faceMeshModule.py

import cv2
import mediapipe as mp
import math
import numpy as np

class faceMeshDetection:
    def __init__(self, staticMode=False, maxFaces=1, minDetectionCon=0.5, minTrackCon=0.5):
        self.staticMode = staticMode
        self.maxFaces = maxFaces
        self.minDetectionCon = minDetectionCon
        self.minTrackCon = minTrackCon

        self.mpDraw = mp.solutions.drawing_utils
        self.mpFaceMesh = mp.solutions.face_mesh
        self.faceMesh = self.mpFaceMesh.FaceMesh(static_image_mode=self.staticMode,
                                                 max_num_faces=self.maxFaces,
                                                 min_detection_confidence=self.minDetectionCon,
                                                 min_tracking_confidence=self.minTrackCon)
        self.drawSpec = self.mpDraw.DrawingSpec(thickness=1, circle_radius=2)

    def findFaceMesh(self, img, draw=True):
        imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        results = self.faceMesh.process(imgRGB)
        faces = []
        for faceLms in results.multi_face_landmarks:
            if draw:
                self.mpDraw.draw_landmarks(img, faceLms, self.mpFaceMesh.FACEMESH_CONTOURS,
                                        self.drawSpec, self.drawSpec)
            face = np.array([[int(lm.x * img.shape[1]), int(lm.y * img.shape[0])] for lm in faceLms.landmark])
            faces.append(face)
        return img, faces


    @staticmethod
    def findDistance(p1, p2, img=None):
        x1, y1 = p1
        x2, y2 = p2
        cx, cy = (x1 + x2) // 2, (y1 + y2) // 2
        length = np.hypot(x2 - x1, y2 - y1)
        info = (x1, y1, x2, y2, cx, cy)
        if img is not None:
            cv2.circle(img, (x1, y1), 15, (255, 0, 255), cv2.FILLED)
            cv2.circle(img, (x2, y2), 15, (255, 0, 255), cv2.FILLED)
            cv2.line(img, (x1, y1), (x2, y2), (255, 0, 255), 3)
            cv2.circle(img, (cx, cy), 15, (255, 0, 255), cv2.FILLED)
            return length, info, img
        else:
            return length, info


def main():
    cap = cv2.VideoCapture(0)
    detector = FaceMeshDetector(maxFaces=2)
    while True:
        success, img = cap.read()
        img, faces = detector.findFaceMesh(img)
        if faces:
            print(faces[0])
        cv2.imshow("Image", img)
        cv2.waitKey(1)


if __name__ == "__main__":
    main()