keras-squeezenet 
SqueezeNet v1.1 Implementation using Keras Functional Framework 2.0
This network model has AlexNet accuracy with small footprint (5.1 MB) Pretrained models are converted from original Caffe network.
pip install keras_squeezenet
News
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Project is now up-to-date with the new Keras version (2.0).
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Old Implementation is still available at 'keras1' branch.
Library Versions
- Keras v2.0+
- Tensorflow 1.0+
Example Usage
import numpy as np
from keras_squeezenet import SqueezeNet
from keras.applications.imagenet_utils import preprocess_input, decode_predictions
from keras.preprocessing import image
model = SqueezeNet()
img = image.load_img('../images/cat.jpeg', target_size=(227, 227))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = preprocess_input(x)
preds = model.predict(x)
print('Predicted:', decode_predictions(preds))References
Licence
MIT License
Note: If you find this project useful, please include reference link in your work.