Update app.py

app.py

@@ -47,7 +47,7 @@ def resize_and_pad(image, target_size):
     return new_image
 
 # Process a single frame through the depth model
-def process_frame(frame, seed=0, target_size=(512, 512)):
+def process_frame(frame, seed=0, target_size=(1024, 1024)):
     """Process a single frame and return depth map."""
     try:
         torch.cuda.empty_cache()  # Clear GPU cache
@@ -104,7 +104,7 @@ def process_video(video_path, fps=0, seed=0):
             depth_map = process_frame(frame, seed)
 
             if depth_map is not None:
-                # Save frame
+                # Save frame in lossless PNG format
                 frame_path = os.path.join(frames_dir, f"frame_{i:06d}.png")
                 depth_map.save(frame_path, format='PNG', compress_level=0)
 
@@ -123,20 +123,20 @@ def process_video(video_path, fps=0, seed=0):
         zip_path = os.path.join(temp_dir, zip_filename)
         shutil.make_archive(zip_path[:-4], 'zip', frames_dir)
 
-        # Create MP4 video
+        # Create MP4 video with lossless encoding
         video_filename = f"depth_video_{int(time.time())}.mp4"
         output_video_path = os.path.join(temp_dir, video_filename)
 
         try:
-            # FFmpeg settings for high-quality MP4
+            # FFmpeg settings for lossless MP4
             input_pattern = os.path.join(frames_dir, 'frame_%06d.png')
             (
                 ffmpeg
                 .input(input_pattern, pattern_type='sequence', framerate=fps)
-                .output(output_video_path, vcodec='libx264', pix_fmt='yuv420p', crf=17, preset='slow')
+                .output(output_video_path, vcodec='libx264', pix_fmt='yuv420p', preset='veryslow', crf=0)
                 .run(overwrite_output=True, quiet=True)
             )
-            logger.info("MP4 video created successfully!")
+            logger.info("Lossless MP4 video created successfully!")
 
         except ffmpeg.Error as e:
             logger.error(f"Error creating video: {e.stderr.decode() if e.stderr else str(e)}")