Fix tensor to numpy conversion for video export

- Import numpy for array handling
- Convert torch tensors to numpy arrays
- Handle float [0,1] to uint8 [0,255] conversion
- Convert 4D array to list of frames for export_to_video

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

app.py

@@ -2,6 +2,7 @@ import os
 import tempfile
 
 import gradio as gr
+import numpy as np
 import spaces
 import torch
 from diffusers.utils import export_to_video
@@ -79,6 +80,20 @@ def generate_interpolation(
         else:
             video_frames = output
 
+        # Convert tensor to numpy if needed
+        if torch.is_tensor(video_frames):
+            video_frames = video_frames.cpu().numpy()
+
+        # Ensure correct format: list of numpy arrays in [0, 255] range
+        if isinstance(video_frames, np.ndarray):
+            # If shape is (frames, height, width, channels)
+            if video_frames.ndim == 4:
+                # Convert from float [0, 1] to uint8 [0, 255] if needed
+                if video_frames.dtype == np.float32 or video_frames.dtype == np.float64:
+                    video_frames = (video_frames * 255).astype(np.uint8)
+                # Convert to list of frames
+                video_frames = [video_frames[i] for i in range(video_frames.shape[0])]
+
         # Export to temporary file
         temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
         output_path = temp_file.name