Fallback to OpenCV when ONNX RetinaFace model is missing

.gitignore

@@ -1,58 +1,4 @@
-# Python
-__pycache__/
-*.py[cod]
-*$py.class
-*.so
-.Python
-build/
-develop-eggs/
-dist/
-downloads/
-eggs/
-.eggs/
-lib/
-lib64/
-parts/
-sdist/
-var/
-wheels/
-*.egg-info/
-.installed.cfg
-*.egg
-MANIFEST
-
-# Virtual environments
+templates/
 .venv/
-venv/
-ENV/
-env/
-.env
-
-# IDE
-.vscode/
-.idea/
-*.swp
-*.swo
-*~
-
-# OS
-.DS_Store
-Thumbs.db
-
-# Logs
-*.log
-logs/
-
-# Temporary files
-tmp/
-temp/
-tmp_templates/
-
-# Model files (if large)
-models/*.pkl
-models/*.h5
-models/*.model
-
-# Configuration files with sensitive data
-config/local.yaml
-config/production.yaml
+__pycache__/
+*.pyc

src/biometric/face_detection.py

@@ -14,8 +14,8 @@
 except Exception:  # pragma: no cover - runtime dependency guard
     ort = None  # type: ignore[assignment]
 
-from core.logging import get_logger, PerformanceTimer
-from core.exceptions import FaceDetectionError, ModelLoadError
+from src.core.logging import get_logger, PerformanceTimer
+from src.core.exceptions import FaceDetectionError, ModelLoadError
 
 logger = get_logger(__name__)
 
@@ -416,22 +416,37 @@ def _resolve_haarcascade_path(self) -> str:
         return "haarcascade_frontalface_default.xml"
 
 
-# Example usage and testing
 if __name__ == "__main__":
-    # Test face detection
-    detector = FaceDetector(backend="opencv")  # Use OpenCV for testing
+    detector = FaceDetector(backend="opencv")
 
-    print("Testing face detection...")
+    cap = cv2.VideoCapture(0)
 
-    # Create a test image (in practice, this would come from camera)
-    test_image = np.zeros((480, 640, 3), dtype=np.uint8)
+    if not cap.isOpened():
+        print("Error: Cannot access camera")
+        exit()
 
-    # Test detection
-    faces = detector.detect_faces(test_image)
-    print(f"Detected {len(faces)} faces")
+    print("Press 'q' to exit")
 
-    if faces:
-        largest_face = detector.detect_largest_face(test_image)
-        print(f"Largest face: {largest_face}")
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            break
 
-    print("Face detection test completed!")
+        # Detect faces
+        faces = detector.detect_faces(frame)
+
+        print("Faces detected:", len(faces))
+
+        # Draw boxes
+        for (x, y, w, h) in faces:
+            cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
+
+        # SHOW WINDOW 🔥
+        cv2.imshow("Face Detection", frame)
+
+        # Exit on 'q'
+        if cv2.waitKey(1) & 0xFF == ord('q'):
+            break
+
+    cap.release()
+    cv2.destroyAllWindows()

test_camera.py

@@ -0,0 +1,39 @@
+from src.biometric.face_detection import FaceDetector
+import cv2
+
+detector = FaceDetector(backend="opencv")
+
+cap = cv2.VideoCapture(0)
+
+if not cap.isOpened():
+    print("❌ Cannot access camera")
+    exit()
+
+while True:
+    ret, frame = cap.read()
+    if not ret:
+        break
+
+    # Resize frame for faster processing
+    small_frame = cv2.resize(frame, (0, 0), fx=0.5, fy=0.5)
+
+    # Detect faces on smaller frame
+    faces = detector.detect_faces(small_frame)
+
+    # Scale faces back to original size
+    scaled_faces = []
+    for (x, y, w, h) in faces:
+        scaled_faces.append((x * 2, y * 2, w * 2, h * 2))
+
+    # Draw on original frame
+    frame = detector.visualize_detections(frame, scaled_faces)
+
+    # SHOW WINDOW (correct indentation)
+    cv2.imshow("Face Detection", frame)
+
+    # Press ESC to exit
+    if cv2.waitKey(1) & 0xFF == 27:
+        break
+
+cap.release()
+cv2.destroyAllWindows()

test_face_detection.py

@@ -0,0 +1,28 @@
+import cv2
+import sys, os
+sys.path.append(os.path.abspath("LockLess/src"))
+
+from src.biometric.face_detection import FaceDetector
+detector = FaceDetector(backend="opencv")
+
+cap = cv2.VideoCapture(0)
+
+while True:
+    ret, frame = cap.read()
+    if not ret:
+        break
+
+    faces = detector.detect_faces(frame)
+
+    print("Faces detected:", len(faces))  # 👈 IMPORTANT
+
+    for (x, y, w, h) in faces:
+        cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
+
+    cv2.imshow("Face Detection", frame)
+
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+cap.release()
+cv2.destroyAllWindows()