nivha / single_video_generation Goto Github PK
View Code? Open in Web Editor NEWHome Page: https://nivha.github.io/vgpnn
License: Creative Commons Zero v1.0 Universal
Home Page: https://nivha.github.io/vgpnn
License: Creative Commons Zero v1.0 Universal
When I run it on the ballet example like this:
python3 run_generation.py --frames_dir=/home/frank/tmp/ballet/ballet_Wz_f9B4pPtg --start_frame=1 --end_frame=60
Then I get this error:
Namespace(gpu='0', results_dir='./results/generation', frames_dir='/home/frank/tmp/ballet/ballet_Wz_f9B4pPtg', start_frame=1, end_frame=60, max_size=144, min_size=(3, 15), downfactor=(0.85, 0.85), J=5, J_start_from=1, kernel_size=(3, 7, 7), sthw=(0.5, 1, 1), reduce='median', vgpnn_type='pm', use_noise=True, noise_amp=5, verbose=True, save_intermediate=True, save_intermediate_path='./results/generation')
/home/frank/.local/lib/python3.11/site-packages/transformers/utils/generic.py:441: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.
_torch_pytree._register_pytree_node(
Traceback (most recent call last):
File "/home/frank/tmp/single_video_generation/run_generation.py", line 70, in <module>
VGPNN, orig_vid = vgpnn.get_vgpnn(
^^^^^^^^^^^^^^^^
File "/home/frank/tmp/single_video_generation/vgpnn.py", line 215, in get_vgpnn
orig_vid = read_original_video(o.frames_dir, o.start_frame, o.end_frame, o.max_size, o.device, verbose=verbose, ext=ext)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/frank/tmp/single_video_generation/utils/main_utils.py", line 48, in read_original_video
frames = read_frames(frames_dir, start_frame, end_frame, resizer, device=device, verbose=verbose, ext=ext)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/frank/tmp/single_video_generation/utils/main_utils.py", line 35, in read_frames
x = frame_resizer(x)
^^^^^^^^^^^^^^^^
File "/home/frank/tmp/single_video_generation/utils/resize_right.py", line 71, in resize
field_of_view, weights = prepare_weights_and_field_of_view_1d(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/frank/tmp/single_video_generation/utils/resize_right.py", line 165, in prepare_weights_and_field_of_view_1d
field_of_view = get_field_of_view(projected_grid, cur_support_sz, in_sz,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/frank/tmp/single_video_generation/utils/resize_right.py", line 284, in get_field_of_view
field_of_view = mirror[fw.remainder(field_of_view, mirror.shape[0])]
~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: indices should be either on cpu or on the same device as the indexed tensor (cpu)
`(vgpnn) C:\ai\single_video_generation-main>python run_generation.py --gpu 0 --frames_dir data/airballoons_QGAMTlI6XxY --start_frame 66 --end_frame 80 --max_size 360 --use_noise False --min_size '(6,40)'
Namespace(J=5, J_start_from=1, downfactor=(0.85, 0.85), end_frame=80, frames_dir='data/airballoons_QGAMTlI6XxY', gpu='0', kernel_size=(3, 7, 7), max_size=360, min_size='(6,40)', noise_amp=5, reduce='median', results_dir='./results/generation', save_intermediate=True, save_intermediate_path='./results/generation', start_frame=66, sthw=(0.5, 1, 1), use_noise=False, verbose=True, vgpnn_type='pm')
Traceback (most recent call last):
File "run_generation.py", line 70, in
VGPNN, orig_vid = vgpnn.get_vgpnn(
File "C:\ai\single_video_generation-main\vgpnn.py", line 217, in get_vgpnn
downscales, upscale_factors, out_shapes = scale_utils.get_scales_out_shapes(T, H, W, o.downfactor, o.min_size)
File "C:\ai\single_video_generation-main\utils\scale_utils.py", line 48, in get_scales_out_shapes
assert T >= min_size[0], f"min_size ({min_size[0]},{min_size[1]}) larger than original size ({T},{H},{W}) (it must be smaller)"
TypeError: '>=' not supported between instances of 'int' and 'str'
(vgpnn) C:\ai\single_video_generation-main>python run_generation.py --gpu 0 --frames_dir data/airballoons_QGAMTlI6XxY --start_frame 6 --end_frame 80 --use_noise False
Namespace(J=5, J_start_from=1, downfactor=(0.85, 0.85), end_frame=80, frames_dir='data/airballoons_QGAMTlI6XxY', gpu='0', kernel_size=(3, 7, 7), max_size=144, min_size=(3, 15), noise_amp=5, reduce='median', results_dir='./results/generation', save_intermediate=True, save_intermediate_path='./results/generation', start_frame=6, sthw=(0.5, 1, 1), use_noise=False, verbose=True, vgpnn_type='pm')
Traceback (most recent call last):
File "run_generation.py", line 70, in
VGPNN, orig_vid = vgpnn.get_vgpnn(
File "C:\ai\single_video_generation-main\vgpnn.py", line 226, in get_vgpnn
assert ret_pyr[0].shape[2] >= o.kernel_size[0], f'smallest pyramid level has less frames {ret_pyr[0].shape[2]} than temporal kernel-size {o.kernel_size[0]}. You may want to increase min_size of the temporal dimension'
AssertionError: smallest pyramid level has less frames 2 than temporal kernel-size 3. You may want to increase min_size of the temporal dimension`
Hello, I'm having some problems trying to run the code.
First of all I ran into a device issue in utils/resize_right.py
. I had to add a set device in get_field_of_view
:
mirror = fw_cat((fw.arange(in_sz), fw.arange(in_sz - 1, -1, step=-1)), fw)
mirror = fw_set_device(mirror, projected_grid.device, fw) # <-- avoids device error in the following line
field_of_view = mirror[fw.remainder(field_of_view, mirror.shape[0])]
Now I'm running into an AssertionError related to the temporal dimension:
Namespace(gpu='0', results_dir='output/', frames_dir='data/', start_frame=1, end_frame=15, max_size=144, min_size=(3, 15), downfactor=(0.85, 0.85), J=5, J_start_from=1, kernel_size=(3, 7, 7), sthw=(0.5, 1, 1), reduce='median', vgpnn_type='pm', use_noise=True, noise_amp=5, verbose=True, save_intermediate=True, save_intermediate_path='output/')
Traceback (most recent call last):
File "/home/hans/code/vgpnn/run_generation.py", line 82, in <module>
VGPNN, orig_vid = vgpnn.get_vgpnn(
File "/home/hans/code/vgpnn/vgpnn.py", line 293, in get_vgpnn
assert (
AssertionError: smallest pyramid level has less frames 2 than temporal kernel-size 3. You may want to increase min_size of the temporal dimension
I'm using all the default settings. I've only set --frames_dir
and --frames_dir
. My video is square about 300 frames long (but the default settings only look at the first 15).
I've also tried setting --min_size 4,15
but ran into exactly the same error.
Any idea what could be going wrong?
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.