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qjadud1994 / CRNN-Keras

CRNN (CNN+RNN) for OCR using Keras / License Plate Recognition
MIT License
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Execution problem #13

Closed niranjan8129 closed 4 years ago

niranjan8129 commented 5 years ago

Hi, You are did a great job and model. I liked very much. I have 2 issues . see the blow and help me out

1) while run trainin.py job i get below error

Traceback (most recent call last): File "training.py", line 41, in validation_steps=int(tiger_val.n / val_batch_size)) File "C:\ProgramData\Anaconda3\lib\site-packages\keras\legacy\interfaces.py", line 91, in wrapper return func(*args, **kwargs) File "C:\ProgramData\Anaconda3\lib\site-packages\keras\engine\training.py", line 1418, in fit_generator initial_epoch=initial_epoch) File "C:\ProgramData\Anaconda3\lib\site-packages\keras\engine\training_generator.py", line 68, in fit_generator raise ValueError('validation_steps=None is only valid for a' ValueError: validation_steps=None is only valid for a generator based on the keras.utils.Sequence class. Please specify validation_steps or use the keras.utils.Sequence class.

2 ) if I change validation_steps=int(tiger_val.n / val_batch_size)) to validation_steps=20 , I get below error. Kindly suggest me why I am getting these errors.

Epoch 1/30 Traceback (most recent call last): File "training.py", line 41, in validation_steps=5) File "C:\ProgramData\Anaconda3\lib\site-packages\keras\legacy\interfaces.py", line 91, in wrapper return func(*args, **kwargs) File "C:\ProgramData\Anaconda3\lib\site-packages\keras\engine\training.py", line 1418, in fit_generator initial_epoch=initial_epoch) File "C:\ProgramData\Anaconda3\lib\site-packages\keras\engine\training_generator.py", line 251, in fit_generator callbacks.on_epoch_end(epoch, epoch_logs) File "C:\ProgramData\Anaconda3\lib\site-packages\keras\callbacks.py", line 79, in on_epoch_end callback.on_epoch_end(epoch, logs) File "C:\ProgramData\Anaconda3\lib\site-packages\keras\callbacks.py", line 338, in on_epoch_end self.progbar.update(self.seen, self.log_values) AttributeError: 'ProgbarLogger' object has no attribute 'log_values'

K0BigYang commented 5 years ago

You can try like this :

model.fit_generator(generator=tiger_train.next_batch(), steps_per_epoch=ceil(tiger_train.n / batch_size), epochs=30, callbacks=[checkpoint], validation_data=tiger_val.next_batch(), validation_steps=ceil(tiger_val.n / val_batch_size))

KassemKallas commented 5 years ago

validation_steps = int(val_batch_size/tiger_val.n)

mouadb0101 commented 5 years ago

your batch size greater than your dataset train change your batch_size or add more dataset images