dkatz2391 commited on
Commit
434fa76
·
verified ·
1 Parent(s): f1b0be5

keep it all on HF - easy dict errors

Browse files
Files changed (1) hide show
  1. app.py +10 -8
app.py CHANGED
@@ -166,22 +166,24 @@ def render_preview_video(state: dict, req: gr.Request) -> str:
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  """
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  if not state:
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  print(f"[{req.session_hash}] render_preview_video called with empty state. Returning None.")
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- # Consider returning a placeholder or raising an error if state is required
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  return None
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  user_dir = os.path.join(TMP_DIR, str(req.session_hash))
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  os.makedirs(user_dir, exist_ok=True) # Ensure directory exists
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- print(f"[{req.session_hash}] Unpacking state for video rendering.") # Add logging
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- gs, mesh = unpack_state(state)
 
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- print(f"[{req.session_hash}] Rendering video...") # Add logging
 
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  video = render_utils.render_video(gs, num_frames=120)['color']
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- video_geo = render_utils.render_video(mesh, num_frames=120)['normal']
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- video = [np.concatenate([video[i], video_geo[i]], axis=1) for i in range(len(video))]
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- video_path = os.path.join(user_dir, 'preview_sample.mp4') # Use a distinct name
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- print(f"[{req.session_hash}] Saving video to {video_path}") # Add logging
 
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  imageio.mimsave(video_path, video, fps=15)
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  torch.cuda.empty_cache()
 
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  """
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  if not state:
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  print(f"[{req.session_hash}] render_preview_video called with empty state. Returning None.")
 
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  return None
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  user_dir = os.path.join(TMP_DIR, str(req.session_hash))
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  os.makedirs(user_dir, exist_ok=True) # Ensure directory exists
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+ print(f"[{req.session_hash}] Unpacking state for video rendering.")
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+ # Only unpack gs, as mesh causes type errors with render_utils after unpacking
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+ gs, _ = unpack_state(state) # We still need the mesh for GLB, but not for this video preview
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+ print(f"[{req.session_hash}] Rendering video (Gaussian only)...")
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+ # Render ONLY the Gaussian splats, as rendering the unpacked mesh fails
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  video = render_utils.render_video(gs, num_frames=120)['color']
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+ # REMOVED: video_geo = render_utils.render_video(mesh, num_frames=120)['normal']
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+ # REMOVED: video = [np.concatenate([video[i], video_geo[i]], axis=1) for i in range(len(video))]
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+ video_path = os.path.join(user_dir, 'preview_sample.mp4')
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+ print(f"[{req.session_hash}] Saving video to {video_path}")
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+ # Save only the Gaussian render
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  imageio.mimsave(video_path, video, fps=15)
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  torch.cuda.empty_cache()