Update app.py

app.py

@@ -49,18 +49,15 @@ CONFIG = {
         "domain": "login"
     },
     "PUBLIC_URL_BASE": "https://huggingface.co/spaces/PrashanthB461/AI_Safety_Demo2/resolve/main/static/output/",
-    "FRAME_SKIP": 15,  # Increased to process every 15th frame
-    "MAX_FRAMES": 100,  # Limit the number of frames to process
-    "FRAME_RESIZE": (640, 480),  # Downscale frames to this resolution
-    "MAX_PROCESSING_TIME": 60,  # Max processing time (seconds)
+    "FRAME_SKIP": 20,  # Increased to process every 20th frame (faster)
+    "MAX_PROCESSING_TIME": 25,  # Max processing time (seconds), leaving 5s for post-processing
     "CONFIDENCE_THRESHOLD": {  # Per-class thresholds
         "no_helmet": 0.4,
         "no_harness": 0.3,
         "unsafe_posture": 0.25,
         "unsafe_zone": 0.3,
         "improper_tool_use": 0.35
-    },
-    "MIN_VIOLATION_FRAMES": 2  # Min frames to confirm a violation
+    }
 }
 
 # Setup logging
@@ -219,12 +216,12 @@ def push_report_to_salesforce(violations, score, pdf_file):
 # Video Processing
 # ==========================
 def process_video(video_path):
-    """Analyze video for safety violations."""
+    """Analyze video for safety violations within 30 seconds."""
     try:
+        start_time = time.time()
         cap = cv2.VideoCapture(video_path)
         fps = cap.get(cv2.CAP_PROP_FPS) or 30
         frame_count = 0
-        processed_frames = 0
         violations = []
         snapshots = []
         snapshot_taken = {label: False for label in CONFIG["VIOLATION_LABELS"].values()}
@@ -235,17 +232,15 @@ def process_video(video_path):
             if not ret:
                 break
             
-            # Stop if max frames reached
-            if processed_frames >= CONFIG["MAX_FRAMES"]:
+            # Stop if processing time exceeds limit
+            if time.time() - start_time > CONFIG["MAX_PROCESSING_TIME"]:
+                logger.info("Reached max processing time, stopping frame analysis")
                 break
             
             if frame_count % CONFIG["FRAME_SKIP"] != 0:
                 frame_count += 1
                 continue
             
-            # Downscale frame for faster inference
-            frame = cv2.resize(frame, CONFIG["FRAME_RESIZE"], interpolation=cv2.INTER_AREA)
-            
             # Run detection
             results = model(frame, device=device)
             current_time = frame_count / fps
@@ -268,8 +263,6 @@ def process_video(video_path):
                         "timestamp": current_time
                     }
                     
-                    # Assign a generic worker ID (skipping tracking for speed)
-                    detection["worker_id"] = f"Worker_{frame_count}"
                     violations.append(detection)
                     
                     # Store frame for snapshot if first detection of this type
@@ -282,7 +275,6 @@ def process_video(video_path):
                         snapshot_taken[label] = True
             
             frame_count += 1
-            processed_frames += 1
         
         cap.release()
         
@@ -303,17 +295,6 @@ def process_video(video_path):
                 "url": f"{CONFIG['PUBLIC_URL_BASE']}{os.path.basename(snapshot_path)}"
             })
         
-        # Filter violations (require min frames)
-        filtered_violations = []
-        violation_counts = {}
-        for v in violations:
-            key = (v["worker_id"], v["violation"])
-            violation_counts[key] = violation_counts.get(key, 0) + 1
-        
-        for v in violations:
-            if violation_counts[(v["worker_id"], v["violation"])] >= CONFIG["MIN_VIOLATION_FRAMES"]:
-                filtered_violations.append(v)
-        
         # Calculate safety score
         penalty_weights = {
             "no_helmet": 25,
@@ -322,12 +303,12 @@ def process_video(video_path):
             "unsafe_zone": 35,
             "improper_tool_use": 25
         }
-        unique_violations = set((v["worker_id"], v["violation"]) for v in filtered_violations)
-        total_penalty = sum(penalty_weights.get(v, 0) for _, v in unique_violations)
+        unique_violations = set(v["violation"] for v in violations)
+        total_penalty = sum(penalty_weights.get(v, 0) for v in unique_violations)
         safety_score = max(100 - total_penalty, 0)
         
         return {
-            "violations": filtered_violations,
+            "violations": violations,
             "snapshots": snapshots,
             "score": safety_score,
             "message": ""
@@ -350,6 +331,8 @@ def analyze_video(video_file):
         return "No video uploaded", "", "", "", ""
     
     try:
+        start_time = time.time()
+        
         # Process video
         result = process_video(video_file)
         if result["message"]:
@@ -366,13 +349,18 @@ def analyze_video(video_file):
             pdf_file
         )
         
+        # Check total time
+        total_time = time.time() - start_time
+        if total_time > 30:
+            logger.warning(f"Processing took {total_time:.2f}s, exceeded 30s target")
+        
         # Format outputs
         violation_table = (
-            "| Violation Type         | Timestamp (s) | Confidence | Worker ID |\n"
-            "|------------------------|---------------|------------|-----------|\n" +
+            "| Violation Type         | Timestamp (s) | Confidence |\n"
+            "|------------------------|---------------|------------|\n" +
             "\n".join(
                 f"| {CONFIG['DISPLAY_NAMES'].get(v['violation'], v['violation']):<22} | "
-                f"{v['timestamp']:.2f}        | {v['confidence']:.2f}      | {v['worker_id']} |"
+                f"{v['timestamp']:.2f}        | {v['confidence']:.2f}      |"
                 for v in result["violations"]
             ) if result["violations"] else "No violations detected."
         )