How to use Flow-guided video completion (FGVC)?

Jan 25, 2021
Reaction score
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 (
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 "".
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 "", 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:
File "", line 613, in <module>
    main (args)
  File "", line 576, in main
    video_completion_sphere (args)
  File "", line 383, in video_completion_sphere
    RAFT_model = initialize_RAFT (args)
  File "", line 78, in initialize_RAFT
    model.load_state_dict (torch.load (args.model))
  File "/usr/local/lib/python3.6/dist-packages/torch/", line 594, in load
    return _load (opened_zipfile, map_location, pickle_module, ** pickle_load_args)
  File "/usr/local/lib/python3.6/dist-packages/torch/", line 853, in _load
    result = unpickler.load ()
  File "/usr/local/lib/python3.6/dist-packages/torch/", line 845, in persistent_load
    load_tensor (data_type, size, key, _maybe_decode_ascii (location))
  File "/usr/local/lib/python3.6/dist-packages/torch/", line 834, in load_tensor
    loaded_storages [key] = restore_location (storage, location)
  File "/usr/local/lib/python3.6/dist-packages/torch/", line 175, in default_restore_location
    result = fn (storage, location)
  File "/usr/local/lib/python3.6/dist-packages/torch/", line 151, in _cuda_deserialize
    device = validate_cuda_device (location)
  File "/usr/local/lib/python3.6/dist-packages/torch/", 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!

Ask a Question

Want to reply to this thread or ask your own question?

You'll need to choose a username for the site, which only take a couple of moments. After that, you can post your question and our members will help you out.

Ask a Question

Members online

No members online now.

Forum statistics

Latest member

Latest Threads