"""滑块图像距离计算 """ import randomimport cv2 import numpy as np import requests import ddddocrdef distance_cv(slice_url,bg_url):""":param slice_url: 滑块（缺口）图片地址:param bg_url: 背景图地址:return: distance:rtype:integer"""slice_image = np.asarray(bytearray(requests.get(slice_url).content),dtype=np.uint8)slice_image = cv2.imdecode(slice_image,1)slice_image = cv2.Canny(slice_image,255,255)bg_image = np.asarray(bytearray(requests.get(bg_url).content), dtype=np.uint8)bg_image = cv2.imdecode(bg_image, 1)bg_image = cv2.pyrMeanShiftFiltering(bg_image,5,50)bg_image = cv2.Canny(bg_image, 255, 255)result = cv2.matchTemplate(bg_image,slice_image,cv2.TM_CCOEFF_NORMED)min_val,max_val,min_loc,max_loc = cv2.minMaxLoc(result)return max_loc[0]def distance_orc(bg_url,slice_url):slide = ddddocr.DdddOcr(det=False,ocr=False,show_ad=False)slide_image = requests.get(slice_url).contentbg_image = requests.get(bg_url).contentresult = slide.slide_match(slide_image, bg_image, simple_target=True)# 返回距离return result['target'][0]def distance_puzzle(bg_img_path,puzzle_img_path):"""根据背景图和缺口图，计算滑块距离:param bg_img_path::param puzzle_img_path::return:"""img = cv2.imdecode(np.fromfile(bg_img_path,dtype=np.uint8),cv2.IMREAD_COLOR)tpl = cv2.imdecode(np.fromfile(puzzle_img_path,dtype=np.uint8),cv2.IMREAD_COLOR)img_gry = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)_,img_bw = cv2.threshold(img_gry,127,255,cv2.THRESH_BINARY)tpl = cv2.cvtColor(tpl,cv2.COLOR_BGR2GRAY)for row in range(tpl.shape[0]):for col in range(tpl.shape[1]):if tpl[row,col] == 0:tpl[row,col] = 96lower = np.array([96])upper = np.array([96])mask = cv2.inRange(tpl,lower,upper)tpl[mask == 0] = 0tpl[mask != 0] =255result =cv2.matchTemplate(img_bw,tpl,cv2.TM_CCOEFF_NORMED)_,_,_,max_loc = cv2.minMaxLoc(result)distance = int(max_loc[0] * 0.5833333333333333) + random.randint(0,2)return distance
