gafniguy / 4D-Facial-Avatars

Dynamic Neural Radiance Fields for Monocular 4D Facial Avater Reconstruction

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About real_to_nerf.py

HyunsooCha opened this issue · comments

Hello.
Thank you for your excellent work. NerFACE is helpful for my study.
I recorded my video sequence to make a JSON file. Then, using FFmpeg, I made frame image files. However, I've got this error.

####################################################################################
Reading tracked face data
found 2877 images in image folder
Traceback (most recent call last):
File "real_to_nerf.py", line 1532, in
generate_driven_test_sequence(configargs, 1000)
File "real_to_nerf.py", line 1144, in generate_driven_test_sequence
intrinsics = read_intrinsics(os.path.join(args.source, "intrinsics.txt"), im_size)
File "real_to_nerf.py", line 64, in read_intrinsics
all_intrinsics = np.genfromtxt(path_to_intrinsics_txt, dtype=None)
File "/home/stephencha/.local/lib/python3.8/site-packages/numpy/lib/npyio.py", line 1813, in genfromtxt
fid = np.lib._datasource.open(fname, 'rt', encoding=encoding)
File "/home/stephencha/.local/lib/python3.8/site-packages/numpy/lib/_datasource.py", line 193, in open
return ds.open(path, mode, encoding=encoding, newline=newline)
File "/home/stephencha/.local/lib/python3.8/site-packages/numpy/lib/_datasource.py", line 532, in open
raise FileNotFoundError(f"{path} not found.")
FileNotFoundError: ./real2nerf/source/intrinsics.txt not found.
####################################################################################

I would like to know how to make an intrinsics.txt file.
I think I should make intrinsics.txt using frame tracking to go forward. So I searched GitHub, and I found some useful open sources.

https://github.com/kimoktm/Face2face
https://github.com/YadiraF/DECA

The train JSON file contains camera x, expression, and bounding box parameters. I think DECA (including FLAME) could make these parameters. However, I could not know what was inside the intrinsics.txt file.

Thanks.

Hi,
it's the camera intrinsics, fx fy cx cy
cx and cy are normalized by the image size.

The bounding box parameters are the start and end of the box (in pixel coordinates normalized to [0,1] of where the face is). This is used to guide the sampling of rays to sample more rays there. You can also just use the default 0,1

I appreciate your reply. Thank you :)