Update app.py

app.py

@@ -65,7 +65,7 @@ def to_frames(video_file):
   os.system('rm -r guide_frames;mkdir guide_frames')
   os.system(f"ffmpeg -i {video_file} guide_frames/%04d.jpg")
 
-def update(preset, enhance, video_file):
+def update(preset, enhance, scale2x, video_file):
 
   # Load presets
   ca = RuleCA(hidden_n=32, rule_channels=3)
@@ -91,6 +91,8 @@ def update(preset, enhance, video_file):
     size = (256, int(256*(vid_size[1]/vid_size[0])))
   else:
     size = (int(256*(vid_size[0]/vid_size[1])), 256)
+  if scale2x:
+    size = (size[0]*2, size[1]*2)
 
   # Starting grid
   x = torch.zeros(1, 4, size[1], size[0]).to(ca.device)
@@ -123,11 +125,13 @@ with demo:
     gr.Markdown("Choose a preset below, upload a video and then click **Run** to see the output. Read [this report](https://wandb.ai/johnowhitaker/nca/reports/Fun-with-Neural-Cellular-Automata--VmlldzoyMDQ5Mjg0) for background on this project, or check out my [AI art course](https://github.com/johnowhitaker/aiaiart) for an in-depth lesson on Neural Cellular Automata like this.")
     with gr.Row():
         preset = gr.Dropdown(['Glowing Crystals', 'Rainbow Diamonds', 'Dark Diamonds', 'Dragon Scales'], label='Preset')
-        enhance = gr.Checkbox(label='Rescale inputs (more extreme results)')
+        with gr.Column():
+          enhance = gr.Checkbox(label='Rescale inputs (more extreme results)')
+          scale2x = gr.Checkbox(label='Larger output (slower)')
     with gr.Row():
         inp = gr.Video(format='mp4', source='upload', label="Input video (ideally <30s)")
         out = gr.Video(label="Output")
     btn = gr.Button("Run")
-    btn.click(fn=update, inputs=[preset, enhance, inp], outputs=out)
+    btn.click(fn=update, inputs=[preset, enhance, scale2x, inp], outputs=out)
 
 demo.launch(enable_queue=True)