tongue detection, recognisation

tongue.xamta.in.py

import cv2
import dlib

# Load the pre-trained facial landmark predictor from dlib
predictor_path = "shape_predictor_68_face_landmarks.dat"
predictor = dlib.shape_predictor(predictor_path)

# Load the pre-trained face detector from dlib
face_detector = dlib.get_frontal_face_detector()

# Function to extract facial landmarks, including the tongue region
def get_facial_landmarks(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    faces = face_detector(gray)

    if len(faces) == 0:
        return None

    face = faces[0]
    landmarks = predictor(gray, face)

    # Extract landmarks for the mouth region (including the tongue)
    landmarks_list = []
    for i in range(48, 68):
        landmarks_list.append((landmarks.part(i).x, landmarks.part(i).y))

    return landmarks_list

# Example usage
if __name__ == "__main__":
    # Read the input image
    image_path = "path/to/your/image.jpg"
    image = cv2.imread(image_path)

    # Get facial landmarks (including tongue region)
    facial_landmarks = get_facial_landmarks(image)

    if facial_landmarks:
        # Draw facial landmarks on the image
        for (x, y) in facial_landmarks:
            cv2.circle(image, (x, y), 1, (0, 0, 255), -1)

        # Display the image with facial landmarks
        cv2.imshow("Tongue Recognition", image)
        cv2.waitKey(0)
        cv2.destroyAllWindows()
    else:
        print("No face detected in the image.")