DL之CNN：基于CRNN_OCR算法(keras,CNN+RNN)利用数据集(torch,mdb格式)训练来实现新图片上不定长度字符串进行识别—训练过程

输出结果

设计思路

核心代码

from keras.callbacks import ModelCheckpoint, ReduceLROnPlateau

nclass = len(characters) + 1  

model, basemodel = get_model_train(height=imgH, nclass=nclass)  

import os

if os.path.exists('./models/pretrain_models/keras.hdf5'):

   basemodel.load_weights('./models/pretrain_models/keras.hdf5')

checkpointer = ModelCheckpoint(filepath="./models/ intermediate_model/model{epoch:02d}-{val_loss:.4f}.hdf5", monitor='val_loss',

                              verbose=0, save_weights_only=False, save_best_only=True)

rlu = ReduceLROnPlateau(monitor='val_loss', factor=0.1, patience=1, verbose=0, mode='auto', epsilon=0.0001,

                       cooldown=0, min_lr=0)

model.fit_generator(gen(train_loader, flag='train'),  

                   steps_per_epoch=1024,

                   epochs=10000,

                   validation_data=gen(test_loader, flag='test'),

                   callbacks=[checkpointer, rlu],

                   validation_steps=1024)

#保存两个h5文件

model.save_weights('./models/final_model/final_model_weights.h5')  

model.save('./models/final_model/final_model.h5')