public int myOcrSplit(HObject ho_inImage, HObject ho_inRegion, HTuple hv_ocrClassifier,
HTuple hv_standardText, HTuple hv_charCount, HTuple hv_returnPunctuation, HTuple hv_lightOnDark,
out HTuple hv_Word)
{
// Local iconic variables
HObject ho_Timg1 = null, ho_ImageReduced, ho_Region = null;
HObject ho_Characters = null;
// Local control variables
HTuple hv_step = null, hv_stepMax = null, hv_useEnhanced = null;
HTuple hv_TextModel = null, hv_OCRHandle = null, hv_RegularExpression = null;
HTuple hv_UsedThreshold = new HTuple(), hv_Area = new HTuple();
HTuple hv_Row = new HTuple(), hv_Column = new HTuple();
HTuple hv_Area1 = new HTuple(), hv_Row1 = new HTuple();
HTuple hv_Column1 = new HTuple(), hv_findText = new HTuple();
HTuple hv_bufferCount = new HTuple(), hv_bufferMincontrast = new HTuple();
HTuple hv_Index = new HTuple(), hv_add = new HTuple();
HTuple hv_TextResultID = new HTuple(), hv_Class = new HTuple();
HTuple hv_Confidence = new HTuple(), hv_Score = new HTuple();
HTuple hv_Number = new HTuple(), hv_ScoreSum = new HTuple();
HTuple hv_Index1 = new HTuple(), hv_Length = new HTuple();
// Initialize local and output iconic variables
HOperatorSet.GenEmptyObj(out ho_Timg1);
HOperatorSet.GenEmptyObj(out ho_ImageReduced);
HOperatorSet.GenEmptyObj(out ho_Region);
HOperatorSet.GenEmptyObj(out ho_Characters);
hv_Word = new HTuple();
ho_Timg1.Dispose();
ho_Timg1 = ho_inImage.CopyObj(1, -1);
ho_ImageReduced.Dispose();
HOperatorSet.ReduceDomain(ho_Timg1, ho_inRegion, out ho_ImageReduced);
hv_step = 3;
hv_stepMax = 25;
hv_useEnhanced = 1;
HOperatorSet.CreateTextModelReader("auto", hv_ocrClassifier, out hv_TextModel);
HOperatorSet.ReadOcrClassCnn(hv_ocrClassifier, out hv_OCRHandle);
HOperatorSet.SetTextModelParam(hv_TextModel, "separate_touching_chars", "enhanced");
HOperatorSet.SetTextModelParam(hv_TextModel, "return_separators", "true");
HOperatorSet.SetTextModelParam(hv_TextModel, "add_fragments", "true");
HOperatorSet.SetTextModelParam(hv_TextModel, "return_punctuation", hv_returnPunctuation == 0 ? "false" : "true");
//RegularExpression := ''
//字符串转正则表达式
myStringToRegular(hv_standardText, out hv_RegularExpression);
hv_RegularExpression = ("(" + hv_RegularExpression) + ")";
//判断是否需要反转颜色
if ((int)(new HTuple(hv_lightOnDark.TupleEqual(1))) != 0)
{
HObject ExpTmpOutVar_0;
HOperatorSet.InvertImage(ho_ImageReduced, out ExpTmpOutVar_0);
ho_ImageReduced.Dispose();
ho_ImageReduced = ExpTmpOutVar_0;
}
else if ((int)(new HTuple(hv_lightOnDark.TupleEqual(2))) != 0)
{
//自动判断是否反转颜色，金工之前的项目中并未使用该功能
ho_Region.Dispose();
HOperatorSet.BinaryThreshold(ho_ImageReduced, out ho_Region, "max_separability",
"dark", out hv_UsedThreshold);
HOperatorSet.AreaCenter(ho_ImageReduced, out hv_Area, out hv_Row, out hv_Column);
HOperatorSet.AreaCenter(ho_Region, out hv_Area1, out hv_Row1, out hv_Column1);
if ((int)(new HTuple(hv_Area1.TupleGreater(hv_Area / 2))) != 0)
{
{
HObject ExpTmpOutVar_0;
HOperatorSet.InvertImage(ho_ImageReduced, out ExpTmpOutVar_0);
ho_ImageReduced.Dispose();
ho_ImageReduced = ExpTmpOutVar_0;
}
}
}
//以置信度最高为分割目标
if ((int)(new HTuple(hv_charCount.TupleEqual(0))) != 0)
{
hv_findText = 0;
hv_bufferCount = 0;
hv_bufferMincontrast = 5;
HTuple end_val52 = hv_stepMax;
HTuple step_val52 = 1;
for (hv_Index = 1; hv_Index.Continue(end_val52, step_val52); hv_Index = hv_Index.TupleAdd(step_val52))
{
hv_add = hv_step * hv_Index;
HOperatorSet.SetTextModelParam(hv_TextModel, "min_contrast", hv_add);
HOperatorSet.FindText(ho_ImageReduced, hv_TextModel, out hv_TextResultID);
ho_Characters.Dispose();
HOperatorSet.GetTextObject(out ho_Characters, hv_TextResultID, "all_lines");
HOperatorSet.DoOcrWordCnn(ho_Characters, ho_ImageReduced, hv_OCRHandle, hv_RegularExpression,
3, 10, out hv_Class, out hv_Confidence, out hv_Word, out hv_Score);
HOperatorSet.CountObj(ho_Characters, out hv_Number);
HOperatorSet.TupleSum(hv_Confidence, out hv_ScoreSum);
HOperatorSet.TupleFindFirst(hv_Class, "\x1A", out hv_Index1);
if ((int)((new HTuple(hv_bufferCount.TupleLess(hv_ScoreSum))).TupleAnd(new HTuple(hv_Index1.TupleEqual(
-1)))) != 0)
{
hv_findText = 1;
hv_bufferCount = hv_ScoreSum.Clone();
hv_bufferMincontrast = hv_add.Clone();
}
}
HOperatorSet.SetTextModelParam(hv_TextModel, "min_contrast", hv_bufferMincontrast);
HOperatorSet.FindText(ho_ImageReduced, hv_TextModel, out hv_TextResultID);
ho_Characters.Dispose();
HOperatorSet.GetTextObject(out ho_Characters, hv_TextResultID, "all_lines");
HOperatorSet.DoOcrWordCnn(ho_Characters, ho_ImageReduced, hv_OCRHandle, hv_RegularExpression,
3, 10, out hv_Class, out hv_Confidence, out hv_Word, out hv_Score);
}
//以识别字符为固定长度为分割目标
if ((int)(new HTuple(hv_charCount.TupleGreater(0))) != 0)
{
hv_findText = 0;
hv_bufferCount = 0;
hv_bufferMincontrast = 5;
HTuple end_val86 = hv_stepMax;
HTuple step_val86 = 1;
for (hv_Index = 1; hv_Index.Continue(end_val86, step_val86); hv_Index = hv_Index.TupleAdd(step_val86))
{
hv_add = hv_step * hv_Index;
HOperatorSet.SetTextModelParam(hv_TextModel, "min_contrast", hv_add);
HOperatorSet.FindText(ho_ImageReduced, hv_TextModel, out hv_TextResultID);
ho_Characters.Dispose();
HOperatorSet.GetTextObject(out ho_Characters, hv_TextResultID, "all_lines");
HOperatorSet.CountObj(ho_Characters, out hv_Number);
if ((int)(new HTuple(hv_charCount.TupleEqual(hv_Number))) != 0)
{
hv_findText = 1;
//
HOperatorSet.DoOcrWordCnn(ho_Characters, ho_ImageReduced, hv_OCRHandle,
hv_RegularExpression, 3, 10, out hv_Class, out hv_Confidence, out hv_Word,
out hv_Score);
HOperatorSet.TupleSum(hv_Confidence, out hv_ScoreSum);
HOperatorSet.TupleFindFirst(hv_Class, "\x1A", out hv_Index1);
if ((int)((new HTuple(hv_bufferCount.TupleLess(hv_ScoreSum))).TupleAnd(
new HTuple(hv_Index1.TupleEqual(-1)))) != 0)
{
hv_findText = 1;
hv_bufferCount = hv_ScoreSum.Clone();
hv_bufferMincontrast = hv_add.Clone();
}
}
}
//以置信度最高为分割目标 再识别一次
//if (findText == 0)
HOperatorSet.SetTextModelParam(hv_TextModel, "min_contrast", hv_bufferMincontrast);
HOperatorSet.FindText(ho_ImageReduced, hv_TextModel, out hv_TextResultID);
ho_Characters.Dispose();
HOperatorSet.GetTextObject(out ho_Characters, hv_TextResultID, "all_lines");
HOperatorSet.DoOcrWordCnn(ho_Characters, ho_ImageReduced, hv_OCRHandle, hv_RegularExpression,
3, 10, out hv_Class, out hv_Confidence, out hv_Word, out hv_Score);
//endif
}
//使用标准文本对比
if ((int)(new HTuple(hv_charCount.TupleLess(0))) != 0)
{
//判断是否和标准文本一致
hv_findText = 0;
hv_bufferCount = 0;
hv_bufferMincontrast = 5;
HTuple end_val130 = hv_stepMax;
HTuple step_val130 = 1;
for (hv_Index = 1; hv_Index.Continue(end_val130, step_val130); hv_Index = hv_Index.TupleAdd(step_val130))
{
hv_add = hv_step * hv_Index;
HOperatorSet.SetTextModelParam(hv_TextModel, "min_contrast", hv_add);
HOperatorSet.FindText(ho_ImageReduced, hv_TextModel, out hv_TextResultID);
ho_Characters.Dispose();
HOperatorSet.GetTextObject(out ho_Characters, hv_TextResultID, "all_lines");
HOperatorSet.CountObj(ho_Characters, out hv_Number);
HOperatorSet.TupleStrlen(hv_standardText, out hv_Length);
if ((int)(new HTuple(hv_Length.TupleNotEqual(hv_Number))) != 0)
{
continue;
}
HOperatorSet.DoOcrWordCnn(ho_Characters, ho_ImageReduced, hv_OCRHandle, hv_RegularExpression,
5, 10, out hv_Class, out hv_Confidence, out hv_Word, out hv_Score);
if ((int)(new HTuple(hv_Word.TupleEqual(hv_standardText))) != 0)
{
hv_findText = 1;
break;
}
HOperatorSet.TupleSum(hv_Confidence, out hv_ScoreSum);
HOperatorSet.TupleFindFirst(hv_Class, "\x1A", out hv_Index1);
if ((int)((new HTuple(hv_bufferCount.TupleLess(hv_ScoreSum))).TupleAnd(new HTuple(hv_Index1.TupleEqual(
-1)))) != 0)
{
hv_bufferCount = hv_ScoreSum.Clone();
hv_bufferMincontrast = hv_add.Clone();
}
}
//以置信度最高为分割目标 再识别一次
if ((int)(new HTuple(hv_findText.TupleEqual(0))) != 0)
{
HOperatorSet.SetTextModelParam(hv_TextModel, "min_contrast", hv_bufferMincontrast);
HOperatorSet.FindText(ho_ImageReduced, hv_TextModel, out hv_TextResultID);
ho_Characters.Dispose();
HOperatorSet.GetTextObject(out ho_Characters, hv_TextResultID, "all_lines");
HOperatorSet.DoOcrWordCnn(ho_Characters, ho_ImageReduced, hv_OCRHandle, hv_RegularExpression,
5, 10, out hv_Class, out hv_Confidence, out hv_Word, out hv_Score);
}
}
HOperatorSet.ClearTextModel(hv_TextModel);
HOperatorSet.ClearOcrClassCnn(hv_OCRHandle);
ho_Timg1.Dispose();
ho_ImageReduced.Dispose();
ho_Region.Dispose();
ho_Characters.Dispose();
int nRet = 1;
if (hv_findText == 1)
{
nRet = 0;
}
return(nRet);
}