I used to make it manually, but i am using now flow_from_directory to train my network with my own data. I just have one question. When i make model.predict(), how can i know th
When you gather data, you define that. There is no rule. But a simple way to check is:
This will answer your question.
For getting one sample from a generator, you can see this question: How to get one value from a generator in Python?
As defined in Keras documentation, the generator output is a tuple of (inputs, targets)
Its pretty simple. When you pre-process your data, just replace the class labels with some specific integers (you can call it id). So, when you compute the loss or accuracy from the model's output, just compare the prediction with the ground truth in terms of integer labels (id).
In case if you need the label text, you can get it back from the id (integer).
You can have the the index of each class generated by the generator with class_indices property.
print(validation_generator.class_indices)
Simple...