A lightweight library for pre-processing images for pre-trained keras models
Project description
Keras Image Helper
A lightweight library for pre-processing images for pre-trained keras models
Imagine you have a Keras model. To use it, you need to apply a certain pre-processing function to all the images. Something like that:
from tensorflow.keras.applications.xception import preprocess_input
What if you want to now deploy this model to AWS Lambda? Or deploy your model with TF-Serving? You don't want to use the entire TensorFlow package just for that.
The solution is simple - use keras_image_helper
Usage
For an xception model:
from keras_image_helper import create_preprocessor
preprocessor = create_preprocessor('xception', target_size=(299, 299))
url = 'http://bit.ly/mlbookcamp-pants'
X = preprocessor.from_url(url)
Now you can use X
for your model:
preds = model.predict(X)
That's all :tada:
For more examples, check test.ipynb
Currently you can use the following pre-processors:
xception
resnet50
vgg16
inception_v3
If something you need is missing, PRs are welcome
Installation
It's available on PyPI, so you can install it with pip:
pip install keras_image_helper
Or with Pipenv:
pipenv install keras_image_helper
You can also install the latest version from this repo:
git clone git@github.com:alexeygrigorev/keras-image-helper.git
python setup.py install
Publishing
Use twine for that:
pip install twine
Generate a wheel:
python setup.py sdist bdist_wheel
Check the packages:
twine check dist/*
Upload the library to test PyPI to verify everything is working:
twine upload --repository-url https://test.pypi.org/legacy/ dist/*
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