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fcn - Fully Convolutional Networks

PyPI Version Python Versions Build Status

Chainer implementation of Fully Convolutional Networks.

Installation

pip install fcn

Inference

Inference is done as below:

# forwaring of the networks
img_file=https://farm2.staticflickr.com/1522/26471792680_a485afb024_z_d.jpg
fcn_infer.py --img-files $img_file --gpu -1 -o /tmp  # cpu mode
fcn_infer.py --img-files $img_file --gpu 0 -o /tmp   # gpu mode

Original Image: https://www.flickr.com/photos/faceme/26471792680/

Training

cd examples/voc
./download_datasets.py
./download_models.py

./train_fcn32s.py --gpu 0
# ./train_fcn16s.py --gpu 0
# ./train_fcn8s.py --gpu 0
# ./train_fcn8s_atonce.py --gpu 0

The accuracy of original implementation is computed with (evaluate.py) after converting the caffe model to chainer one using convert_caffe_to_chainermodel.py.
You can download vgg16 model from here: vgg16_from_caffe.npz.

FCN32s

Implementation Accuracy Accuracy Class Mean IU FWAVACC Model File
Original 90.4810 76.4824 63.6261 83.4580 fcn32s_from_caffe.npz
Ours (using vgg16_from_caffe.npz) 90.5668 76.8740 63.8180 83.5067 fcn32s_voc_iter00092000.npz

FCN16s

Implementation Accuracy Accuracy Class Mean IU FWAVACC Model File
Original 90.9971 78.0710 65.0050 84.2614 fcn16s_from_caffe.npz
Ours (using fcn32s_from_caffe.npz) 90.9671 78.0617 65.0911 84.2604 fcn16s_voc_using_fcn32s_from_caffe_iter00032000.npz
Ours (using fcn32s_voc_iter00092000.npz) 91.1009 77.2522 65.3628 84.3675 fcn16s_voc_iter00100000.npz

FCN8s

Implementation Accuracy Accuracy Class Mean IU FWAVACC Model File
Original 91.2212 77.6146 65.5126 84.5445 fcn8s_from_caffe.npz
Ours (using fcn16s_from_caffe.npz) 91.2513 77.1490 65.4789 84.5460 fcn8s_voc_using_fcn16s_from_caffe_iter00016000.npz
Ours (using fcn16s_voc_iter00100000.npz) 91.2608 78.1484 65.8444 84.6447 fcn8s_voc_iter00072000.npz

FCN8sAtOnce

Implementation Accuracy Accuracy Class Mean IU FWAVACC Model File
Original 91.1288 78.4979 65.3998 84.4326 fcn8s-atonce_from_caffe.npz
Ours (using vgg16_from_caffe.npz) 91.0883 77.3528 65.3433 84.4276 fcn8s-atonce_voc_iter00056000.npz

Left to right, FCN32s, FCN16s and FCN8s, which are fully trained using this repo. See above tables to see the accuracy.

License

See LICENSE.