/// <summary>
/// 从文件中识别图片中的文字
/// </summary>
/// <param name="path">图片路径</param>
/// <returns></returns>
public static JObject IdentifyImageFile(string path)
{
var image = File.ReadAllBytes(path);
// 调用通用文字识别, 图片参数为本地图片，可能会抛出网络等异常，请使用try/catch捕获
//var result = client.GeneralBasic(image);//基本版
var result = client.Accurate(image);//高精度版 位置
return(result);
}
/// <summary>
/// 圖片辨識
/// </summary>
public static string BaiduOCR(string imagepath) // 百度_圖片辨識
{
var API_KEY = "cohIahxAt7HveHLYSHYK6G5N"; // "FGPi0QpCbZxZxBaN6dvqt87X";
var SECRET_KEY = "e8SAsDIWSK9NPUKviYiPQNlfaVDXQSY5"; // "HunNq6XsLjF3a7aCAuirVaVQO7CKBuwW";
var client = new Baidu.Aip.Ocr.Ocr(API_KEY, SECRET_KEY);
client.Timeout = 60000; // 修改超時時間
var image = File.ReadAllBytes(imagepath);
// 呼叫通用文字識別, 圖片引數為本地圖片，可能會丟擲網路等異常，請使用try/catch捕獲
//使用者向服務請求識別某張圖中的所有文字
//var result = client.GeneralBasic(image); //本地圖圖片
//var result = client.GeneralBasicUrl(url); //網路圖片
//var result = client.General(image); //本地圖片：通用文字識別（含位置資訊版）
//var result = client.GeneralUrl(url); //網路圖片：通用文字識別（含位置資訊版）
//var result = client.GeneralEnhanced(image); //本地圖片：呼叫通用文字識別（含生僻字版）
//var result = client.GeneralEnhancedUrl(url); //網路圖片：呼叫通用文字識別（含生僻字版）
//var result = client.WebImage(image); //本地圖片:使用者向服務請求識別一些背景複雜，特殊字型的文字。
//var result = client.WebImageUrl(url); //網路圖片:使用者向服務請求識別一些背景複雜，特殊字型的文字。
string JsonString = client.Accurate(image).ToString(); //本地圖片：相對於通用文字識別該產品精度更高，但是識別耗時會稍長。
string cut = JsonString.Substring(45, 10); // 擷取jason 文字串中 解析出的圖片文字 這段
string CutResult = Regex.Replace(cut, "[^0-9A-Za-z]", ""); //去除掉符號空白...只留下字母&数字
return(CutResult);
}
public static string getString(Image img)
{
var API_KEY = "FGPi0QpCbZxZxBaN6dvqt87X";
var SECRET_KEY = "HunNq6XsLjF3a7aCAuirVaVQO7CKBuwW";
var client = new Baidu.Aip.Ocr.Ocr(API_KEY, SECRET_KEY);
client.Timeout = 60000; // 修改超时时间
var result = client.Accurate(imageToByteArray(img));
JToken words = null;
if (result.TryGetValue("words_result", out words))
{
if (words.Count() > 0)
{
if (words[0].Contains("words"))
{
return(words[0]["words"].ToString());
}
}
return(null);
}
return(result.ToString());
//var result = client.General(File.ReadAllBytes("c:\\untitled.png"));
return(result["words_result"][0]["words"].ToString());
}
public static void Accurate()
{
var client = new Baidu.Aip.Ocr.Ocr("Api Key", "Secret Key");
var image = File.ReadAllBytes("图片文件路径");
// 高精度识别
var result = client.Accurate(image);
}
public void AccurateDemo()
{
var client = new Baidu.Aip.Ocr.Ocr(API_Key, SECRE_KEY);
client.Timeout = 60000;
var image = File.ReadAllBytes(ImagePath);
OutResult = client.Accurate(image);
}
public static String Accurate(string imgpath)
{
var client = new Baidu.Aip.Ocr.Ocr(API_KEY, SECRET_KEY);
var image = File.ReadAllBytes(imgpath);
// 高精度识别
var result = client.Accurate(image);
return(result.ToString());
}
public static string SECRET_KEY = ConfigurationManager.AppSettings["BAIDU_SECRET_KEY"].ToString(); //"HunNq6XsLjF3a7aCAuirVaVQO7CKBuwW";
/// <summary>
/// https://ai.baidu.com/ai-doc/OCR/Mk3h7y6j8 百度接口文档
/// </summary>
/// <param name="imgpath"></param>
/// <returns></returns>
public static string Transformation(string imgpath)
{
var client = new Baidu.Aip.Ocr.Ocr(API_KEY, SECRET_KEY);
client.Timeout = 60000; // 修改超时时间
var image = File.ReadAllBytes(imgpath);
// var url = "https://timgsa.baidu.com/timg?image&quality=80&size=b9999_10000&sec=1564654456007&di=7832dd6f515e654bdf5074e47b6803b1&imgtype=0&src=http%3A%2F%2Fpic.962.net%2Fup%2F2018-5%2F2018527102938219310.jpg";
// 调用通用文字识别, 图片参数为本地图片，可能会抛出网络等异常，请使用try/catch捕获
//用户向服务请求识别某张图中的所有文字
// var result = client.GeneralBasic(image); //本地图图片
// 如果有可选参数
// var options = new Dictionary<string, object>{
// {"language_type", "CHN_ENG"},
// {"detect_direction", "true"},
// {"detect_language", "true"},
// {"probability", "true"}
//};
// // 带参数调用通用文字识别, 图片参数为本地图片
// result = client.GeneralBasic(image, options);
//var result = client.GeneralBasicUrl(url); //网络图片
var result = client.Accurate(image);
// var options = new Dictionary<string, object>{
// {"detect_direction", "true"},
// {"probability", "true"}
//};
//var result = client.Accurate(image,options); //本地图片：相对于通用文字识别该产品精度更高，但是识别耗时会稍长。
//var result = client.General(image); //本地图片：通用文字识别（含位置信息版）
//var result = client.GeneralUrl(url); //网络图片：通用文字识别（含位置信息版）
//var result = client.GeneralEnhanced(image); //本地图片：调用通用文字识别（含生僻字版）
//var result = client.GeneralEnhancedUrl(url); //网络图片：调用通用文字识别（含生僻字版）
//var result = client.WebImage(image); //本地图片:用户向服务请求识别一些背景复杂，特殊字体的文字。
//var result = client.WebImageUrl(url); //网络图片:用户向服务请求识别一些背景复杂，特殊字体的文字。
YunCe.OCR.Common.BaiduEntity.LocalImageResponseEntity info = JsonConvert.DeserializeObject <YunCe.OCR.Common.BaiduEntity.LocalImageResponseEntity>(result.ToString());
StringBuilder str = new StringBuilder();
foreach (var item in info.WordsResult)
{
str.Append(item.words + "<br>");
}
return(str.ToString());
}
private void GetOcrJsonAndPrint(Baidu.Aip.Ocr.Ocr client, byte[] bytes)
{
IsProgressVisibility = Visibility.Visible;
List <Root> rootList = new List <Root>();
string jsonStr = string.Empty;
try
{
if (NormalRadioButton == true)
{
jsonStr = JsonConvert.SerializeObject(client.GeneralBasic(bytes));
}
else
{
jsonStr = JsonConvert.SerializeObject(client.Accurate(bytes));
}
}
catch (Exception ex)
{
System.Windows.MessageBox.Show("Ocr获取结果失败" + ex);
IsProgressVisibility = Visibility.Collapsed;
return;
}
Root root = null;
if (!string.IsNullOrWhiteSpace(jsonStr))
{
root = JsonConvert.DeserializeObject <Root>(jsonStr);
}
OcrResult = string.Empty;
foreach (var item in root.words_result)
{
OcrResult = OcrResult + item.words + "\n";
}
IsProgressVisibility = Visibility.Collapsed;
MyWindow.Dispatcher.Invoke(new Action(() =>
{
AddRecord();
}));
}
private void LoadImage(string filePath)
{
_textSegments.Clear();
List <Mat> croppedChars = new List <Mat>();
byte[] image = File.ReadAllBytes(filePath);
Mat originalMat = Mat.FromImageData(image, ImreadModes.AnyColor);
Mat displayMat = originalMat.Clone();
_imageSize = originalMat.Size();
Dictionary <string, object> options = new Dictionary <string, object>
{
{ "recognize_granularity", "small" },
{ "detect_direction", "true" },
{ "vertexes_location", "true" },
{ "probability", "true" },
{ "detect_language", "true" }
};
JObject resultJson = _client.Accurate(image, options); // OCR accurate
//Debug.Print(resultJson.ToString());
dynamic ocrResult = JsonConvert.DeserializeObject <dynamic>(resultJson.ToString());
int wordCount = ocrResult.words_result_num;
for (int i = 0; i < wordCount; i++)
{
dynamic chars = ocrResult.words_result[i].chars;
for (int j = 0; j < chars.Count; j++)
{
TextSegmentData segmentData = new TextSegmentData
{
TextLine = ocrResult.words_result[i].words,
TextLineWidth = ocrResult.words_result[i].location.width,
TextLineTop = ocrResult.words_result[i].location.top,
TextLineLeft = ocrResult.words_result[i].location.left,
TextLineHeight = ocrResult.words_result[i].location.height,
TextChar = chars[j]["char"],
TextCharWidth = chars[j].location.width,
TextCharTop = chars[j].location.top,
TextCharLeft = chars[j].location.left,
TextCharHeight = chars[j].location.height
};
segmentData.IsCJK = segmentData.TextChar.Any(x => x.IsChinese());
Debug.Print($"Text: {segmentData.TextChar}, IsCJK? {segmentData.IsCJK}, W {segmentData.TextCharWidth}, H {segmentData.TextCharHeight}, T {segmentData.TextCharTop}, L {segmentData.TextCharLeft} ");
if (segmentData.IsCJK)
{
Rect cropCharRect = new Rect(
segmentData.TextCharLeft,
segmentData.TextCharTop,
GetSizeSafe((int)(segmentData.TextCharWidth * 1.5), segmentData.TextCharLeft, originalMat.Width),
GetSizeSafe((int)(segmentData.TextCharHeight * 1.2), segmentData.TextCharTop, originalMat.Height)
);
//displayMat.Rectangle(cropCharRect, Scalar.RandomColor(), 2, LineTypes.AntiAlias); // mark every word
Mat croppedChar = new Mat(originalMat, cropCharRect);
croppedChars.Add(croppedChar);
segmentData.TextCharCroppedMat = croppedChar.Clone();
Rect cropTextRect = new Rect(segmentData.TextLineLeft, segmentData.TextLineTop, segmentData.TextLineWidth, segmentData.TextLineHeight);
Mat croppedLine = new Mat(originalMat, cropTextRect);
segmentData.TextLineCroppedMat = croppedLine.Clone();
//croppedChar.SaveImage("!" + DateTime.Now.Ticks + ".png");
}
_textSegments.Add(segmentData);
}
}
int netInputWidth = 80;
int netInputHeight = 80;
using (Net net = CvDnn.ReadNetFromTensorflow(AppDomain.CurrentDomain.BaseDirectory + "all_freezed_vgg19_tf115.pb"))
{
foreach (TextSegmentData sgData in _textSegments.Where(x => x.IsCJK).ToArray())
{
// preprocess
//sgData.TextCharCroppedMat.SaveImage("!" + DateTime.Now.Ticks + ".png");
Mat greyText = sgData.TextCharCroppedMat.CvtColor(ColorConversionCodes.BGR2GRAY);
//Mat textAfterThreshold = new Mat();
//Cv2.Threshold(greyText, textAfterThreshold, 0, 255, ThresholdTypes.Binary | ThresholdTypes.Otsu);
//Mat textAfterMorph = new Mat();
//Mat kernel = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(1, 1));
//Cv2.MorphologyEx(textAfterThreshold, textAfterMorph, MorphTypes.Open, kernel);
//Cv2.MorphologyEx(textAfterMorph, textAfterMorph, MorphTypes.Close, kernel);
// resize
double scaleW = netInputWidth / (double)sgData.TextCharCroppedMat.Width;
double scaleH = netInputHeight / (double)sgData.TextCharCroppedMat.Height;
double scale = scaleW < scaleH ? scaleW : scaleH;
Mat resizedText = new Mat();
Cv2.Resize(greyText, resizedText, new Size(0, 0), scale, scale, InterpolationFlags.Cubic);
int padTop = 0;
int padBottom = 0;
int padLeft = 0;
int padRight = 0;
if (resizedText.Width < netInputWidth)
{
padLeft = (netInputWidth - resizedText.Width) / 2;
if ((netInputWidth - resizedText.Width) % 2 > 0)
{
padRight = padLeft + 1;
}
else
{
padRight = padLeft;
}
}
else if (resizedText.Height < netInputHeight)
{
padTop = (netInputHeight - resizedText.Height) / 2;
if ((netInputHeight - resizedText.Height) % 2 > 0)
{
padBottom = padTop + 1;
}
else
{
padBottom = padTop;
}
}
resizedText = resizedText.CopyMakeBorder(padTop, padBottom, padLeft, padRight, BorderTypes.Constant, Scalar.White);
resizedText = resizedText.CvtColor(ColorConversionCodes.GRAY2BGR); // inferring needs BGR input instead of gray
//Cv2.ImShow("" + Guid.NewGuid(), resizedText);
//resizedText.SaveImage("!" + DateTime.Now.Ticks + ".png");
int classId1;
double classProb1;
List <CharProbClass> probList;
var inputBlob = CvDnn.BlobFromImage(resizedText, 1, new Size(netInputWidth, netInputHeight), new Scalar(104, 117, 123));
net.SetInput(inputBlob);
var prob = net.Forward();
GetMaxClass(prob, out classId1, out classProb1, out probList);
sgData.ClassLable = GetClassText(classId1);
sgData.ClassProb = classProb1;
sgData.ProbClassList = probList;
Debug.Print($"Char:{sgData.TextChar}, ClassID:{GetClassText(classId1)}, classProb:{classProb1}");
}
}
// done image processing, calculating
var groupedTextLines = _textSegments.Where(x => x.IsCJK).GroupBy(
x => new
{
x.TextLineWidth,
x.TextLineTop,
x.TextLineLeft,
x.TextLineHeight
}).ToArray();
foreach (var textLine in groupedTextLines)
{
Dictionary <string, double> fontProbDict = new Dictionary <string, double>();
foreach (TextSegmentData segmentData in textLine)
{
if (!fontProbDict.ContainsKey(segmentData.ClassLable))
{
fontProbDict.Add(segmentData.ClassLable, segmentData.ClassProb);
}
else if (segmentData.ClassProb > fontProbDict[segmentData.ClassLable])
{
fontProbDict[segmentData.ClassLable] += segmentData.ClassProb;
}
}
var orderedFontProb = fontProbDict.OrderByDescending(x => x.Value).ToArray();
Debug.Print($"Text Line: {textLine.FirstOrDefault()?.TextLine}, Font Name: {orderedFontProb[0].Key}");
foreach (TextSegmentData data in textLine)
{
data.TextLineFont = orderedFontProb[0].Key;
data.ProbClassList = textLine.ToList().FirstOrDefault()?.ProbClassList;
}
Rect textLineRect = new Rect((int)textLine.FirstOrDefault()?.TextLineLeft, (int)textLine.FirstOrDefault()?.TextLineTop, (int)textLine.FirstOrDefault()?.TextLineWidth, (int)textLine.FirstOrDefault()?.TextLineHeight);
displayMat.Rectangle(textLineRect, Scalar.RandomColor(), 2, LineTypes.AntiAlias);
}
pictureBoxOriginal.Image = displayMat.ToBitmap();
}
public static void Run(string path, List <Models> models)
{
var image = File.ReadAllBytes(path);
// 调用通用文字识别, 图片参数为本地图片，可能会抛出网络等异常，请使用try/catch捕获
//var result = client.AccurateBasic(image);
//Console.WriteLine(result);
// 如果有可选参数
var options = new Dictionary <string, object> {
{ "language_type", "CHN_ENG" },
{ "detect_direction", "true" },
{ "detect_language", "true" },
//是否显示置信度
{ "probability", "true" }
};
// 带参数调用通用文字识别, 图片参数为本地图片
var result = client.Accurate(image, options);
Console.WriteLine(result);
Console.Read();
//解释Json
Root rt = JsonConvert.DeserializeObject <Root>(result.ToString());
//List<Models> models = new List<Models>();
//右半页OCR后的识别判断,location.left的值只适用于河北省招生计划右半页
if (path.Contains("right"))
{
//要定位left筛选出专业代号和专业名称，只测试过右半部分，有时会误选专业说明，是IEnumerable
var majors = (from t in rt.words_result
where t.location.left > 0 && t.location.left < 250 && Regex.IsMatch(t.words, @"^\d{2}\D")
select t).ToList();
//要定位left筛选出院校代号和院校名称，只测试过右半部分,是IEnumerable
var colleges = (from t in rt.words_result
where t.location.left >= 0 && t.location.left < 60 &&
Regex.IsMatch(t.words, @"^\d{4}") &&
!t.words.Contains("代号")
select t).ToList();
//要left及与院校名称差不多高度的top定位，筛选出院校招生人数
var collegeNums = from t in rt.words_result
from c in colleges
where Math.Abs(t.location.top - c.location.top) < 30 && t.location.left > 600
select t.words;
for (int i = 0; i < majors.Count; i++)
{
//要left及与专业名称差不多高度的top定位，筛选出招生人数、学制和学费
string majorNum = (from t in rt.words_result
where Math.Abs(t.location.top - majors[i].location.top) < 40 && t.location.left > 600
select t.words).OrderBy(wordsResultItem => wordsResultItem.Length).LastOrDefault();
var college = (from c in colleges
where c.location.top - majors[i].location.top < 0
select c).LastOrDefault();
if (college != null)
{
string collegeNum = (from t in rt.words_result
where Math.Abs(t.location.top - college.location.top) < 40 && t.location.left > 600
select t.words).FirstOrDefault();
models.Add(new Models(majors[i].words, majorNum, college.words, collegeNum));
}
else
{
models.Add(models.Count > 0
? new Models(majors[i].words, majorNum, models.Last().CollegeName,
models.Last().CollegeNum)
: new Models(majors[i].words, majorNum, string.Empty, string.Empty));
}
}
//保存出现在页未的学校名，但下面没专业，留待下一页用
if (!models.Last().Equals(colleges.Last()))
{
models.Add(new Models(string.Empty, string.Empty, colleges.Last().words, collegeNums.Last()));
}
//foreach (var model in models)
//{
// Console.WriteLine(model.MajorName + " " + model.MajorNum + " " + model.CollegeName + " " + model.CollegeNum);
//}
}
//左半页OCR后的识别判断,location.left的值只适用于河北省招生计划左半页
else if (path.Contains("left"))
{
var majors = (from t in rt.words_result
where t.location.left > 0 && t.location.left <= 250 && Regex.IsMatch(t.words, @"^\d{2}\D")
select t).ToList();
//要定位left筛选出院校代号和院校名称，只适用左半部分,是IEnumerable
var colleges = rt.words_result.Where(t =>
t.location.left >= 130 && t.location.left < 210 && Regex.IsMatch(t.words, @"^\d{4}") &&
!t.words.Contains("代号")).ToList();
//要left及与院校名称差不多高度的top定位，筛选出院校招生人数
var collegeNums = rt.words_result.SelectMany(t => colleges, (t, c) => new { t, c })
.Where(@t1 => Math.Abs(@t1.t.location.top - @t1.c.location.top) < 30 && @t1.t.location.left > 600)
.Select(@t1 => @t1.t.words).ToList();
for (int i = 0; i < majors.Count; i++)
{
//要left及与专业名称差不多高度的top定位，筛选出招生人数、学制和学费
string majorNum = (from t in rt.words_result
where Math.Abs(t.location.top - majors[i].location.top) < 40 && t.location.left > 600
select t.words).OrderBy(wordsResultItem => wordsResultItem.Length).LastOrDefault();
var college = (from c in colleges
where c.location.top - majors[i].location.top < 0
select c).LastOrDefault();
if (college != null)
{
string collegeNum = (from t in rt.words_result
where Math.Abs(t.location.top - college.location.top) < 40 && t.location.left > 600
select t.words).FirstOrDefault();
models.Add(new Models(majors[i].words, majorNum, college.words, collegeNum));
}
else
{
models.Add(models.Count > 0
? new Models(majors[i].words, majorNum, models.Last().CollegeName,
models.Last().CollegeNum)
: new Models(majors[i].words, majorNum, string.Empty, string.Empty));
}
}
//保存出现在页未的学校名，但下面没专业，留待下一页用
if (!models.Last().Equals(colleges.Last()))
{
models.Add(new Models(string.Empty, string.Empty, colleges.Last().words, collegeNums.Last()));
}
//foreach (var model in models)
//{
// Console.WriteLine(model.MajorName + " " + model.MajorNum + " " + model.CollegeName + " " + model.CollegeNum);
//}
}
}
public void TestMethod1()
{
var fileList = new string[] { "A", "B", "C", "D" };
var client = new Baidu.Aip.Ocr.Ocr(BaiduHelper.API_KEY, BaiduHelper.SECRET_KEY);
foreach (var fItem in fileList)
{
//var ocr = new TesseractEngine("./tessdata", "chi_sim", EngineMode.Default);
//ocr.SetVariable("tessedit_char_whitelist", "委买卖一");
var img = new Bitmap(@"F:\byj\pic\" + fItem + ".png");
var image = File.ReadAllBytes(@"F:\byj\pic\" + fItem + ".png");
// 调用通用文字识别, 图片参数为本地图片，可能会抛出网络等异常，请使用try/catch捕获
var options = new Dictionary <string, object> {
{ "recognize_granularity", "big" },
{ "language_type", "CHN_ENG" },
{ "detect_direction", "true" },
{ "detect_language", "true" },
{ "vertexes_location", "true" },
{ "probability", "true" }
};
// 带参数调用通用文字识别（含位置信息版）, 图片参数为本地图片
var result = client.General(image, options);
var show = result["words_result"].ToList();
var one = show.Where(a => a["words"].ToString().StartsWith("委买队列")).FirstOrDefault();
Newtonsoft.Json.Linq.JToken buyone = null;
if (one == null)
{
var AccurateOptions = new Dictionary <string, object> {
{ "recognize_granularity", "big" },
{ "detect_direction", "true" },
{ "vertexes_location", "true" },
{ "probability", "true" }
};
result = client.Accurate(image, AccurateOptions);
show = result["words_result"].ToList();
one = show.Where(a => a["words"].ToString().StartsWith("委买队列")).FirstOrDefault();
}
if (one == null)
{
throw new Exception("分析失败 ");
}
Pen myPen = new Pen(System.Drawing.Color.BurlyWood, 3);
var g = Graphics.FromImage(img);
int width = Convert.ToUInt16(one["location"]["width"].ToString());
int height = Convert.ToUInt16(one["location"]["height"].ToString());
int x = Convert.ToUInt16(one["location"]["left"].ToString());
int y = Convert.ToUInt16(one["location"]["top"].ToString());
g.DrawRectangle(myPen, new Rectangle(x, y, width, height));
g.DrawRectangle(myPen, new Rectangle(x - 68, y + height, 55, height));
//g.DrawRectangle(myPen, new Rectangle(x - 40, y + 37, 80, 31));
g.DrawRectangle(myPen, new Rectangle(x + 36, y + height, 40, height));
g.DrawRectangle(myPen, new Rectangle(x + 89, y + height, 30, height));
Bitmap bmp = new Bitmap(img);
img.Dispose();
bmp.Save(@"F:\byj\pic\" + fItem + "_b.png"); //
}
}