Update app.py

app.py

@@ -505,16 +505,39 @@ def push_report_to_salesforce(violations, score, pdf_path, pdf_file):
 
 def process_video(video_data):
     """Process video to detect safety violations"""
+    video_path = None  # Initialize video_path for cleanup
     try:
         # Validate video data
         if not video_data:
             raise ValueError("Empty video data provided.")
-
-        # Save video to a temporary file
-        video_fd, video_path = tempfile.mkstemp(suffix=".mp4", dir=TEMP_DIR)
-        with os.fdopen(video_fd, "wb") as f:
-            f.write(video_data)
-        logger.info(f"Video saved: {video_path}")
+        
+        # Log the size of the video data
+        logger.info(f"Received video data size: {len(video_data)} bytes")
+        if len(video_data) == 0:
+            raise ValueError("Video data is empty.")
+
+        # Save video to a temporary file using NamedTemporaryFile
+        with tempfile.NamedTemporaryFile(suffix=".mp4", dir=TEMP_DIR, delete=False) as temp_file:
+            temp_file.write(video_data)
+            temp_file.flush()  # Ensure all data is written to disk
+            video_path = temp_file.name
+        logger.info(f"Video saved to temporary file: {video_path}")
+
+        # Verify the file exists and has content
+        if not os.path.exists(video_path):
+            raise FileNotFoundError(f"Temporary video file not found: {video_path}")
+        file_size = os.path.getsize(video_path)
+        if file_size == 0:
+            raise ValueError(f"Temporary video file is empty: {video_path}")
+        logger.info(f"Temporary video file size: {file_size} bytes")
+
+        # Ensure the file is readable
+        try:
+            with open(video_path, "rb") as f:
+                f.read(1)  # Test read access
+            logger.info(f"Temporary video file is readable: {video_path}")
+        except Exception as e:
+            raise IOError(f"Cannot read temporary video file {video_path}: {str(e)}")
 
         # Open video with OpenCV
         cap = cv2.VideoCapture(video_path)
@@ -676,8 +699,6 @@ def process_video(video_data):
 
         # Ensure resources are released
         cap.release()
-        if os.path.exists(video_path):
-            os.remove(video_path)
             
         processing_time = time.time() - start_time
         logger.info(f"Processing complete in {processing_time:.2f}s")
@@ -754,13 +775,19 @@ def process_video(video_data):
 
     except Exception as e:
         logger.error(f"Error processing video: {str(e)}", exc_info=True)
-        if 'video_path' in locals() and os.path.exists(video_path):
-            os.remove(video_path)
         yield f"Error processing video: {str(e)}", "", "", "", ""
     finally:
+        # Clean up the temporary video file
+        if video_path and os.path.exists(video_path):
+            try:
+                os.remove(video_path)
+                logger.info(f"Cleaned up temporary video file: {video_path}")
+            except Exception as e:
+                logger.error(f"Failed to clean up temporary video file {video_path}: {e}")
         # Clean up temporary directory
         if os.path.exists(TEMP_DIR):
             shutil.rmtree(TEMP_DIR, ignore_errors=True)
+            logger.info(f"Cleaned up temporary directory: {TEMP_DIR}")
 
 def gradio_interface(video_file):
     """Gradio interface for the video processing"""
@@ -768,13 +795,20 @@ def gradio_interface(video_file):
         return "No file uploaded.", "", "No file uploaded.", "", ""
         
     try:
+        # Read the video file
         with open(video_file, "rb") as f:
             video_data = f.read()
 
+        # Log the size of the uploaded video file
+        logger.info(f"Uploaded video file size: {len(video_data)} bytes")
+        if len(video_data) == 0:
+            return "Uploaded video file is empty.", "", "", "", ""
+
         # Validate FFmpeg availability
         if not FFMPEG_AVAILABLE:
             return "FFmpeg is not available in the environment. Please install FFmpeg to process videos.", "", "", "", ""
 
+        # Process the video
         for status, score, snapshots_text, record_id, details_url in process_video(video_data):
             yield status, score, snapshots_text, record_id, details_url