Create face_detection.py

face_detection.py

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+from mtcnn import MTCNN
+
+detector = MTCNN()
+
+def detect_faces(image):
+    """
+    Detects faces in an image using MTCNN.
+
+    Args:
+        image (numpy.ndarray): The input image.
+
+    Returns:
+        list: A list of dictionaries, where each dictionary contains
+              'box' (bounding box coordinates [x, y, width, height])
+              and 'confidence' (the confidence score).
+    """
+    faces = detector.detect_faces(image)
+    return faces
+
+if __name__ == '__main__':
+    # Example usage
+    import cv2
+    img = cv2.imread("test_image.jpg") # Replace with your image path
+    if img is not None:
+        detected_faces = detect_faces(img)
+        print(f"Detected {len(detected_faces)} faces.")
+        for face in detected_faces:
+            print(face['box'], face['confidence'])
+            x, y, w, h = face['box']
+            cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
+        cv2.imshow("Detected Faces", img)
+        cv2.waitKey(0)
+        cv2.destroyAllWindows()
+    else:
+        print("Error loading image.")