from an image by haar cascade get plate, then from plate get regions (by MSER) , from regions get letters/digits by SVM/logistic regression or by neural network
python3 image2characters.py "filename"
the path one above current directory (Plate) must be in $PYTHONPATH
for neural network you need weight.npz
https://archive.ics.uci.edu/ml/datasets/Letter+Recognition raw training data in mka@mka-HP:~/PycharmProjects/Rekkari/Training
└── TrainSVM ├── Digits │ └── SvmDir ├── Letters │ └── SvmDir
copied as follows
Kauppi:/PycharmProjects/Image2Characters> cp TrainSVM/Letters/SvmDir/logistic.pkl letters_logistic.pkl
Kauppi:/PycharmProjects/Image2Characters> cp TrainSVM/Letters/SvmDir/allSVM.txt.dict letters_logreg.dict
Kauppi:/PycharmProjects/Image2Characters> cp TrainSVM/Digits//SvmDir/logistic.pkl digits_logistic.pkl
Kauppi:/PycharmProjects/Image2Characters> cp TrainSVM/Digits//SvmDir/allSVM.txt.dict digits_logreg.dict
sphinx-quickstart
autodoc: automatically insert docstrings from modules (y/n) [n]: y edit index.rst make html