leitor_contador_facila.py

import cv2
import mediapipe as mp


face_detection = mp.solutions.face_detection.FaceDetection(0.6)

img = cv2.imread ("texte1.jpg")




def detector(frame):

    count = 0
    height, width, channel = frame.shape

    #  BGR para RGB colorspace

    imgRGB = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    
    result = face_detection.process(imgRGB)

    # print(result.detections)

    try:
        for count, detection in enumerate(result.detections):

            # print(detection)

        

            score = detection.score
            box = detection.location_data.relative_bounding_box

            # print(score)
            # print(box)

            x, y, w, h = int(box.xmin*width), int(box.ymin * height), int(box.width*width), int(box.height*height)
            
            score = str(round(score[0]*100, 2))

            print(x, y, w, h)

            
            cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 0, 255), 2)
            cv2.rectangle(frame, (x, y), (x+w, y-25), (0, 0, 255), -1)

            cv2.putText(frame, score, (x, y), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 2)

        count += 1
        print("Found ",count, "Faces!")

        
    
    except:
        pass

    return count, frame

#imagem
count, output = detector(img)

cv2.putText(output, "Number of Faces: "+str(count),(10, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2 )
imS = cv2.resize(img, (960, 540)) 
cv2.imshow("output", imS)
cv2.waitKey(0)


#video
# cap = cv2.VideoCapture('video.mkv')
# while True:
#     _, frame = cap.read()
#     count, output = detector(frame)
#     cv2.putText(output, "Number of Faces: "+str(count),(10, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2 )
#     cv2.imshow("frame", output)
#     if cv2.waitKey(15) == ord('q'):
#         break

# cap.release()
# cv2.destroyAllWindows()