OpenALPR通過自定義訓練數據退出並出現段錯誤

Question

我使用OpenALPR，並且我已經訓練了OCR以識別強制字體。當我嘗試使用訓練數據時，alpr退出時出現分段錯誤。

我使用的是1.2.0版本的tesseract和3.03，與leptonica-1.71

當我用gdb運行它，我得到以下堆棧跟蹤：

(gdb) bt 
#0 0x00007ffff67ded7b in tesseract::Classify::ComputeCharNormArrays(FEATURE_STRUCT*, INT_TEMPLATES_STRUCT*, unsigned char*, unsigned char*)() from /usr/local/lib/libtesseract.so.3 
#1 0x00007ffff67e3b6b in tesseract::Classify::CharNormTrainingSample(bool, int, tesseract::TrainingSample const&, GenericVector<tesseract::UnicharRating>*)() from /usr/local/lib/libtesseract.so.3 
#2 0x00007ffff6806882 in tesseract::TessClassifier::UnicharClassifySample(tesseract::TrainingSample const&, Pix*, int, int, GenericVector<tesseract::UnicharRating>*)() from /usr/local/lib/libtesseract.so.3 
#3 0x00007ffff67e1b22 in tesseract::Classify::CharNormClassifier(TBLOB*, tesseract::TrainingSample const&, ADAPT_RESULTS*)() from /usr/local/lib/libtesseract.so.3 
#4 0x00007ffff67e1c95 in tesseract::Classify::DoAdaptiveMatch(TBLOB*, ADAPT_RESULTS*)() from /usr/local/lib/libtesseract.so.3 
#5 0x00007ffff67e1f24 in tesseract::Classify::AdaptiveClassifier(TBLOB*, BLOB_CHOICE_LIST*)() from /usr/local/lib/libtesseract.so.3 
#6 0x00007ffff67d993d in tesseract::Wordrec::call_matcher(TBLOB*)() from /usr/local/lib/libtesseract.so.3 
#7 0x00007ffff67d9986 in tesseract::Wordrec::classify_blob(TBLOB*, char const*, C_COL, BlamerBundle*)() from /usr/local/lib/libtesseract.so.3 
#8 0x00007ffff67d6bab in tesseract::Wordrec::classify_piece(GenericVector<SEAM*> const&, short, short, char const*, TWERD*, BlamerBundle*)() from /usr/local/lib/libtesseract.so.3 
#9 0x00007ffff67c808d in tesseract::Wordrec::chop_word_main(WERD_RES*)() from /usr/local/lib/libtesseract.so.3 
#10 0x00007ffff67d9821 in tesseract::Wordrec::cc_recog(WERD_RES*)() from /usr/local/lib/libtesseract.so.3 
#11 0x00007ffff6716e62 in tesseract::Tesseract::recog_word_recursive(WERD_RES*)() from /usr/local/lib/libtesseract.so.3 
#12 0x00007ffff6716ff5 in tesseract::Tesseract::recog_word(WERD_RES*)() from /usr/local/lib/libtesseract.so.3 
#13 0x00007ffff6708160 in tesseract::Tesseract::tess_segment_pass_n(int, WERD_RES*)() from /usr/local/lib/libtesseract.so.3 
#14 0x00007ffff66cf2a5 in tesseract::Tesseract::match_word_pass_n(int, WERD_RES*, ROW*, BLOCK*)() from /usr/local/lib/libtesseract.so.3 
#15 0x00007ffff66cf482 in tesseract::Tesseract::classify_word_pass1(tesseract::WordData*, WERD_RES*)() from /usr/local/lib/libtesseract.so.3 
#16 0x00007ffff66d26d6 in tesseract::Tesseract::classify_word_and_language(void (tesseract::Tesseract::*)(tesseract::WordData*, WERD_RES*), tesseract::WordData*)() from /usr/local/lib/libtesseract.so.3 
#17 0x00007ffff66d2dea in tesseract::Tesseract::RecogAllWordsPassN(int, ETEXT_DESC*, GenericVector<tesseract::WordData>*)() from /usr/local/lib/libtesseract.so.3 
#18 0x00007ffff66d3701 in tesseract::Tesseract::recog_all_words(PAGE_RES*, ETEXT_DESC*, TBOX const*, char const*, int)() from /usr/local/lib/libtesseract.so.3 
#19 0x00007ffff66c203d in tesseract::TessBaseAPI::Recognize(ETEXT_DESC*)() from /usr/local/lib/libtesseract.so.3 
#20 0x00000000004aadf4 in OCR::performOCR (this=0x93d7c0, pipeline_data=0x7fffe0a3a9b0) at /opt/openalpr/src/openalpr/ocr.cpp:79 
#21 0x000000000048845b in plateAnalysisThread (arg=0x7fffffffd380) at /opt/openalpr/src/openalpr/alpr_impl.cpp:261 
#22 0x00000000004df217 in tthread::thread::wrapper_function (aArg=0x93d210) at /opt/openalpr/src/openalpr/support/tinythread.cpp:169 
#23 0x00007ffff6401182 in start_thread (arg=0x7fffe0a3b700) at pthread_create.c:312 
#24 0x00007ffff590e00d in clone() at ../sysdeps/unix/sysv/linux/x86_64/clone.S:111 

Answer 1

我在調試時的Tesseract我看到發生此錯誤的原因是shape_table _-> getShape（id）正在使用id> =調用shape_table_的大小，在文件adaptmatch.cpp中調用。

作爲一種解決方法，我將代碼更改爲先檢查大小，然後跳過迭代而不是使用segfault退出。

這種解決方法有可能會產生不良後果，但至少它不會中斷。這是差異：

diff --git a/classify/adaptmatch.cpp b/classify/adaptmatch.cpp 
index 0eaf144..b21d980 100644 
--- a/classify/adaptmatch.cpp 
+++ b/classify/adaptmatch.cpp 
@@ -1148,7 +1148,7 @@ void Classify::ExpandShapesAndApplyCorrections(
    fontinfo_id = ClassAndConfigIDToFontOrShapeID(class_id, int_result.Config); 
    fontinfo_id2 = ClassAndConfigIDToFontOrShapeID(class_id, 
                int_result.Config2); 
- if (shape_table_ != NULL) { 
+ if (shape_table_ != NULL && fontinfo_id < shape_table_->NumShapes()) { 
     // Actually fontinfo_id is an index into the shape_table_ and it 
     // contains a list of unchar_id/font_id pairs. 
     int shape_id = fontinfo_id; 
@@ -1781,10 +1781,12 @@ void Classify::ComputeCharNormArrays(FEATURE_STRUCT* norm_feature, 
     int font_set_id = templates->Class[id]->font_set_id; 
     const FontSet &fs = fontset_table_.get(font_set_id); 
     for (int config = 0; config < fs.size; ++config) { 
-   const Shape& shape = shape_table_->GetShape(fs.configs[config]); 
-   for (int c = 0; c < shape.size(); ++c) { 
-   if (char_norm_array[shape[c].unichar_id] < pruner_array[id]) 
-    pruner_array[id] = char_norm_array[shape[c].unichar_id]; 
+   if (shape_table_->NumShapes() > fs.configs[config]) { 
+   const Shape shape = shape_table_->GetShape(fs.configs[config]); 
+   for (int c = 0; c < shape.size(); ++c) { 
+    if (char_norm_array[shape[c].unichar_id] < pruner_array[id]) 
+    pruner_array[id] = char_norm_array[shape[c].unichar_id]; 
+   } 
      } 
     } 
     }