Update app.py

app.py

@@ -34,8 +34,6 @@ CONFIG = {
         "domain": "login"
     },
     "PUBLIC_URL_BASE": "https://huggingface.co/spaces/PrashanthB461/AI_Safety_Demo1/resolve/main/static/output/",
-    "FRAME_SKIP": 5,
-    "MAX_PROCESSING_TIME": 30
 }
 
 # Setup logging
@@ -74,8 +72,7 @@ def connect_to_salesforce():
     try:
         sf = Salesforce(**CONFIG["SF_CREDENTIALS"])
         logger.info("Connected to Salesforce")
-        # Verify object accessibility
-        sf.describe()  # Fetch metadata to ensure connection
+        sf.describe()
         logger.debug("Salesforce object metadata fetched successfully")
         return sf
     except Exception as e:
@@ -175,7 +172,6 @@ def push_report_to_salesforce(violations, score, pdf_path, pdf_file):
             record = sf.Safety_Video_Report__c.create(record_data)
         except Exception as e:
             logger.error(f"Failed to create Safety_Video_Report__c: {e}")
-            # Fallback to a standard object for debugging
             record = sf.Account.create({"Name": f"Safety_Report_{int(time.time())}"})
             logger.warning(f"Fell back to creating Account record: {record}")
         record_id = record["id"]
@@ -188,7 +184,6 @@ def push_report_to_salesforce(violations, score, pdf_path, pdf_file):
                     sf.Safety_Video_Report__c.update(record_id, {"PDF_Report_URL__c": uploaded_url})
                 except Exception as e:
                     logger.error(f"Failed to update Safety_Video_Report__c: {e}")
-                    # Fallback update
                     sf.Account.update(record_id, {"Description": uploaded_url})
                 pdf_url = uploaded_url
                 logger.debug(f"Updated record {record_id} with PDF URL: {pdf_url}")
@@ -205,9 +200,9 @@ def calculate_safety_score(violations):
     penalties = {
         "no_helmet": 25,
         "no_harness": 30,
-        "unsafe_posture": 20,
-        "unsafe_zone": 25
+        "unsafe_posture": 20
     }
+    # Only penalize for detected violations (no_helmet, no_harness, unsafe_posture)
     score = 100 - sum(penalties.get(v["violation"], 0) for v in violations)
     return max(score, 0)
 
@@ -227,15 +222,11 @@ def process_video(video_data):
 
         violations, snapshots = [], []
         frame_count = 0
-        start_time = time.time()
 
         while True:
             ret, frame = video.read()
             if not ret:
                 break
-            if frame_count % CONFIG["FRAME_SKIP"] != 0:
-                frame_count += 1
-                continue
 
             results = model(frame, device=device)
             seen_violations = set()  # Track unique violations in this frame
@@ -243,6 +234,9 @@ def process_video(video_data):
                 for box in result.boxes:
                     cls, conf = int(box.cls), float(box.conf)
                     label = CONFIG["VIOLATION_LABELS"].get(cls, f"class_{cls}")
+                    # Only consider "no_helmet", "no_harness", "unsafe_posture" as violations
+                    if label not in ["no_helmet", "no_harness", "unsafe_posture"]:
+                        continue
                     if label in seen_violations:
                         continue  # Skip if this violation type was already recorded in this frame
                     seen_violations.add(label)
@@ -258,7 +252,6 @@ def process_video(video_data):
 
                     snapshot_path = os.path.join(CONFIG["OUTPUT_DIR"], f"snapshot_{frame_count}_{label}.jpg")
                     cv2.imwrite(snapshot_path, frame)
-                    # Encode snapshot as base64 for immediate display
                     with open(snapshot_path, "rb") as img_file:
                         img_base64 = base64.b64encode(img_file.read()).decode('utf-8')
                     snapshots.append({
@@ -269,9 +262,6 @@ def process_video(video_data):
                     })
 
             frame_count += 1
-            if time.time() - start_time > CONFIG["MAX_PROCESSING_TIME"]:
-                logger.warning("Processing time limit exceeded")
-                break
 
         video.release()
         os.remove(video_path)
@@ -307,7 +297,6 @@ def gradio_interface(video_file):
             video_data = f.read()
         result = process_video(video_data)
 
-        # Format violations as a Markdown table
         violation_table = "No violations detected."
         if result["violations"]:
             header = "| Violation     | Timestamp | Confidence | Bounding Box             | Violation Details       |\n"
@@ -323,7 +312,6 @@ def gradio_interface(video_file):
                 rows.append(row)
             violation_table = header + separator + "\n".join(rows)
 
-        # Format snapshots as a bullet list with base64 images
         snapshots_text = "No snapshots captured."
         if result["snapshots"]:
             snapshots_text = "\n".join(