opencv 識別微信登錄驗證滑動塊位置

# 讀取截圖
screenshot = cv2.imread('screenshot.jpg')
# 篩選出符合顏色區(qū)間的區(qū)域
inRange = cv2.inRange(screenshot, np.array([90, 90, 90]), np.array([115, 115, 115]))
# 從圖中找出所有的輪廓
_, cnts, _ = cv2.findContours(inRange.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# 對所有輪廓做排序，排序依據(jù)是每個輪廓包含的點的數(shù)量
cnts.sort(key=len, reverse=True)
# 取前兩個輪廓(有些圖片目標(biāo)位置不一定是第一個輪廓)
for cnt in cnts[0: 2]:
 xSum = 0
 xCounter = 0
 for position in cnt:
 xCounter += 1
 xSum += position[0][0]
 # 算出所有點的X坐標(biāo)平均值，并在此基礎(chǔ)上做一個60像素的偏移，這個偏移可以根據(jù)自己手機(jī)進(jìn)行調(diào)整
 x = int(xSum / xCounter - 60)
 # 在截圖上畫一條紅線，表示識別的x坐標(biāo)位置
 cv2.line(screenshot, (x, 0), (x, 500), (0, 0, 255), 5)
cv2.imshow("screenshot", screenshot)
cv2.waitKey(0)

# 讀取滑塊圖片，并給其加上相同的灰黑色透明前景色，再進(jìn)行灰化
block = cv2.imread('block.jpg')
blockCopy = block.copy()
w, h = block.shape[:-1]
cv2.rectangle(blockCopy, (0, 0), (w, h), (47, 47, 47), -1)
cv2.addWeighted(blockCopy, 0.7, block, 0.3, 0, block)
block = cv2.cvtColor(block, cv2.COLOR_RGB2GRAY)
# 讀取驗證碼圖片，并灰化
captcha = cv2.imread('captcha.jpg')
captchaGray = cv2.cvtColor(captcha, cv2.COLOR_RGB2GRAY)
# 尋找captcha中匹配block的位置
res = cv2.matchTemplate(captchaGray, block, cv2.TM_SQDIFF)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
# 在最符合的畫一個矩形
cv2.rectangle(captcha, min_loc, (min_loc[0] + w, min_loc[1] + h), (0, 0, 255), -1)
cv2.imshow('block', block)
cv2.imshow("captcha", captcha)
cv2.waitKey(0);