import cv2

img = cv2.imread('jack.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faceCascade = cv2.CascadeClassifier('face_detect.html')
faceRect = faceCascade.detectMultiScale(gray, 1.1, 3)
print(len(faceRect))

for (x,y,w,h) in faceRect:
    cv2.rectangle(img, (x,y), (x+w, y+h), (0,255,0), 2)

cv2.imshow('img',img)
cv2.waitKey(0)

import cv2
import mediapipe as mp
import time

cap = cv2.VideoCapture('VIDEO/1.mp4')
pTime = 0

mpFaceDetection = mp.solutions.face_detection
mpDraw = mp.solutions.drawing_utils
faceDetection = mpFaceDetection.FaceDetection(0.75)

while True:
    success, img = cap.read()
    imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    results = faceDetection.process(imgRGB)
    print(results)

    if results.detections:
        for id, detection in enumerate(results.detections):
            # mpDraw.draw_detection(img, detection)
            # print(id, detection)
            # print(detection.score)
            # print(detection.location_data.relative_bounding_box)
            bboxC = detection.location_data.relative_bounding_box
            ih, iw, ic = img.shape
            bbox = int(bboxC.xmin*iw), int(bboxC.ymin*ih), \
                   int(bboxC.width * iw), int(bboxC.height * ih)
            cv2.rectangle(img, bbox, (255, 0, 255), 3)
            cv2.putText(img, f'{int(detection.score[0] * 100)}%', (bbox[0], bbox[1] - 20), cv2.FONT_HERSHEY_PLAIN, 2,
                        (255, 0, 255), 2)

    img = cv2.resize(img, (0, 0), fx=0.7, fy=0.7)
    cTime = time.time()
    fps = 1 / (cTime - pTime)
    pTime = cTime
    cv2.putText(img, f'FPS: {int(fps)}', (20, 70), cv2.FONT_HERSHEY_PLAIN, 1, (0, 255, 0), 2)
    cv2.imshow('img', img)

    cv2.waitKey(1)

import cv2
import mediapipe as mp
import time

class FaceDetector():
    def __init__(self, minDetectionCon=0.5):
        self.minDetectionCon = minDetectionCon
        self.mpFaceDetection = mp.solutions.face_detection
        self.mpDraw = mp.solutions.drawing_utils
        self.faceDetection = self.mpFaceDetection.FaceDetection(0.75)

    def findFaces(self, img, draw=True):
        imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        self.results = self.faceDetection.process(imgRGB)
        # print(self.results)
        bboxs = []

        if self.results.detections:
            for id, detection in enumerate(self.results.detections):
                bboxC = detection.location_data.relative_bounding_box
                ih, iw, ic = img.shape
                bbox = int(bboxC.xmin*iw), int(bboxC.ymin*ih), \
                       int(bboxC.width * iw), int(bboxC.height * ih)
                bboxs.append([id, bbox, detection.score])
                if draw:
                    img = self.fancyDraw(img, bbox)

                    cv2.putText(img, f'{int(detection.score[0] * 100)}%', (bbox[0], bbox[1] - 20), cv2.FONT_HERSHEY_PLAIN, 2,
                            (255, 0, 255), 2)
        return img, bboxs
    def fancyDraw(self, img, bbox, l = 30, t = 5, rt=1):
        x ,y, w, h = bbox
        x1, y1 = x + w, y + h
        cv2.rectangle(img, bbox, (255, 0, 255), rt)
        #top left x,y
        cv2.line(img, (x, y), (x + l, y), (255, 0, 255), t)
        cv2.line(img, (x, y), (x, y + l), (255, 0, 255), t)
        # top right x1,y
        cv2.line(img, (x1, y), (x1 - l, y), (255, 0, 255), t)
        cv2.line(img, (x1, y), (x1, y + l), (255, 0, 255), t)
        # top bottom left x,y1
        cv2.line(img, (x, y1), (x + l, y1), (255, 0, 255), t)
        cv2.line(img, (x, y1), (x, y1 - l), (255, 0, 255), t)
        # top bottom right x1,y
        cv2.line(img, (x1, y1), (x1 - l, y1), (255, 0, 255), t)
        cv2.line(img, (x1, y1), (x1, y1 - l), (255, 0, 255), t)
        return img


def main():
    cap = cv2.VideoCapture('VIDEO/1.mp4')
    pTime = 0
    detector = FaceDetector()

    while True:
        success, img = cap.read()
        img, bboxs = detector.findFaces(img)
        print(bboxs)

        cTime = time.time()
        fps = 1 / (cTime - pTime)
        pTime = cTime
        cv2.putText(img, f'FPS: {int(fps)}', (20, 70), cv2.FONT_HERSHEY_PLAIN, 1, (0, 255, 0), 2)
        img = cv2.resize(img, (0, 0), fx=0.7, fy=0.7)
        cv2.imshow('img', img)

        cv2.waitKey(1)

if __name__ == '__main__':
    main()