Haarcascade und Landmarks zu Main eingefügt

projectmood/main.py

 import cv2
 import sys
-import cvhelper
+import dlib
+
+from projectmood import cvhelper
+
 
 def main():
+    # Set up some required objects
+    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
 
     if len(sys.argv) > 1:
         cap = cv2.VideoCapture(str(sys.argv[1]))
@@ -16,6 +24,23 @@ def main():
         # Our operations on the frame come here
         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
+
+        for k, d in enumerate(detections):  # For each detected face
+
+            shape = predictor(clahe_image, d)  # Get coordinates
+            for i in range(1, 68):  # There are 68 landmark points on each face
+                cv2.circle(gray, (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(gray, (x, y), (x + w, y + h), (255, 0, 0), 2)
+                    roi_gray = gray[y:y + h, x:x + w]
+                    roi_color = frame[y:y + h, x:x + w]
+
         cvhelper.createwindow('Grayscale', gray)