openCV抓图片

import numpy as np
import cv2
from PIL import ImageGrab
from demo import get_XY, classify_hist_with_split
import time

cap = cv2.VideoCapture(0)  # 开启摄像头


def find_picture(target, template):
    theight, twidth = template.shape[:2]
    result = cv2.matchTemplate(target, template, cv2.TM_SQDIFF_NORMED)
    cv2.normalize(result, result, 0, 1, cv2.NORM_MINMAX, -1)
    min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
    cv2.rectangle(target, min_loc, (min_loc[0] + twidth, min_loc[1] + theight), (0, 0, 225), 2)
    x = min_loc[0]
    y = min_loc[1]

    return x, y


def get_xy(A, base='image.jpg'):
    """获取A在B的坐标, 反返回A的高和宽"""
    target = cv2.imread(A)
    w, h,  = target.shape[0], target.shape[1]  # 图片的高宽
    if base == 'image.jpg':
        template = cv2.imread(base)
    else:
        template = base
    x, y = find_picture(target, template)
    print(A, "的坐标", x, y, h, w)
    return x, y, w, h


def get_pic_from_pic(x, y, w, h, target):
    region = target[y:y + h, x:x + w]
    return region


if __name__ == '__main__':
    # x, y, h, w = get_xy("yanjing.jpg", "image.jpg")
    #
    # human_box = [x, y, w+x, h+y]

    while True:
        screen = ImageGrab.grab(bbox=(0, 0, 800, 600))
        print(screen)
        frame = cv2.cvtColor(np.array(screen), cv2.COLOR_RGB2BGR)
        # cv2.imshow("threshold", frame)  # 显示图像
        x, y, h, w = get_xy("yanjing.jpg", frame)
        human_box = [x, y, x + w, h + y]
        # cv2.waitKey(25)
        # img = cv2.imread(image_path)
        # img = cv2.imread("image.jpg")
        cv2.rectangle(frame, (human_box[0], human_box[1]), (human_box[2], human_box[3]), (255, 255, 0), 3)  #

        cv2.imshow("output_path", frame)
        cv2.waitKey(25)