2048 is too large and the errors are about CPU/GPU memory explosion.
Is the input image contain a single person? This algorithm requires a single person input. And I guess 1024 and 2048 is too large and the errors are about CPU/GPU memory explosion.
Hey thanks for the quick response!~
I don't understand why the algorithm requires a single-person input. In your demo (people skiing), there are also multiple people, right?
About the CPU/GPU memory explosion, I'm using 4 RTX 8000. If that's still not sufficient enough, is there a way to properly train and test the image with (2048,1024)? Should I scale the input image or what will you suggest?
Thanks a lot!
It crops and processes each human separately. Please read this line
Okay, this I understand. But what about this?
What is this input_size then? Isn't it the whole image size? Or the maximum size for each bbox?
Please read the instructions carefully. here. It also crops and processes each human separately.
Please read the instructions carefully. here. It also crops and processes each human separately.
I read it again but I only see this description about the input_size for config.py.
In the main/config.py, you can change settings of the model including dataset to use, network backbone, and input size and so on.
My understanding is this is the whole image size right? Since human36M' size is (256,256), which is the same as the default one in config.py. Then if my picture input_size is (2048,1024), should I change it to (2048,1024)?
The instruction of Quick demo says Set bbox_list at here.
The instruction of Quick demo says
Set bbox_list at here.
OK, this is pretty clear to me and I already set the individual bbox in the bbox_list.
demo.py references config.py and uses its input_shape to derive the vis_root array. I want to know what input_shape does here. Is this the whole image size?
No. The code crops and resizes each person to input_img_shape.
Hi thanks for the great works!
I've been trying testing the pre-trained model on cityperson dataset under the cityscape dataset.
The code perfectly went through when the input_size was setting as (256, 256) for Human3.6M as default. But obviously, the output root location was not correct due to the scaling problem. The proper input_size of the cityperson image is (2048, 1024). However, if I set the size to (2048, 1024) I got the following error:
To debug, I then make the input_size to (1024,1024). Then it perfectly went through and the result makes more sense than when I set it to (256, 256). I also tried (2048, 2048) and it gave a different error:
I don't know what is going on when the input_size is different. Can you please look at the problem and offer me some clues?
Thanks a lot!