Create app.py

app.py

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+import os
+import torch
+from torchvision.io import read_video, read_video_timestamps
+
+from videogpt import download, load_vqvae
+from videogpt.data import preprocess
+import imageio
+import gradio as gr
+from moviepy.editor import *
+
+device = torch.device('cpu')
+vqvae = load_vqvae('kinetics_stride2x4x4', device=device).to(device)
+
+resolution, sequence_length = vqvae.hparams.resolution, 16
+
+def vgpt(invid):
+  try:
+    os.remove("output.mp4")
+  except FileNotFoundError:
+    pass
+  clip = VideoFileClip(invid)
+  rate = clip.fps
+  pts = read_video_timestamps(invid, pts_unit='sec')[0]
+  video = read_video(invid, pts_unit='sec', start_pts=pts[0], end_pts=pts[sequence_length - 1])[0]
+  video = preprocess(video, resolution, sequence_length).unsqueeze(0).to(device)
+
+  with torch.no_grad():
+      encodings = vqvae.encode(video)
+      video_recon = vqvae.decode(encodings)
+      video_recon = torch.clamp(video_recon, -0.5, 0.5)
+
+  videos = video_recon[0].permute(1, 2, 3, 0) # CTHW -> THWC
+  videos = ((videos + 0.5) * 255).cpu().numpy().astype('uint8')
+  imageio.mimwrite('output.mp4', videos, fps=int(rate))
+  return './output.mp4'
+
+inputs = gr.inputs.Video(label="Input Video")
+outputs = gr.outputs.Video(label="Output Video")
+
+title = "VideoGPT"
+description = "demo for VideoGPT by University of California, Berkeley. To use it, simply upload your video, or click one of the examples to load them. Read more at the links below."
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2104.10157'>VideoGPT: Video Generation using VQ-VAE and Transformers</a> | <a href='https://github.com/wilson1yan/VideoGPT'>Github Repo</a></p>"
+
+examples = [
+    ['gradio/bear.mp4'],
+    ['gradio/breakdance.mp4']
+]
+
+gr.Interface(vgpt, inputs, outputs, title=title, description=description, article=article, examples=examples).launch(debug=True)