Supprimer 'mediapipe.py/test3.py'

mediapipe.py/test3.py

@@ -1,92 +0,0 @@
-import cv2
-import mediapipe as mp
-
-mp_drawing = mp.solutions.drawing_utils
-mp_drawing_styles = mp.solutions.drawing_styles
-mp_face_mesh = mp.solutions.face_mesh
-
-drawing_spec = mp_drawing.DrawingSpec(thickness=1, circle_radius=1)
-cap = cv2.VideoCapture('X:/video.mp4')
-
-R = 0
-G = 0
-B = 0
-red = green = blue = 0
-n = 0
-i = 0
-
-with mp_face_mesh.FaceMesh(
-    max_num_faces=1,
-    refine_landmarks=True,
-    min_detection_confidence=0.5,
-    min_tracking_confidence=0.5) as face_mesh:
-  while cap.isOpened():
-    success, image = cap.read()
-    if not success:
-      print("Ignoring empty camera frame.")
-      # If loading a video, use 'break' instead of 'continue'.
-      continue
-    i += 1
-    # To improve performance, optionally mark the image as not writeable to
-    # pass by reference.
-    image.flags.writeable = False
-    img = cv2.resize(image, (640, 480))
-    image = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-    results = face_mesh.process(image)
-
-    # Draw the face mesh annotations on the image.
-    image.flags.writeable = False
-    image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
-    if results.multi_face_landmarks:
-        for face_landmarks in results.multi_face_landmarks:
-            shape = image.shape
-            for landmark in face_landmarks.landmark:
-                n += 1
-                x = landmark.x
-                y = landmark.y
-                relative_x = int(x * shape[1])
-                relative_y = int(y * shape[0])
-                #cv2.circle()
-
-                if relative_x >= shape[0]:
-                    relative_x = shape[0]-1
-                if relative_y >= shape[1]:
-                    relative_y = shape[1]-1
-                B, G, R = img[relative_x, relative_y]
-                #cv2.circle(image, [relative_x, relative_y], 3, [int(B), int(G), int(R)], 3)
-                red += R
-                blue += B
-                green += G
-            color = [int(blue/n), int(green/n), int(red/n)]
-            print(color)
-            red = green = blue = n = 0
-            #cv2.rectangle(image, [400, 450], [450, 450], [255,255,255], 10)
-            #color_hex = '#'+str(hex(color[2])[2:])+str(hex(color[1])[2:])+str(hex(color[0])[2:])
-            #cv2.putText(img,str(i), [400,450], cv2.FONT_HERSHEY_PLAIN, 1, color, 2)
-            #cv2.text(image, [600, 400], )
-        mp_drawing.draw_landmarks(
-                image=image,
-                landmark_list=face_landmarks,
-                connections=mp_face_mesh.FACEMESH_TESSELATION,
-                landmark_drawing_spec=None,
-                connection_drawing_spec=mp_drawing_styles
-                .get_default_face_mesh_tesselation_style())
-        '''mp_drawing.draw_landmarks(
-            image=image,
-            landmark_list=face_landmarks,
-            connections=mp_face_mesh.FACEMESH_CONTOURS,
-            landmark_drawing_spec=None,
-            connection_drawing_spec=mp_drawing_styles
-            .get_default_face_mesh_contours_style())
-        mp_drawing.draw_landmarks(
-            image=image,
-            landmark_list=face_landmarks,
-            connections=mp_face_mesh.FACEMESH_IRISES,
-            landmark_drawing_spec=None,
-            connection_drawing_spec=mp_drawing_styles
-            .get_default_face_mesh_iris_connections_style())'''
-    # Flip the image horizontally for a selfie-view display.
-    cv2.imshow('MediaPipe Face Mesh', cv2.flip(image, 1))
-    if cv2.waitKey(5) & 0xFF == 27:
-      break
-cap.release()