fcn 6.4.17

Fully Convolutional Networks

fcn - Fully Convolutional Networks

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.

Cite This Project

If you use this project in your research or wish to refer to the baseline results published in the README, please use the following BibTeX entry.

@misc{chainer-fcn2016,
  author =       {Ketaro Wada},
  title =        {{fcn: Chainer Implementation of Fully Convolutional Networks}},
  howpublished = {\url{https://github.com/wkentaro/fcn}},
  year =         {2016}
}