/ZF_UNET_224_Pretrained_Model

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

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

ZF_UNET_224 Pretrained Model

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

Requirements

Python 3.*, Keras 2.0.8, Theano 0.9 or Tensorflow 1.3.0

Usage

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

model = ZF_UNET_224()
model.load_weights("zf_unet_224.h5") # optional
optim = Adam()
model.compile(optimizer=optim, loss=dice_coef_loss, metrics=[dice_coef])

model.fit(...)

Notes

Pretrained weights

Download: Weights for Theano backend ~123 MB (for old version of Keras 1.2)

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: ~0.999. See history of learning below:

Log of dice coefficient during training process