intégration de la détéction audio à l'interface

code_autre/Interface_Lounes/determinationGenre.py

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+import cv2
+import mediapipe as mp
+
+mp_drawing = mp.solutions.drawing_utils
+mp_face_mesh = mp.solutions.face_mesh
+
+drawing_spec = mp_drawing.DrawingSpec(thickness=1, circle_radius=1)
+cap = cv2.VideoCapture(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.")
+            continue
+        # Initialize the face mesh model
+        face_mesh = mp_face_mesh.FaceMesh(static_image_mode=False, max_num_faces=1, min_detection_confidence=0.5)
+
+        # Load the input image
+        # lecture de la vidéo
+        ret, frame = cap.read()
+        # conversion de l'image en RGB    
+        image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        # Process the image and extract the landmarks
+        results = face_mesh.process(image)
+        if results.multi_face_landmarks:
+            landmarks = results.multi_face_landmarks[0]
+
+            # Define the landmark indices for the corners of the eyes and the tip of the nose
+            left_eye = [33, 133, 246, 161, 160, 159, 158, 157, 173, 133]
+            right_eye = [362, 263, 373, 380, 381, 382, 384, 385, 386, 362]
+            nose_tip = 4
+
+            # Calculate the distance between the eyes and the nose tip
+            left_eye_x = landmarks.landmark[left_eye[0]].x * image.shape[1]
+            right_eye_x = landmarks.landmark[right_eye[0]].x * image.shape[1]
+            nose_x = landmarks.landmark[nose_tip].x * image.shape[1]
+            eye_distance = abs(left_eye_x - right_eye_x)
+            nose_distance = abs(nose_x - (left_eye_x + right_eye_x) / 2)
+
+            # Determine the gender based on the eye and nose distances
+            if eye_distance > 1.5 * nose_distance:
+                gender = "Female"
+            else:
+                gender = "Male"
+
+            # Draw the landmarks on the image
+            cv2.putText(image, gender, (10, 50),cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
+        # affichage de la vidéo
+        cv2.imshow('Video', cv2.cvtColor(image, cv2.COLOR_RGB2BGR))
+        if cv2.waitKey(10) & 0xFF == ord('q'):
+            break
+
+# libération de la caméra et des ressources
+cap.release()
+cv2.destroyAllWindows()