Update app.py

app.py

@@ -36,35 +36,21 @@ HF_API_TOKEN = os.getenv("HUGGINGFACE_API_TOKEN")
 
 # Salesforce configuration
 SF_CREDENTIALS = {
-    "username": os.getenv("SF_USERNAME", "smartlabour@attendance.system"),
-    "password": os.getenv("SF_PASSWORD", "#Prashanth@123"),
-    "security_token": os.getenv("SF_SECURITY_TOKEN", "pasQDqmWApzD0skgbv76gVgIs"),
-    "domain": "login"  # Use "test" for sandbox
+    "username": "smartlabour@attendance.system",
+    "password": "#Prashanth@123",
+    "security_token": "pasQDqmWApzD0skgbv76gVgIs",
+    "domain": "login"
 }
 
-
 @retry(stop_max_attempt_number=3, wait_fixed=2000)
 def connect_to_salesforce():
     try:
-        if SF_CREDENTIALS["instance"]:
-            sf = Salesforce(
-                username=SF_CREDENTIALS["username"],
-                password=SF_CREDENTIALS["password"],
-                security_token=SF_CREDENTIALS["security_token"],
-                instance=SF_CREDENTIALS["instance"]
-            )
-        else:
-            sf = Salesforce(
-                username=SF_CREDENTIALS["username"],
-                password=SF_CREDENTIALS["password"],
-                security_token=SF_CREDENTIALS["security_token"],
-                domain=SF_CREDENTIALS["domain"]
-            )
-        logger.info("Connected to Salesforce successfully")
+        sf = Salesforce(**SF_CREDENTIALS)
+        logger.info("Connected to Salesforce")
         sf.describe()
         return sf
     except Exception as e:
-        logger.error(f"Salesforce connection failed: {e}. Check SF_USERNAME, SF_PASSWORD, SF_SECURITY_TOKEN, and SF_DOMAIN in .env file.")
+        logger.error(f"Salesforce connection failed: {e}")
         raise
 
 class AttendanceSystem:
@@ -82,13 +68,12 @@ class AttendanceSystem:
         self.recognition_cooldown = 5  # seconds
         self.video_file_path = None
         self.video_processing = False
-        self.min_face_size = (100, 100)  # Minimum face size for registration/recognition
 
         # Initialize Salesforce
         try:
             self.sf = connect_to_salesforce()
         except Exception as e:
-            logger.error(f"Failed to initialize Salesforce connection: {e}")
+            logger.error(f"Error connecting to Salesforce: {e}")
             self.sf = None
     
         # Create directories
@@ -110,6 +95,21 @@ class AttendanceSystem:
             if os.path.exists("data/attendance.json"):
                 with open("data/attendance.json", "r") as f:
                     self.attendance_records = json.load(f)
+        
+            # Load embeddings from Salesforce for duplicate checks
+            if self.sf:
+                try:
+                    workers = self.sf.query_all("SELECT Worker_ID__c, Name, Face_Embedding__c FROM Worker__c")['records']
+                    for worker in workers:
+                        if worker['Face_Embedding__c']:
+                            embedding = json.loads(worker['Face_Embedding__c'])
+                            if worker['Worker_ID__c'] not in self.known_face_ids:
+                                self.known_face_embeddings.append(embedding)
+                                self.known_face_names.append(worker['Name'])
+                                self.known_face_ids.append(worker['Worker_ID__c'])
+                                self.next_worker_id = max(self.next_worker_id, int(worker['Worker_ID__c'][1:]) + 1)
+                except Exception as e:
+                    logger.error(f"Error loading embeddings from Salesforce: {e}")
         except Exception as e:
             logger.error(f"Error loading data: {e}")
             self.known_face_embeddings = []
@@ -192,25 +192,24 @@ class AttendanceSystem:
         image_array = np.array(image)
     
         try:
-            # Verify face and size
             face_analysis = DeepFace.analyze(img_path=image_array, actions=['emotion'], enforce_detection=True, detector_backend='opencv')
-            faces = DeepFace.extract_faces(img_path=image_array, target_size=(160, 160), enforce_detection=False, detector_backend='opencv')
-            if not faces or faces[0]['facial_area']['w'] < self.min_face_size[0] or faces[0]['facial_area']['h'] < self.min_face_size[1]:
-                return "❌ Face too small or not clear enough (must be at least 100x100 pixels)!", self.get_registered_workers_info()
         
             embedding = DeepFace.represent(img_path=image_array, model_name='Facenet')[0]['embedding']
         
+            name = name.strip().title()
+            if name in self.known_face_names:
+                return f"❌ {name} is already registered!", self.get_registered_workers_info()
+        
             # Check for duplicate face
             if len(self.known_face_embeddings) > 0:
                 distances = [np.linalg.norm(np.array(embedding) - np.array(known_embedding)) 
                             for known_embedding in self.known_face_embeddings]
-                if min(distances) < 10:
-                    best_match_index = distances.index(min(distances))
-                    return f"❌ Face already registered as {self.known_face_names[best_match_index]} (ID: {self.known_face_ids[best_match_index]})!", self.get_registered_workers_info()
-        
-            name = name.strip().title()
-            if name in self.known_face_names:
-                return f"❌ {name} is already registered!", self.get_registered_workers_info()
+                min_distance = min(distances)
+                if min_distance < 10:
+                    best_match_index = distances.index(min_distance)
+                    matched_name = self.known_face_names[best_match_index]
+                    matched_id = self.known_face_ids[best_match_index]
+                    return f"❌ Face matches existing worker: {matched_name} ({matched_id})!", self.get_registered_workers_info()
         
             worker_id = f"W{self.next_worker_id:04d}"
         
@@ -241,7 +240,6 @@ class AttendanceSystem:
                         logger.warning("Image URL not set due to upload failure")
                 except Exception as e:
                     logger.error(f"Error saving to Salesforce: {e}")
-                    return f"❌ Error saving to Salesforce: {e}. Check connection and permissions.", self.get_registered_workers_info()
         
             self.save_data()
         
@@ -254,23 +252,18 @@ class AttendanceSystem:
         except Exception as e:
             return f"❌ Error during registration: {str(e)}", self.get_registered_workers_info()
 
-    def register_worker_auto(self, face_image: np.ndarray, face_area: dict) -> Tuple[Optional[str], Optional[str]]:
+    def register_worker_auto(self, face_image: np.ndarray) -> Tuple[Optional[str], Optional[str]]:
         """Automatic worker registration for unrecognized faces"""
         try:
-            # Verify face size
-            if face_area['w'] < self.min_face_size[0] or face_area['h'] < self.min_face_size[1]:
-                logger.info("Face too small for registration (must be at least 100x100 pixels)")
-                return None, None
-        
             embedding = DeepFace.represent(img_path=face_image, model_name='Facenet')[0]['embedding']
         
             # Check for duplicate face
             if len(self.known_face_embeddings) > 0:
                 distances = [np.linalg.norm(np.array(embedding) - np.array(known_embedding)) 
                             for known_embedding in self.known_face_embeddings]
-                if min(distances) < 10:
-                    best_match_index = distances.index(min(distances))
-                    logger.info(f"Face already registered as {self.known_face_names[best_match_index]} (ID: {self.known_face_ids[best_match_index]})")
+                min_distance = min(distances)
+                if min_distance < 10:
+                    best_match_index = distances.index(min_distance)
                     return self.known_face_ids[best_match_index], self.known_face_names[best_match_index]
         
             worker_id = f"W{self.next_worker_id:04d}"
@@ -367,10 +360,6 @@ class AttendanceSystem:
                     face_area = face_obj['facial_area']
                     x, y, w, h = face_area['x'], face_area['y'], face_area['w'], face_area['h']
                 
-                    # Check face size
-                    if w < self.min_face_size[0] or h < self.min_face_size[1]:
-                        continue
-                
                     face_image = frame[y:y+h, x:x+w]
                 
                     try:
@@ -398,7 +387,7 @@ class AttendanceSystem:
                                     self.last_recognition_time[worker_id] = current_time
                             else:
                                 if face_image.size > 0:
-                                    new_id, new_name = self.register_worker_auto(face_image, face_area)
+                                    new_id, new_name = self.register_worker_auto(face_image)
                                     if new_id:
                                         worker_id = new_id
                                         worker_name = new_name
@@ -527,7 +516,7 @@ class AttendanceSystem:
 
     def get_registered_workers_info(self) -> str:
         if not self.sf:
-            return "❌ Salesforce connection not established. Check credentials in .env file and ensure user has access to Worker__c and ContentVersion objects."
+            return "❌ Salesforce connection not established."
     
         try:
             workers = self.sf.query_all("SELECT Name, Worker_ID__c, Image_Caption__c, Image_URL__c FROM Worker__c")['records']
@@ -555,7 +544,7 @@ class AttendanceSystem:
 
     def get_today_attendance(self) -> str:
         if not self.sf:
-            return "❌ Salesforce connection not established. Check credentials in .env file and ensure user has access to Attendance__c object."
+            return "❌ Salesforce connection not established."
     
         today = date.today().isoformat()
         try:
@@ -599,7 +588,7 @@ class AttendanceSystem:
             return "Invalid date format. Please use YYYY-MM-DD."
     
         if not self.sf:
-            return "❌ Salesforce connection not established. Check credentials in .env file and ensure user has access to Attendance__c object."
+            return "❌ Salesforce connection not established."
     
         try:
             records = self.sf.query_all(
@@ -705,7 +694,7 @@ def create_interface():
             ## 🚀 **Key Features:**
             - **🎥 Live Camera Recognition** - Real-time face detection from camera/CCTV
             - **📹 Video File Processing** - Process pre-recorded videos for attendance
-            - **🤖 Automatic Worker Registration** - Auto-register unknown faces with unique IDs in Salesforce
+            - **🤖 Automatic Worker Registration** - Auto-register unknown faces with unique IDs
             - **👤 Manual Registration** - Register workers manually with photos and AI-generated captions
             - **📅 24-Hour Attendance Rule** - One attendance mark per worker per day
             - **📊 Advanced Analytics** - Detailed reports and data export