Mit FaceDetectionAndLandmark ist es nun moeglich ein Gesicht zu erkennen und...

Mit FaceDetectionAndLandmark ist es nun moeglich ein Gesicht zu erkennen und die Landmarks im Gesicht werden angezeigt

projectmood/ZweiterTest → projectmood/FaceDetectionAndLandmark

@@ -5,6 +5,7 @@ import dlib
 # Set up some required objects
 video_capture = cv2.VideoCapture(0)  # Webcam object
 detector = dlib.get_frontal_face_detector()  # Face detector
+detectors = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
 predictor = dlib.shape_predictor(
     "shape_predictor_68_face_landmarks.dat")  # Landmark identifier. Set the filename to whatever you named the downloaded file
 
@@ -13,6 +14,7 @@ while True:
     gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
     clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
     clahe_image = clahe.apply(gray)
+    faces = detectors.detectMultiScale(gray, 1.3, 5)
 
     detections = detector(clahe_image, 1)  # Detect the faces in the image
 
@@ -22,7 +24,8 @@ while True:
         for i in range(1, 68):  # There are 68 landmark points on each face
             cv2.circle(frame, (shape.part(i).x, shape.part(i).y), 1, (0, 0, 255),
                        thickness=2)  # For each point, draw a red circle with thickness2 on the original frame
-
+            for (x, y, w, h) in faces:
+                cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
     cv2.imshow("image", frame)  # Display the frame
 
     if cv2.waitKey(1) & 0xFF == ord('q'):  # Exit program when the user presses 'q'