Landmark Wajah Dengan Library Mediapipe

 Berikut program membuat landmark wajah menggunakan Python dan library mediapipe (https://mediapipe.dev) yang dikembangkan oleh team Google.

Sementara ini library mediapipe hanya didukung engine python versi 3.7, sehingga jika Anda memiliki python versi di atasnya kemungkinan besar instalasi akan gagal.

Kebutuhan perangkat lunak:

• Editor python menggunakan PyCharm
• Library Numpy
• Library OpenCV
• Library Mediapipe

import cv2
import mediapipe as mp
import time


class FaceMeshDetector():

    def __init__(self, staticMode=False, maxFaces=2, 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(self.staticMode, self.maxFaces,
                                                 self.minDetectionCon, self.minTrackCon)
        self.drawSpec = self.mpDraw.DrawingSpec(thickness=1, circle_radius=1)

    def findFaceMesh(self, img, draw=True):
        self.imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        results = self.faceMesh.process(self.imgRGB)
        faces = []
        if results.multi_face_landmarks:
            for faceLms in results.multi_face_landmarks:
                if draw:
                    self.mpDraw.draw_landmarks(img, faceLms, self.mpFaceMesh.FACE_CONNECTIONS,
                                               self.drawSpec, self.drawSpec)
                face = []
                for id, lm in enumerate(faceLms.landmark):
                    ih, iw, ic = img.shape
                    x, y = int(lm.x * iw), int(lm.y * ih)
                    # print(id, x, y)
                    face.append([x, y])
                faces.append(face)
        return img, faces


def main():
    # cap = cv2.VideoCapture("video/6.mp4")
    cap = cv2.VideoCapture(0)
    pTime = 0

    detector = FaceMeshDetector()

    while True:
        success, img = cap.read()

        img, faces = detector.findFaceMesh(img, True)
        if len(faces) != 0:
            print(faces[0])

        cTime = time.time()
        fps = 1 / (cTime - pTime)
        pTime = cTime
        cv2.putText(img, f'FPS: {int(fps)}', (20, 70), cv2.FONT_HERSHEY_PLAIN,
                    3, (0, 255, 0), 3)

        cv2.imshow("Image", img)
        cv2.waitKey(1)


if __name__ == "__main__":
    main()