bg.jpg

tb.png

結(jié)果.png

以上是需要是別的圖片缺口，來(lái)自某東登錄。
opencv是計(jì)算機(jī)視覺(jué)。

一、cv函數(shù)

1、imread：讀取圖片
?imread(image_path, flag):
? ? images_path:圖片路徑，找不到不報(bào)錯(cuò)
?? flag:
????1/cv2.IMREAD_COLOR:彩色圖片,圖片透明性會(huì)被忽略,默認(rèn)參數(shù)
????0/cv2.IMREAD_GRAYSCALE:灰色圖片
????-1/cv2.IMREAD_UNCHANGED:包括其alpha通道
2、imwrite
?imwrite(img_path_name,img)
?? img_path_name:保存的文件名
??img：文件對(duì)象
3、cvtColor
??cvtColor(img,code)
?img: 圖像對(duì)象
?? code：
??? cv2.COLOR_RGB2GRAY: RGB轉(zhuǎn)換到灰度模式
???cv2.COLOR_RGB2HSV： RGB轉(zhuǎn)換到HSV模式（hue,saturation,Value）
4、matchTemplate
?matchTemplate(img_path, bg_path, cv2.TM_CCOEFF_NORMED)
??img_path:對(duì)比圖片
??bg_path：背景圖片
??cv2.TM_CCOEFF_NORMED

以下源碼

# encoding=utf8

import cv2
import numpy as np
def show(name):
    cv2.imshow('Show', name)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

def main():
    otemp = './images/tb.png'
    oblk = './images/bg.jpg'
    target = cv2.imread(otemp, 0)
    template = cv2.imread(oblk, 0) # 讀取到兩個(gè)圖片，進(jìn)行灰值化處理
    w, h = target.shape[::-1]
    print(w, h)
    temp = './images/temp.jpg'
    targ = './images/targ.jpg'
    cv2.imwrite(temp, template)
    cv2.imwrite(targ, target) # 處理后進(jìn)行保存
    target = cv2.imread(targ)
    target = cv2.cvtColor(target, cv2.COLOR_BGR2GRAY) # 轉(zhuǎn)化到灰度
    target = abs(255 - target)  # 返回絕對(duì)值
    cv2.imwrite(targ, target)  # 重新寫(xiě)入
    target = cv2.imread(targ)
    template = cv2.imread(temp)
    result = cv2.matchTemplate(target, template, cv2.TM_CCOEFF_NORMED) #進(jìn)行匹配
    x, y = np.unravel_index(result.argmax(), result.shape) # 通過(guò)np轉(zhuǎn)化為數(shù)值，就是坐標(biāo)
    # 展示圈出來(lái)的區(qū)域
    cv2.rectangle(template, (y, x), (y + w, x + h), (7, 249, 151), 2)
    show(template)
    return y, x

if __name__ == '__main__':
    main()

優(yōu)化代碼

import cv2
import numpy as np


def from_file_get_distanct(hx, bg):
    '''
    根據(jù)文件進(jìn)行識(shí)別
    :param hx: 滑塊圖片的文件路徑
    :param bg: 背景圖片的文件路徑
    :return:
    '''
    target = cv2.imread(hx)
    template = cv2.imread(bg, 0)  # 讀取到兩個(gè)圖片，進(jìn)行灰值化處理
    target = cv2.cvtColor(target, cv2.COLOR_BGR2GRAY)  # 轉(zhuǎn)化到灰度
    target = abs(255 - target)  # 返回絕對(duì)值
    target = cv2.cvtColor(target, cv2.COLOR_GRAY2RGB)  # 單通道轉(zhuǎn)3通道
    template = cv2.cvtColor(template, cv2.COLOR_GRAY2RGB)
    result = cv2.matchTemplate(target, template, cv2.TM_CCOEFF_NORMED)  # 進(jìn)行匹配
    x, y = np.unravel_index(result.argmax(), result.shape)  # 通過(guò)np轉(zhuǎn)化為數(shù)值，就是坐標(biāo)
    return y, x


def from_buffer_get_distanct(hx, bg):
    '''
    根據(jù)二進(jìn)制進(jìn)行識(shí)別
    :param hx: 滑塊圖片的二進(jìn)制
    :param bg: 背景圖片的二進(jìn)制
    :return:
    '''
    target = cv2.imdecode(np.frombuffer(hx, np.uint8), cv2.IMREAD_COLOR)
    template = cv2.imdecode(np.frombuffer(bg, np.uint8), cv2.IMREAD_COLOR) if type(bg) == bytes else cv2.cvtColor(
        np.asarray(bg), cv2.COLOR_RGB2BGR)  # 如果是PIL.images就換讀取方式
    target = cv2.cvtColor(target, cv2.COLOR_BGR2GRAY)  # 轉(zhuǎn)化到灰度
    target = abs(255 - target)  # 返回絕對(duì)值
    target = cv2.cvtColor(target, cv2.COLOR_GRAY2RGB)  # 單通道轉(zhuǎn)3通道
    result = cv2.matchTemplate(target, template, cv2.TM_CCOEFF_NORMED)  # 進(jìn)行匹配
    x, y = np.unravel_index(result.argmax(), result.shape)  # 通過(guò)np轉(zhuǎn)化為數(shù)值，就是坐標(biāo)
    return y, x