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app.py

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+import os
+import cv2
+import mediapipe as mp
+from mediapipe.tasks import python
+from mediapipe.tasks.python import vision
+from deepface import DeepFace
+import threading
+import time
+
+# --- Configuration ---
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
+DB_PATH = "known_faces"
+MODEL_PATH = 'blaze_face_short_range.tflite'
+
+# --- Shared Variables for Threading ---
+current_name = "Scanning..."
+is_recognizing = False  # Lock to prevent multiple recognition threads
+
+def recognize_face_async(face_crop):
+    """Background task to identify the face."""
+    global current_name, is_recognizing
+    try:
+        # enforce_detection=False is CRITICAL for speed since we already cropped
+        results = DeepFace.find(img_path=face_crop, 
+                                db_path=DB_PATH, 
+                                enforce_detection=False, 
+                                model_name="ArcFace", 
+                                silent=True)
+        
+        if len(results) > 0 and not results[0].empty:
+            new_name = os.path.basename(results[0]['identity'][0]).split('.')[0]
+            current_name = new_name
+        else:
+            current_name = "Unknown"
+    except Exception:
+        pass
+    finally:
+        is_recognizing = False
+
+# --- Initialize MediaPipe ---
+base_options = python.BaseOptions(model_asset_path=MODEL_PATH)
+options = vision.FaceDetectorOptions(base_options=base_options)
+detector = vision.FaceDetector.create_from_options(options)
+
+cap = cv2.VideoCapture(0)
+cv2.namedWindow('Smooth Face Recognition', cv2.WINDOW_NORMAL)
+cv2.resizeWindow('Smooth Face Recognition', 800, 900)
+prev_time = 0
+
+while cap.isOpened():
+    success, frame = cap.read()
+    if not success: break
+
+    # 1. High-Speed Detection (Runs at 60 FPS)
+    mp_image = mp.Image(image_format=mp.ImageFormat.SRGB, data=cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
+    detection_result = detector.detect(mp_image)
+
+    if detection_result.detections:
+        for detection in detection_result.detections:
+            bbox = detection.bounding_box
+            x, y, w, h = bbox.origin_x, bbox.origin_y, bbox.width, bbox.height
+
+            # 2. Trigger Recognition Thread (Doesn't block the video)
+            if not is_recognizing:
+                face_roi = frame[max(0, y):y+h, max(0, x):x+w].copy()
+                if face_roi.size > 0:
+                    is_recognizing = True
+                    # Start the background 'brain'
+                    thread = threading.Thread(target=recognize_face_async, args=(face_roi,))
+                    thread.daemon = True # Closes if main program closes
+                    thread.start()
+
+            # 3. Draw UI (Updates instantly)
+            color = (0, 255, 0) if current_name != "Unknown" else (0, 0, 255)
+            cv2.rectangle(frame, (x, y), (x + w, y + h), color, 2)
+            cv2.putText(frame, current_name, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), 2)
+
+    # FPS Counter
+    curr_time = time.time()
+    fps = 1 / (curr_time - prev_time)
+    prev_time = curr_time
+    cv2.putText(frame, f"FPS: {int(fps)}", (20, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 2)
+
+    cv2.imshow('Smooth Face Recognition', frame)
+    if cv2.waitKey(1) & 0xFF == ord('q'): break
+
+cap.release()
+cv2.destroyAllWindows()

requirements.txt

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+requests>=2.27.1
+numpy>=1.14.0
+pandas>=0.23.4
+gdown>=3.10.1
+tqdm>=4.30.0
+Pillow>=5.2.0
+opencv-python>=4.5.5.64
+tensorflow>=1.9.0
+keras>=2.2.0
+Flask>=1.1.2
+flask_cors>=4.0.1
+mtcnn>=0.1.0
+retina-face>=0.0.14
+fire>=0.4.0
+gunicorn>=20.1.0
+lightphe>=0.0.15
+lightdsa>=0.0.3
+python-dotenv>=1.0.1