dvschultz / ml-art-colabs Goto Github PK

Hi, in colab version of "Pix2PixHD_Next_Frame_Prediction", when trying to generate video using the parameter START FROM:

!python generate_video.py --name cuttlefish1 --dataroot ./datasets/cuttlefish1/ --fps 24 --how_many 600 --which_epoch latest --start_from 100

I get this error:
NameError: name 't' is not defined

Any clue? Thanks in advance

Hi there, I'm getting the following error when trying to run this notebook:

Traceback (most recent call last):
File "train.py", line 645, in
main()
File "train.py", line 637, in main
run_training(**vars(args))
File "train.py", line 522, in run_training
training_loop.training_loop(**training_options)
File "/content/drive/My Drive/colab-sg2-ada/stylegan2-ada/training/training_loop.py", line 129, in training_loop
G.copy_vars_from(rG)
File "/content/drive/My Drive/colab-sg2-ada/stylegan2-ada/dnnlib/tflib/network.py", line 512, in copy_vars_from
self._components[name].copy_vars_from(src_comp)
File "/content/drive/My Drive/colab-sg2-ada/stylegan2-ada/dnnlib/tflib/network.py", line 509, in copy_vars_from
self.copy_own_vars_from(src_net)
File "/content/drive/My Drive/colab-sg2-ada/stylegan2-ada/dnnlib/tflib/network.py", line 482, in copy_own_vars_from
tfutil.set_vars({self._get_vars()[name]: value for name, value in value_dict.items() if name in self._get_vars()})
File "/content/drive/My Drive/colab-sg2-ada/stylegan2-ada/dnnlib/tflib/tfutil.py", line 227, in set_vars
run(ops, feed_dict)
File "/content/drive/My Drive/colab-sg2-ada/stylegan2-ada/dnnlib/tflib/tfutil.py", line 33, in run
return tf.get_default_session().run(*args, **kwargs)
File "/tensorflow-1.15.2/python3.7/tensorflow_core/python/client/session.py", line 956, in run
run_metadata_ptr)
File "/tensorflow-1.15.2/python3.7/tensorflow_core/python/client/session.py", line 1156, in _run
(np_val.shape, subfeed_t.name, str(subfeed_t.get_shape())))
ValueError: Cannot feed value of shape (3, 3, 512, 256) for Tensor 'G_synthesis/64x64/Conv0_up/weight/new_value:0', which has shape '(3, 3, 512, 512)'

Can you please help me debug this? Since it is coming from the files I didn't write and I am a beginner, I am not sure how to tackle this. Thank you!

i faced this when I execute !pip install torch==1.4.0 torchvision==0.5.0
ERROR: Could not find a version that satisfies the requirement torch==1.4.0 (from versions: 1.11.0, 1.12.0, 1.12.1, 1.13.0, 1.13.1, 2.0.0, 2.0.1)
ERROR: No matching distribution found for torch==1.4.0

so the result is fake_int_img in result folder right?
and i trained my own dataset why the result still someone face.. ?

Hello, issues don't seem to be enabled on the pix2pixHD fork so I hope it is ok to write here. functions.gcd(a,b) has been deprecated and I just encountered an error when running.
The lines https://github.com/dvschultz/pix2pixHD/blob/video/train_video.py#L10-L11 can be updated to:

import math
def lcm(a,b): return abs(a * b)/math.gcd(a,b) if a and b else 0

Thank you for this awesome resource!

Hi there,
I'm running Pix2PixHD_Next_Frame_Prediction.ipynb in Google colab, following the link to 'open in colab' on this page: https://github.com/dvschultz/ml-art-colabs/blob/master/Pix2PixHD_Next_Frame_Prediction.ipynb
Everything works well until I start 'Initial Training' where it hangs at 'create web directory' & no epochs appear beneath.
Apparently I'm connected to a Tesla K80 GPU. Tried restarting the runtime a few times and it always hangs at the same place. I left it a good 30 mins or more, and the dataset is only ~350 images at 1280x736 pixels (which seemed to work well when I tried this a few months ago!) It gets as far as making the 'web' folder which contains 'loss_log.txt' and 'opt.txt' - but nothing else.

https://github.com/dvschultz/ml-art-colabs/blob/master/Demucs.ipynb?short_path=102e2a5

There is a mistake in line 145.
It should be:
"%cd /content/demucs" instead of
"%cd demucs/" otherwise the notebook won't work properly

Even in the moment of that video it is shown that previously it was
"%cd /content/demucs"

https://youtu.be/tHxsqFcx7gw?t=296

Furthemore -
!zip -r AI_01-tasnet_extra-shifts.zip ./separated/tasnet_extra/your_track_name_without_extension/*
instead of
!zip -r AI_01-tasnet_extra-shifts.zip ./separated/demucs/your_track_name_without_extension/*

otherwise it won't work

And you could add the line in the very end:
from google.colab import files files.download('AI_01-tasnet_extra-shifts.zip')
to actually allow to download the result file

depth_edge_model_ckpt: checkpoints/edge-model.pth
depth_feat_model_ckpt: checkpoints/depth-model.pth
rgb_feat_model_ckpt: checkpoints/color-model.pth
MiDaS_model_ckpt: MiDaS/model.pt
use_boostmonodepth: True
fps: 40
num_frames: 600
x_shift_range: [0.00, 0.00, -0.015, -0.015]
y_shift_range: [0.00, 0.00, -0.015, -0.00]
z_shift_range: [-0.05, -0.05, -0.05, -0.05]
traj_types: ['double-straight-line', 'double-straight-line', 'circle', 'circle']
video_postfix: ['dolly-zoom-in', 'zoom-in', 'circle', 'swing']
specific: ''
longer_side_len: 960
src_folder: image
depth_folder: depth
mesh_folder: mesh
video_folder: video
load_ply: False
save_ply: True
inference_video: True
gpu_ids: 0
offscreen_rendering: False
img_format: '.jpg'
depth_format: '.npy'
require_midas: True
depth_threshold: 0.04
ext_edge_threshold: 0.002
sparse_iter: 5
filter_size: [7, 7, 5, 5, 5]
sigma_s: 4.0
sigma_r: 0.5
redundant_number: 12
background_thickness: 70
context_thickness: 140
background_thickness_2: 70
context_thickness_2: 70
discount_factor: 1.00
log_depth: True
largest_size: 512
depth_edge_dilate: 10
depth_edge_dilate_2: 5
extrapolate_border: True
extrapolation_thickness: 60
repeat_inpaint_edge: True
crop_border: [0.03, 0.03, 0.05, 0.03]
anti_flickering: True

Potentially a limit related/caused to the input image resolution?

please share the weights, and also if possible then the dataset link or gdrive, too.