Feat: Implement ImageDataGenerator for real-time data augmentation #118
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Description:
This PR adds the
ImageDataGeneratorclass inpydeepflow/preprocessing.pyto enable real-time image data augmentation (rotation, shift, zoom, flip). This enhances the CNN capabilities by helping prevent overfitting and improving model robustness.Key Changes:
pydeepflow/preprocessing.pycontaining theImageDataGenerator.pydeepflow/model.py- Updatedfit()methods inMulti_Layer_ANNandMulti_Layer_CNNto accept the generator. Fixed pooling layer__init__for integerpool_size.pydeepflow/__init__.py- ExportedImageDataGenerator.Test
The new feature can be tested by creating an instance of the
ImageDataGeneratorand passing itsflowmethod to the model'sfitfunction. All existing tests continue to pass, ensuring no regressions were introduced.Closes #117