新增ocr训练代码

train/keras-train/train.py

@@ -70,8 +70,9 @@ if __name__=='__main__':
     model,basemodel = get_model(height=imgH, nclass=nclass)
     import os
     if os.path.exists('pretrain-models/keras.hdf5'):
-       model.load_weights('pretrain-models/keras.hdf5')
-
+       basemodel.load_weights('pretrain-models/keras.hdf5')
+    
+    ##注意此处保存的是model的权重
     checkpointer = ModelCheckpoint(filepath="save_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)
 

train/keras-train/trainbatch.py

@@ -4,7 +4,7 @@ model,basemodel = get_model(height=imgH, nclass=nclass)
 import os
 modelPath = '../pretrain-models/keras.hdf5'
 if os.path.exists(modelPath):
-       model.load_weights(modelPath)
+       basemodel.load_weights(modelPath)
         
 batchSize = 128
 train_loader = torch.utils.data.DataLoader(
@@ -43,7 +43,7 @@ for i in range(3):
                         loss = crrentLoss
                         path = 'save_model/model{}.h5'.format(loss)
                         print "save model:".format(path)
-                        model.save(path)
+                        basemodel.save(path)
 
                 j+=1