Update app.py

app.py

@@ -209,11 +209,13 @@ def calculate_safety_score(violations):
 
 def process_video(video_data):
     try:
+        # Save video to temporary file
         video_path = os.path.join(CONFIG["OUTPUT_DIR"], f"temp_{int(time.time())}.mp4")
         with open(video_path, "wb") as f:
             f.write(video_data)
         logger.info(f"Video saved: {video_path}")
 
+        # Read the video
         video = cv2.VideoCapture(video_path)
         if not video.isOpened():
             raise ValueError("Could not open video file")
@@ -228,8 +230,9 @@ def process_video(video_data):
         while True:
             ret, frame = video.read()
             if not ret:
-                break
+                break  # Break if the video has ended
 
+            # Process every frame (or based on FRAME_SKIP)
             if frame_count % CONFIG["FRAME_SKIP"] != 0:
                 frame_count += 1
                 continue
@@ -238,20 +241,25 @@ def process_video(video_data):
                 logger.info("Processing time limit reached")
                 break
 
+            # Model inference
             results = model(frame, device=device)
-            seen_violations = set()
+            seen_violations = set()  # Track violations detected in the current frame
+
             for result in results:
                 for box in result.boxes:
                     cls, conf = int(box.cls), float(box.conf)
                     label = CONFIG["VIOLATION_LABELS"].get(cls, None)
-                    if label not in CONFIG["VIOLATION_LABELS"].values():
-                        continue
-                    if conf < CONFIG["CONFIDENCE_THRESHOLD"]:
+                    
+                    # Skip if it's not a relevant violation or if confidence is too low
+                    if label not in CONFIG["VIOLATION_LABELS"].values() or conf < CONFIG["CONFIDENCE_THRESHOLD"]:
                         continue
+                    
                     if label in seen_violations:
-                        continue
+                        continue  # Avoid duplicates in the same frame
+                    
                     seen_violations.add(label)
 
+                    # Save the violation data
                     violation = {
                         "frame": frame_count,
                         "violation": label,
@@ -261,6 +269,7 @@ def process_video(video_data):
                     }
                     violations.append(violation)
 
+                    # Snapshot for the first occurrence of each violation
                     if not snapshot_taken[label]:
                         snapshot_path = os.path.join(CONFIG["OUTPUT_DIR"], f"snapshot_{frame_count}_{label}.jpg")
                         cv2.imwrite(snapshot_path, frame)
@@ -279,6 +288,7 @@ def process_video(video_data):
         video.release()
         os.remove(video_path)
 
+        # If no violations were detected, return a message
         if not violations:
             logger.info("No violations detected")
             return {
@@ -290,6 +300,7 @@ def process_video(video_data):
                 "message": "No violations detected in the video."
             }
 
+        # Calculate compliance score
         score = calculate_safety_score(violations)
         pdf_path, pdf_url, pdf_file = generate_violation_pdf(violations, score)
         report_id, final_pdf_url = push_report_to_salesforce(violations, score, pdf_path, pdf_file)