Extract deep learning features from images using simple python interface.
You are looking for generic image features for
- Image classification
- Image retrieval
- Image similarity and so on.
Sometimes, you are not looking for latest and greatest. You just need something that just works. With image_features, you can extract such deep learning based features from images in a single line of code:
from image_features import image_features features = image_features(['your_image_1.png', 'your_image_2.jpg'])
You can use these features to train a scikit-learn classification model:
from sklearn import linear_model from image_features import image_features X_train = image_features(['your_image_1.png', 'your_image_2.jpg']) y_train = ['cat', 'dog'] clf = linear_model.LogisticRegression() clf.fit(X_train, y_train)
Package internally uses PyTorch and imagenet pretrained deep learning model like resnet50 (default).
pip install -U git+https://github.com/chsasank/image_features.git
I have written an accompanying tutorial to help you get started.
- Inspired by face_recognition and how it just works most of the time.
- Simple yet fairly complete implementation.
- If there is enough interest in this, put on pypi
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