# -*- coding: utf-8 -*-
__author__ = "小柒"
__blog__ = "https://blog.52itstyle.vip/"
import cv2
import os


# 保存好的視頻檢測人臉并截圖
def CatchPICFromVideo(window_name, camera_idx, catch_pic_num, path_name):
 cv2.namedWindow(window_name)

 # 視頻來源
 cap = cv2.VideoCapture(camera_idx)

 # 告訴OpenCV使用人臉識(shí)別分類器
 classfier = cv2.CascadeClassifier(os.getcwd()+"\\haarcascade\\haarcascade_frontalface_alt.xml")

 # 識(shí)別出人臉后要畫的邊框的顏色，RGB格式, color是一個(gè)不可增刪的數(shù)組
 color = (0, 255, 0)

 num = 0
 while cap.isOpened():
 ok, frame = cap.read() # 讀取一幀數(shù)據(jù)
 if not ok:
  break

 grey = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # 將當(dāng)前楨圖像轉(zhuǎn)換成灰度圖像

 # 人臉檢測，1.2和2分別為圖片縮放比例和需要檢測的有效點(diǎn)數(shù)
 faceRects = classfier.detectMultiScale(grey, scaleFactor=1.2, minNeighbors=3, minSize=(32, 32))
 if len(faceRects) > 0: # 大于0則檢測到人臉
  for faceRect in faceRects: # 單獨(dú)框出每一張人臉
  x, y, w, h = faceRect

  # 將當(dāng)前幀保存為圖片
  img_name = "%s/%d.jpg" % (path_name, num)
  # print(img_name)
  image = frame[y - 10: y + h + 10, x - 10: x + w + 10]
  cv2.imwrite(img_name, image, [int(cv2.IMWRITE_PNG_COMPRESSION), 9])

  num += 1
  if num > (catch_pic_num): # 如果超過指定最大保存數(shù)量退出循環(huán)
   break

  # 畫出矩形框
  cv2.rectangle(frame, (x - 10, y - 10), (x + w + 10, y + h + 10), color, 2)

  # 顯示當(dāng)前捕捉到了多少人臉圖片了，這樣站在那里被拍攝時(shí)心里有個(gè)數(shù)，不用兩眼一抹黑傻等著
  font = cv2.FONT_HERSHEY_SIMPLEX
  cv2.putText(frame, 'num:%d/100' % (num), (x + 30, y + 30), font, 1, (255, 0, 255), 4)

  # 超過指定最大保存數(shù)量結(jié)束程序
 if num > (catch_pic_num): break

 # 顯示圖像
 cv2.imshow(window_name, frame)
 c = cv2.waitKey(10)
 if c & 0xFF == ord('q'):
  break

  # 釋放攝像頭并銷毀所有窗口
 cap.release()
 cv2.destroyAllWindows()


if __name__ == '__main__':
 # 連續(xù)截100張圖像
 CatchPICFromVideo("get face", os.getcwd()+"\\video\\kelake.mp4", 100, "E:\\VideoCapture")

# 如果獲取攝像頭，參數(shù)修改為 0 即可
cap = cv2.VideoCapture(0)