Python开发之基于模板匹配的信用卡数字识别功能

 # ！/usr/bin/env python # ―*― coding: utf-8 ―*― # @Time: 2020/1/11 14:57 # @Author: Martin # @File: utils.py # @Software:PyCharm import cv2 def sort_contours(cnts, method='left-to-right'): reverse = False i = 0 if method == 'right-to-left' or method == 'bottom-to-top': reverse = True if method == 'top-to-bottom' or method == 'bottom-to-top': i = 1 boundingboxes = [cv2.boundingRect(c) for c in cnts] (cnts, boundingboxes) = zip(*sorted(zip(cnts, boundingboxes), key=lambda b: b[1][i], reverse=reverse)) return cnts, boundingboxes def resize(image, width=None, height=None, inter=cv2.INTER_AREA): (h, w) = image.shape[:2] if width is None and height is None: return image if width is None: r = height / float(h) dim = (int(w * r), height) else: r = width / float(w) dim = (width, int(h * r)) resized = cv2.resize(image, dim, interpolation=inter) return resized # ！/usr/bin/env python # ―*― coding: utf-8 ―*― # @Time: 2020/1/11 14:57 # @Author: Martin # @File: template_match.py # @Software:PyCharm """ 基于模板匹配的信用卡数字识别 """ import cv2 import utils import numpy as np # 指定信用卡类型 FIRST_NUMBER = { '3' : 'American Express', '4' : 'Visa', '5' : 'MasterCard', '6' : 'Discover Card' } # 绘图显示 def cv_show(name, image): cv2.imshow(name, image) cv2.waitKey(0) cv2.destroyAllWindows() # 读取模板图像 img = cv2.imread('./images/ocr_a_reference.png-600') cv_show('img', img) # 转化成灰度图 ref = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) cv_show('ref', ref) # 转化成二值图像 ref = cv2.threshold(ref, 10, 255, cv2.THRESH_BINARY_INV)[1] cv_show('ref', ref) # 计算轮廓 ref_, refCnts, hierarchy = cv2.findContours(ref.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) cv2.drawContours(img, refCnts, -1, (0, 0, 255), 3) cv_show('img', img) print(np.array(refCnts).shape) # 排序，从左到右，从上到下 refCnts = utils.sort_contours(refCnts, method='left-to-right')[0] digits = {} # 遍历每一个轮廓 for (i, c) in enumerate(refCnts): (x, y , w, h) = cv2.boundingRect(c) roi = ref[y:y+h, x:x+w] roi = cv2.resize(roi, (57, 88)) digits[i] = roi # 初始化卷积核 rectKernel = cv2.getStructuringElement(cv2.MORPH_RECT, (9, 3)) sqKernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5)) # 读取输入图像，预处理 img_path = input("Input the path and image name: ") image_input = cv2.imread(img_path) cv_show('image', image_input) image_input = utils.resize(image_input, width=300) gray = cv2.cvtColor(image_input, cv2.COLOR_BGR2GRAY) cv_show('gray', gray) # 礼帽操作，突出更明亮的区域 tophat = cv2.morphologyEx(gray, cv2.MORPH_TOPHAT, rectKernel) cv_show('tophat', tophat) gradX = cv2.Sobel(tophat, ddepth=cv2.CV_32F, dx=1, dy=0, ksize=-1) gradX = np.absolute(gradX) (minVal, maxVal) = (np.min(gradX), np.max(gradX)) gradX = (255 * ((gradX - minVal) / (maxVal - minVal))) gradX = gradX.astype("uint8") print(np.array(gradX).shape) cv_show('gradX', gradX) # 闭操作 gradX = cv2.morphologyEx(gradX, cv2.MORPH_CLOSE, rectKernel) cv_show('gradX', gradX) thresh = cv2.threshold(gradX, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1] cv_show('thresh', thresh) thresh = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, sqKernel) cv_show('thresh', thresh) # 计算轮廓 thresh_, threshCnts, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) cnts = threshCnts cur_img = image_input.copy() cv2.drawContours(cur_img, cnts, -1, (0, 0, 255), 3) cv_show('img', cur_img) locs = [] # 遍历轮廓 for (i, c) in enumerate(cnts): (x, y, w, h) = cv2.boundingRect(c) ar = w / float(h) if 2.5 </div><p>结果展示</p><p style="text-align: center"></p><div class="gaodaimacode"><pre class="prettyprint linenums"> Credit Card Type: Visa Credit Card #: 4020340002345678