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https://github.com/wkentaro/fcn

Chainer Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
https://github.com/wkentaro/fcn

chainer computer-vision convolutional-networks deep-learning fcn fcn8s segmentation semantic-segmentation

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Chainer Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)

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README

        

fcn - Fully Convolutional Networks
==================================

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[![Python Versions](https://img.shields.io/pypi/pyversions/fcn.svg)](https://pypi.org/project/fcn)
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Chainer implementation of [Fully Convolutional Networks](https://github.com/shelhamer/fcn.berkeleyvision.org).

Installation
------------

```bash
pip install fcn
```

Inference
---------

Inference is done as below:

```bash
# 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:

Training
--------

```bash
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`](https://drive.google.com/uc?id=1lKjYpFOc9EAPIt7foOO2nbaOWIpIZRaw).

**FCN32s**

| Implementation | Accuracy | Accuracy Class | Mean IU | FWAVACC | Model File |
|:--------------:|:--------:|:--------------:|:-------:|:-------:|:----------:|
| [Original](https://github.com/shelhamer/fcn.berkeleyvision.org/tree/main/voc-fcn32s) | 90.4810 | 76.4824 | 63.6261 | 83.4580 | [`fcn32s_from_caffe.npz`](https://drive.google.com/uc?id=1l5Ubj7zflQAwaNI7G35DzNcMoTf8CDLW) |
| Ours (using `vgg16_from_caffe.npz`) | **90.5668** | **76.8740** | **63.8180** | **83.5067** | - |

**FCN16s**

| Implementation | Accuracy | Accuracy Class | Mean IU | FWAVACC | Model File |
|:--------------:|:--------:|:--------------:|:-------:|:-------:|:----------:|
| [Original](https://github.com/shelhamer/fcn.berkeleyvision.org/tree/main/voc-fcn16s) | 90.9971 | **78.0710** | 65.0050 | 84.2614 | [`fcn16s_from_caffe.npz`](https://drive.google.com/uc?id=1kwLpLz1jzQqqF5QxQphsO4-aObQIQMWS) |
| Ours (using `fcn32s_from_caffe.npz`) | 90.9671 | 78.0617 | 65.0911 | 84.2604 | - |
| Ours (using `fcn32s_voc_iter00092000.npz`) | **91.1009** | 77.2522 | **65.3628** | **84.3675** | - |

**FCN8s**

| Implementation | Accuracy | Accuracy Class | Mean IU | FWAVACC | Model File |
|:--------------:|:--------:|:--------------:|:-------:|:-------:|:----------:|
| [Original](https://github.com/shelhamer/fcn.berkeleyvision.org/tree/main/voc-fcn8s) | 91.2212 | 77.6146 | 65.5126 | 84.5445 | [`fcn8s_from_caffe.npz`](https://drive.google.com/uc?id=1l_5RK28JRL19wpT22B-DY9We3TVXnnQQ) |
| Ours (using `fcn16s_from_caffe.npz`) | 91.2513 | 77.1490 | 65.4789 | 84.5460 | - |
| Ours (using `fcn16s_voc_iter00100000.npz`) | **91.2608** | **78.1484** | **65.8444** | **84.6447** | - |

**FCN8sAtOnce**

| Implementation | Accuracy | Accuracy Class | Mean IU | FWAVACC | Model File |
|:--------------:|:--------:|:--------------:|:-------:|:-------:|:----------:|
| [Original](https://github.com/shelhamer/fcn.berkeleyvision.org/tree/main/voc-fcn8s-atonce) | **91.1288** | **78.4979** | **65.3998** | **84.4326** | [`fcn8s-atonce_from_caffe.npz`](https://drive.google.com/uc?id=1lNHAz5QEo-OoHL8uAUuBPki-8xrEArhs) |
| Ours (using `vgg16_from_caffe.npz`) | 91.0883 | 77.3528 | 65.3433 | 84.4276 | - |

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

License
-------

See [LICENSE](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.

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