GitHub - DeliriumV01D/Traffic-sign-recognition: Simple exercise solution. Convolutional neural net classifier applied to the image by the sliding window method. Using c++, OpenCV, dlib.

Traffic sign recognition based on the convolutional neural net classifier. Background is assigned to one of the classes to avoid creating a detector. Classifier is applied by sliding window method. The program is written in c++ using OpenCV, dlib libraries. For classifier training images from The German Traffic Sign Detection Benchmark (http://benchmark.ini.rub.de/?section=gtsdb&subsection=dataset) are used.

Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
Classifiers.cpp		Classifiers.cpp
Classifiers.h		Classifiers.h
CommonDefinitions.h		CommonDefinitions.h
Descriptors.cpp		Descriptors.cpp
Descriptors.h		Descriptors.h
README.md		README.md
RandomWarpedImage.h		RandomWarpedImage.h
Resnet.h		Resnet.h
TDNNClassifier.h		TDNNClassifier.h
TData.cpp		TData.cpp
TData.h		TData.h
TDataset.cpp		TDataset.cpp
TDataset.h		TDataset.h
TIndexedObjects.h		TIndexedObjects.h
TRandomDouble.h		TRandomDouble.h
TRandomInt.h		TRandomInt.h
TTrafficSignClassifier.cpp		TTrafficSignClassifier.cpp
TTrafficSignClassifier.h		TTrafficSignClassifier.h
TTrafficSignDataset.cpp		TTrafficSignDataset.cpp
TTrafficSignDataset.h		TTrafficSignDataset.h
WriteToLog.h		WriteToLog.h
cascade_detector.cpp		cascade_detector.cpp
cascade_detector.h		cascade_detector.h
main.cpp		main.cpp
multiscale_sampler.cpp		multiscale_sampler.cpp
multiscale_sampler.h		multiscale_sampler.h

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