Update app.py

app.py

@@ -100,7 +100,9 @@ def chunkify(video_path, fps, nb_frames):
     return chunks_array
     
         
-def run_inference(prompt, video_path, condition, video_length):
+def run_inference_by_chunkify(prompt, video_path, condition, video_length):
+
+    # DOESN'T WORK
 
     # Get FPS of original video input
     target_fps = get_video_dimension(video_path)[2] 
@@ -147,6 +149,43 @@ def run_inference(prompt, video_path, condition, video_length):
 
     return "done", processed_chunks[0] 
 
+
+def run_inference(prompt, video_path, condition, video_length):
+
+    
+
+    # Get FPS of original video input
+    target_fps = get_video_dimension(video_path)[2] 
+    print(f"INPUT FPS: {target_fps}")
+    
+    # Count total frames according to fps
+    total_frames = get_video_dimension(video_path)[3]
+
+    # Resize the video
+    resized = resize_video(video_path, 'resized.mp4', 512, 512, target_fps)
+
+    
+            
+    # Check if the file already exists
+    if os.path.exists(os.path.join(output_path, f"result.mp4")):
+        # Delete the existing file
+        os.remove(os.path.join(output_path, f"result.mp4"))
+    
+    if video_length > 12:
+        command = f"python inference.py --prompt '{prompt}' --condition '{condition}' --video_path '{resized}' --output_path '{output_path}' --width 512 --height 512 --fps 8 --video_length {video_length} --is_long_video"
+    else:
+        command = f"python inference.py --prompt '{prompt}' --condition '{condition}' --video_path '{resized}' --output_path '{output_path}' --temp_chunk_path 'result'  --width 512 --height 512 --fps 8 --video_length {video_length}"
+    subprocess.run(command, shell=True)
+    
+    # Construct the video path
+    video_path_output = os.path.join(output_path, f"result.mp4")
+
+    # Append processed chunk to final array
+    processed_chunks.append(video_path_output)
+    
+
+    return "done", video_path_output 
+
  
 
 css="""