Modification of convolutional neural net "UNET" for image segmentation in Keras framework
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README.md

ZF_UNET_224 Pretrained Model

Modification of convolutional neural net "UNET" for image segmentation in Keras framework

Requirements

Python 3.*, Keras 2.1, Tensorflow 1.4

Usage

from zf_unet_224_model import ZF_UNET_224, dice_coef_loss, dice_coef
from keras.optimizers import Adam

model = ZF_UNET_224(weights='generator')
optim = Adam()
model.compile(optimizer=optim, loss=dice_coef_loss, metrics=[dice_coef])

model.fit(...)

Notes

Pretrained weights

Download: Weights for Tensorflow backend ~123 MB (Keras 2.1, Dice coef: 0.998)

Weights were obtained with random image generator (generator code available here: train_infinite_generator.py). See example of images from generator below.

Example of images from generator

Dice coefficient for pretrained weights: ~0.998. See history of learning below:

Log of dice coefficient during training process