Skip to main content

Fully Convolutional Networks

Project description

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

[![](https://badge.fury.io/gh/wkentaro%2Ffcn.svg)](https://badge.fury.io/gh/wkentaro%2Ffcn)
[![](https://api.travis-ci.org/wkentaro/fcn.svg?branch=master)](https://travis-ci.org/wkentaro/fcn)

This is [Chainer](https://github.com/pfnet/chainer.git) implementation of
[fcn.berkeley.vision.org](https://github.com/shelhamer/fcn.berkeleyvision.org.git).


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

```bash
pip install --upgrade setuptools

pip install fcn
```


Inference
---------

Inference is done as below:

```bash
# Download sample image
wget https://farm2.staticflickr.com/1522/26471792680_a485afb024_z_d.jpg -O sample.jpg

# forwaring of the networks
fcn_infer.py --img-files sample.jpg --gpu -1 # cpu mode
fcn_infer.py --img-files sample.jpg # gpu mode
```

<img src="static/fcn8s_26471792680.jpg" width="80%" >

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


Training
--------

```bash
cd examples/voc
./download_dataset.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/open?id=0B9P1L--7Wd2vRy1XYnRSa1hNSW8).

**FCN32s**

| Implementation | Accuracy | Accuracy Class | Mean IU | FWAVACC | Model File |
|:--------------:|:--------:|:--------------:|:-------:|:-------:|:----------:|
| [Original](https://github.com/shelhamer/fcn.berkeleyvision.org/tree/master/voc-fcn32s) | 90.4810 | 76.4824 | 63.6261 | 83.4580 | [`fcn32s_from_caffe.npz`](https://drive.google.com/uc?id=0B9P1L--7Wd2vTElpa1p3WFNDczQ) |
| Ours (using `vgg16_from_caffe.npz`) | **90.5668** | **76.8740** | **63.8180** | **83.5067** | [`fcn32s_voc_iter00092000.npz`](https://drive.google.com/uc?0B9P1L--7Wd2vRTQzQl8xcUI5Uk0) |

**FCN16s**

| Implementation | Accuracy | Accuracy Class | Mean IU | FWAVACC | Model File |
|:--------------:|:--------:|:--------------:|:-------:|:-------:|:----------:|
| [Original](https://github.com/shelhamer/fcn.berkeleyvision.org/tree/master/voc-fcn16s) | 90.9971 | **78.0710** | 65.0050 | 84.2614 | [`fcn16s_from_caffe.npz`](https://drive.google.com/uc?id=0B9P1L--7Wd2vcnBiXzZTcG9FU3c) |
| Ours (using `fcn32s_from_caffe.npz`) | 90.9671 | 78.0617 | 65.0911 | 84.2604 | [`fcn16s_voc_using_fcn32s_from_caffe_iter00032000.npz`](https://drive.google.com/uc?id=0B9P1L--7Wd2vNTFyZDlXel9ZZms) |
| Ours (using `fcn32s_voc_iter00092000.npz`) | **91.1009** | 77.2522 | **65.3628** | **84.3675** | [`fcn16s_voc_iter00100000.npz`](https://drive.google.com/uc?id=0B9P1L--7Wd2vZ1ZUYTJhRkZ1WTg) |

**FCN8s**

| Implementation | Accuracy | Accuracy Class | Mean IU | FWAVACC | Model File |
|:--------------:|:--------:|:--------------:|:-------:|:-------:|:----------:|
| [Original](https://github.com/shelhamer/fcn.berkeleyvision.org/tree/master/voc-fcn8s) | 91.2212 | 77.6146 | 65.5126 | 84.5445 | [`fcn8s_from_caffe.npz`](https://drive.google.com/uc?id=0B9P1L--7Wd2vb0cxV0VhcG1Lb28) |
| Ours (using `fcn16s_from_caffe.npz`) | 91.2513 | 77.1490 | 65.4789 | 84.5460 | [`fcn8s_voc_using_fcn16s_from_caffe_iter00016000.npz`](https://drive.google.com/uc?id=0B9P1L--7Wd2vdVpRN253el9fdzA) |
| Ours (using `fcn16s_voc_iter00100000.npz`) | **91.2608** | **78.1484** | **65.8444** | **84.6447** | [`fcn8s_voc_iter00072000.npz`](https://drive.google.com/uc?id=0B9P1L--7Wd2vWG5MeUEwWmxudU0) |

**FCN8sAtOnce**

| Implementation | Accuracy | Accuracy Class | Mean IU | FWAVACC | Model File |
|:--------------:|:--------:|:--------------:|:-------:|:-------:|:----------:|
| [Original](https://github.com/shelhamer/fcn.berkeleyvision.org/tree/master/voc-fcn8s-atonce) | **91.1288** | **78.4979** | **65.3998** | **84.4326** | [`fcn8s-atonce_from_caffe.npz`](https://drive.google.com/uc?id=0B9P1L--7Wd2vZ1RJdXotZkNhSEk) |
| Ours (using `vgg16_from_caffe.npz`) | 91.0883 | 77.3528 | 65.3433 | 84.4276 | [`fcn8s-atonce_voc_iter00056000.npz`](https://drive.google.com/uc?id=0B9P1L--7Wd2vcl9STGhJY1J4WUE) |

<img src="examples/voc/static/fcn32s_iter00092000.jpg" width="30%" /> <img src="examples/voc/static/fcn16s_iter00100000.jpg" width="30%" /> <img src="examples/voc/static/fcn8s_iter00072000.jpg" width="30%" />

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

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fcn-6.0.5.tar.gz (1.2 MB view details)

Uploaded Source

File details

Details for the file fcn-6.0.5.tar.gz.

File metadata

  • Download URL: fcn-6.0.5.tar.gz
  • Upload date:
  • Size: 1.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for fcn-6.0.5.tar.gz
Algorithm Hash digest
SHA256 9b3375929ca11477fd45b250345fe135c7a694d355246b5ce0c159e38ba0be00
MD5 43e8c17ef80cc2c7e138b1f62a14d657
BLAKE2b-256 0139351300710210a2d43ec737e8feab905650e29893d7c7cc63d1d7415f90a0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page