How can you use Flow-guided video completion (FGVC) for a personal file?
Operation is not specified on the various official sources for those who would like to use the FGVC freely from the Google Colab platform (https://colab.research.google.com/drive/1pb6FjWdwq_q445rG2NP0dubw7LKNUkqc?usp=sharing).
I, as a test, I uploaded a video to Google Drive (of the same account from which I was running Google Colab's scripts) divided into various frames, located in a .zip folder called "demo1.zip".
I then ran the first script in the sequence, called "Prepare environment", I activated video sharing via public link and I copied the link in the second script (immediately after the first word "wget –quiet") and in the first entry "rm" I entered "demo1.zip", in relation to the name of my video file.
I proceeded like this after reading the description just above the run button of the second script: "We show a demo on a 15-frames sequence. To process your own data, simply upload the sequence and specify the path."
Running the second script as well, this is successful and my video file is loaded.
I then go to the fourth (and last) script which consists in processing the content through an AI to obtain the final product with an enlarged Field Of View (FOV => larger aspect ratio). After a few seconds of running, the process ends with an error:
What's wrong with execution? Is there a way to fix and allow to finish the process with Google Colab? Let me know!
Operation is not specified on the various official sources for those who would like to use the FGVC freely from the Google Colab platform (https://colab.research.google.com/drive/1pb6FjWdwq_q445rG2NP0dubw7LKNUkqc?usp=sharing).
I, as a test, I uploaded a video to Google Drive (of the same account from which I was running Google Colab's scripts) divided into various frames, located in a .zip folder called "demo1.zip".
I then ran the first script in the sequence, called "Prepare environment", I activated video sharing via public link and I copied the link in the second script (immediately after the first word "wget –quiet") and in the first entry "rm" I entered "demo1.zip", in relation to the name of my video file.
I proceeded like this after reading the description just above the run button of the second script: "We show a demo on a 15-frames sequence. To process your own data, simply upload the sequence and specify the path."
Running the second script as well, this is successful and my video file is loaded.
I then go to the fourth (and last) script which consists in processing the content through an AI to obtain the final product with an enlarged Field Of View (FOV => larger aspect ratio). After a few seconds of running, the process ends with an error:
Python:
File "video_completion.py", line 613, in <module>
main (args)
File "video_completion.py", line 576, in main
video_completion_sphere (args)
File "video_completion.py", line 383, in video_completion_sphere
RAFT_model = initialize_RAFT (args)
File "video_completion.py", line 78, in initialize_RAFT
model.load_state_dict (torch.load (args.model))
File "/usr/local/lib/python3.6/dist-packages/torch/serialization.py", line 594, in load
return _load (opened_zipfile, map_location, pickle_module, ** pickle_load_args)
File "/usr/local/lib/python3.6/dist-packages/torch/serialization.py", line 853, in _load
result = unpickler.load ()
File "/usr/local/lib/python3.6/dist-packages/torch/serialization.py", line 845, in persistent_load
load_tensor (data_type, size, key, _maybe_decode_ascii (location))
File "/usr/local/lib/python3.6/dist-packages/torch/serialization.py", line 834, in load_tensor
loaded_storages [key] = restore_location (storage, location)
File "/usr/local/lib/python3.6/dist-packages/torch/serialization.py", line 175, in default_restore_location
result = fn (storage, location)
File "/usr/local/lib/python3.6/dist-packages/torch/serialization.py", line 151, in _cuda_deserialize
device = validate_cuda_device (location)
File "/usr/local/lib/python3.6/dist-packages/torch/serialization.py", line 135, in validate_cuda_device
raise RuntimeError ('Attempting to deserialize object on a CUDA'
RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available () is False. If you are running on a CPU-only machine, please use torch.load with map_location = torch.device ('cpu') to map your storages to the CPU.What's wrong with execution? Is there a way to fix and allow to finish the process with Google Colab? Let me know!