Update app.py

app.py

@@ -109,8 +109,43 @@ def infer(video_in):
     # Get the directory name
     folder_path = os.path.dirname(video_in)
 
+    # Path to the input video file
+    input_video_path = video_in
+    
+    # Load the video file
+    video = VideoFileClip(input_video_path)
+    
+    # Get the length of the video in seconds
+    video_duration = video.duration
+    print(f"Video duration: {video_duration} seconds")
+    
+    # Check if the video duration is more than 10 seconds
+    if video_duration > 10:
+        # Cut the video to the first 10 seconds
+        cut_video = video.subclip(0, 10)
+        video_duration = 10
+        
+        # Extract the directory and filename
+        dir_name = os.path.dirname(input_video_path)
+        base_name = os.path.basename(input_video_path)
+        
+        # Generate the new filename
+        new_base_name = base_name.replace(".mp4", "_10sec_cut.mp4")
+        output_video_path = os.path.join(dir_name, new_base_name)
+        
+        # Save the cut video
+        cut_video.write_videofile(output_video_path, codec='libx264', audio_codec='aac')
+        print(f"Cut video saved as: {output_video_path}")
+    else:
+        print("Video is 10 seconds or shorter; no cutting needed.")
+
     # Execute the inference command
-    command = ['python', 'inference_from_video.py', '--original_args', 'ckpt/vta-ldm-clip4clip-v-large/summary.jsonl', '--model', 'ckpt/vta-ldm-clip4clip-v-large/pytorch_model_2.bin', '--data_path', folder_path]
+    command = ['python', 'inference_from_video.py', 
+               '--original_args', 'ckpt/vta-ldm-clip4clip-v-large/summary.jsonl', 
+               '--model', 'ckpt/vta-ldm-clip4clip-v-large/pytorch_model_2.bin', 
+               '--data_path', folder_path,
+               '--max_duration', video_duration
+              ]
     process = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True, bufsize=1)
 
     # Create threads to handle stdout and stderr