高考答题卡怎么被识别？基于OpenCV答题卡识别模拟ARM+FPGA异构
本篇测评由优秀测评者“筑梦者与梦同行”提供。01.前言MYD-JX8MMA7SDK发布说明根据下图文件内容可以知道myir-image-full系统支持的功能，其支持OpenCV，也就不用在格外安装相关驱动包等，省了很多事情。https://www.myir.cn/public/uploads/images/20230609/3e1fb481306c7b5006958ef6daef2d6b.png
02.MYD-JX8MMA7软件评估指南本文介绍了Python的基本操作，在文档中10.1开发语言支持。
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03.历程路径/usr/share/OpenCV/samples//usr/share/opencv4/samples/python/
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文件目录中有一些python程序。
04.图像识别开发1.使用参考图片
https://www.myir.cn/public/uploads/images/20230609/7c3f4d8208a9ac953b746ca9ce7351dd.png
上面的图片是模拟的答题卡，与实际答题卡理论相同，具体细节可能需要变动。正常的答题卡采集的数据较多。2.源代码1）源代码截图
https://www.myir.cn/public/uploads/images/20230609/a4735dc33aa6a62a8813837ed07a3a73.png
2）源代码粘贴#!/usr/bin/env python3
"""
Created on Thu Sep 30 07:53:41 2021
"""
Python 2/3 compatibilityfrom future import print_function
import numpy as np
import cv2
img = cv2.imread('b.jpg')
cv2.imshow("orginal",img)
gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
cv2.imshow("gray",gray)
gaussian = cv2.GaussianBlur(gray, (5, 5), 0)
cv2.imshow("gaussian",gaussian)
edged=cv2.Canny(gaussian,50,200)
cv2.imshow("edged",edged)
cts, hierarchy = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
cv2.drawContours(img, cts, -1, (0,0,255), 3)
cv2.imshow("img",img)
cv2.waitKey()
cv2.destroyAllWindows()
3.代码图片上传
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4.实际运行效果
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