程序基本目的是实现提取图片中的文字。做了一个winfrom界面，接了腾讯云的OCR图片识别。

这里接入文档就不给出了，想看的直接去腾讯云看接入文档即可。

由于想做跨平台的应用。分析了接入文档，并且之前想做一个web界面接口的，但是无奈javascript技术不到家，表单传递时的header头问题迟迟没有解决。

所有就在我的网站里弄了一个接口来计算我的Authorization，计算方法是直接采用腾讯给出的标准文档中的方法。直接把计算结果echo到web上。

而我windows上采用的是C#编程。主要想法就是先使用HTTPREQUEST方法做一个简单的爬虫。具体方法在我之前的博客《C#使用Winfrom编程时的注意事项》有讲过到。

主要还是卡在了header传值的问题。由于Authorization不是标准Header值，需要采用别的方式来进行传递。这是比较需要注意的。

这个地方我主要采用了Content-Type=application/x-www-form-urlencoded,用POST方法把上传文件到腾讯云的API接口，然后接受返回值而已。

接受的时候也要注意，由于收到的信息是JSON码的形式，需要自己下载一个Newtonsoft.Json.dll的文件，并加入解决方案的引用当中。然后命名空间引用

using Newtonsoft.Json;
using Newtonsoft.Json.Linq;

这样就可以直接使用JObject对象来转换string型的json对象。并采用json标准来进行对象的访问。

C# Winfrom的界面就不具体放出，我先给出C#的代码。

Windows下的代码

using Newtonsoft.Json.Linq;
using System;
using System.Collections.Generic;
using System.IO;
using System.Linq;
using System.Net;
using System.Text;
using System.Threading;
using System.Windows.Forms;

namespace PDF转WORD
{

    public partial class Form2 : Form
    {
        private string filename="";
        public Form2()
        {
            InitializeComponent();
            System.Windows.Forms.Control.CheckForIllegalCrossThreadCalls = false;
            this.Text = "图片转PDF";
        }

        private void button1_Click(object sender, EventArgs e)
        {
            OpenFileDialog fileDialog = new OpenFileDialog();
            fileDialog.Multiselect = true;
            fileDialog.Title = "请选择文件";
            fileDialog.Filter = "(*jpg*)|*.jpg*||(*.jpg*)||*.*";
            if (fileDialog.ShowDialog() == DialogResult.OK)
            {
                string file = fileDialog.FileName;
                filename = file;
                label2.Text = filename.ToString();
                MessageBox.Show("选择成功！");
            }
        }

        private void POST_DATA() {
            HttpWebRequest req = (HttpWebRequest)WebRequest.Create(new Uri(@"我的web服务器"));
            req.Method = "POST";
            req.UserAgent = "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:62.0) Gecko/20100101 Firefox/62.0";
            req.ContentType = "application/x-www-form-urlencoded";
            req.Accept = "application/json";
            string result1 = "";

            StringBuilder builder = new StringBuilder();

            byte[] data = Encoding.UTF8.GetBytes(builder.ToString());
            req.ContentLength = data.Length;
            using (Stream reqStream = req.GetRequestStream())
            { reqStream.Write(data, 0, data.Length); reqStream.Close(); }
            HttpWebResponse resp = (HttpWebResponse)req.GetResponse();
            Stream stream = resp.GetResponseStream();
            //获取响应内容         
            using (StreamReader reader = new StreamReader(stream, Encoding.UTF8))
            { result1 = reader.ReadToEnd(); }

            HttpWebRequest webReq = (HttpWebRequest)WebRequest.Create(new Uri("http://recognition.image.myqcloud.com/ocr/general"));
            Stream memStream = new MemoryStream();
            webReq.Method = "POST";
            string boundary = "--------------" + DateTime.Now.Ticks.ToString("x");// 边界符 
            webReq.ContentType = "multipart/form-data; boundary=" + boundary;
            byte[] enter = Encoding.ASCII.GetBytes("\r\n");  //换行
            memStream.Write(enter, 0, enter.Length);
            Dictionary<string, string> dic = new Dictionary<string, string>()
            {
                {"appid","你的APPID"}
            };
            //写入文本字段
            string inputPartHeaderFormat = "--" + boundary + "\r\n" + "Content-Disposition:form-data;name=\"{0}\";" + "\r\n\r\n{1}\r\n";
            foreach (var kv in dic)
            {
                string inputPartHeader = string.Format(inputPartHeaderFormat, kv.Key, kv.Value);
                var inputPartHeaderBytes = Encoding.ASCII.GetBytes(inputPartHeader);
                memStream.Write(inputPartHeaderBytes, 0, inputPartHeaderBytes.Length);
            }

            var fileStream = new FileStream(filename, FileMode.Open, FileAccess.Read);
            // 写入文件 
            string imagePartHeader = "--" + boundary + "\r\n" +
                                     "Content-Disposition: form-data; name=\"{0}\"; filename=\"{1}\"\r\n" +
                                     "Content-Type: image/jpeg\r\n\r\n";
            var header = string.Format(imagePartHeader, "image", "1.jpg");
            var headerbytes = Encoding.UTF8.GetBytes(header);
            memStream.Write(headerbytes, 0, headerbytes.Length);
            var buffer = new byte[1024];
            int bytesRead;
            while ((bytesRead = fileStream.Read(buffer, 0, buffer.Length)) != 0)
            {
                memStream.Write(buffer, 0, bytesRead);
            }
            byte[] endBoundary = Encoding.ASCII.GetBytes("xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" + "\r\n" + boundary + "--\r\n");
            memStream.Write(endBoundary, 0, endBoundary.Length);
            webReq.ContentLength = memStream.Length;
            webReq.Headers.Add(HttpRequestHeader.Authorization, result1);
            webReq.Host = "recognition.image.myqcloud.com";
            var requestStream = webReq.GetRequestStream();
            memStream.Position = 0;
            memStream.CopyTo(requestStream);
            HttpWebResponse response = (HttpWebResponse)webReq.GetResponse();
            StreamReader sr = new StreamReader(response.GetResponseStream(), Encoding.UTF8);
            var ret = sr.ReadToEnd();
            sr.Close();
            response.Close();
            requestStream.Close();
            memStream.Close();
            JObject content_info = JObject.Parse(ret);
//这里就是主要的对返回的json的处理了
            for (int i = 0; i < content_info["data"]["items"].Count(); i++)
            {
                try
                {
                    richTextBox1.AppendText(content_info["data"]["items"][i]["itemstring"].ToString());
                }
                catch (Exception e)
                {
                    MessageBox.Show(e.ToString());
                }
            }
        }

        private void button2_Click(object sender, EventArgs e)
        {
            if(filename!="")
            {
                Thread th1 = new Thread(POST_DATA);
                th1.IsBackground = true;
                th1.Start();
            }
            else {
                MessageBox.Show("请先选择图片。", "提示！");
            }
        }

        private void button3_Click(object sender, EventArgs e)
        {
            filename = "";
            if (filename == "")
            {
                label2.Text = "暂未选择图片";
                MessageBox.Show("清空成功！");
            }
        }

        private void button4_Click(object sender, EventArgs e)
        {
            richTextBox1.Clear();
        }
    }
}

以上就是主要界面的代码。而主界面的代码就不再放出，我先给出windows下的实验效果。（照片带水印）

Windows下的效果

LINUX上的代码实现（ubuntu）

用python实现的，所以代码比较简洁。主要用到的函数库为requests

没什么需要注意的==毕竟python比较简单。直接安装官方给的文档设置image和header就可以了。话不多说直接上代码QWQ

#!/usr/bin/env python
#encoding=utf-8
import re
import sys,os
import requests
def GetAuthorization():
  html = requests.post(url="我的WEB服务器地址")
  html = html.text
  info = html.split("\n")
  return info[1].replace("\n","")

Authorization = str(GetAuthorization().replace("\n","").replace("\r",""))
def createRequest(filepath):
  global Authorization
  headers = {
    'host':'recognition.image.myqcloud.com',
    'Authorization':Authorization
  }
  files = {
    'appid':(None,'你的appid'),
    'image':('1.jpg',open(filepath,'rb'),'image/jpeg')
  }

  r = requests.post("http://recognition.image.myqcloud.com/ocr/general", files=files,headers=headers) 
  responseinfo = r.content
  data = responseinfo.decode('utf-8')
  print data  
  r_index = r'itemstring":"(.*?)"'
  result = re.findall(r_index, data)
  for i in result:
      print(i)

def main():
  createRequest(sys.argv[1])


if __name__ == '__main__':
  main()

程序的第一个参数就是你要上传文件的绝对路径==就是一个普通脚本，没有什么很大的技术难度。

我要处理的照片还是上面那张，现在给出扫描结果。

LINUX下的效果图