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https://github.com/rusty1s/graph-based-image-classification
Implementation of Planar Graph Convolutional Networks in TensorFlow
https://github.com/rusty1s/graph-based-image-classification
convolutional-neural-networks gcn graph graph-convolutional-networks pgcn planar-graph-convolutional-networks planar-graphs python spatial spectral tensorflow
Last synced: 3 months ago
JSON representation
Implementation of Planar Graph Convolutional Networks in TensorFlow
- Host: GitHub
- URL: https://github.com/rusty1s/graph-based-image-classification
- Owner: rusty1s
- License: mit
- Created: 2016-11-16T12:28:38.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2017-05-02T18:50:28.000Z (about 7 years ago)
- Last Synced: 2024-01-16T19:22:51.591Z (5 months ago)
- Topics: convolutional-neural-networks, gcn, graph, graph-convolutional-networks, pgcn, planar-graph-convolutional-networks, planar-graphs, python, spatial, spectral, tensorflow
- Language: Python
- Homepage:
- Size: 169 MB
- Stars: 41
- Watchers: 3
- Forks: 15
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Lists
- awesome-gcn - rusty1s/graph-based-image-classification
README
# A TensorFlow implementation of Graph-based Image Classification
[![Build Status][build-image]][build-url]
[![Code Coverage][coverage-image]][coverage-url]
[![Requirements Status][requirements-image]][requirements-url]
[![Code Climate][code-climate-image]][code-climate-url]
[![Code Climate Issues][code-climate-issues-image]][code-climate-issues-url]
This is a TensorFlow implementation based on my "[Graph-based Image
Classification](https://github.com/rusty1s/deep-learning/tree/master/thesis)"
master thesis.
## Requirements
Project is tested on Python 2.7, 3.4 and 3.5.
To install the additional required python packages, run:
```bash
pip install -r requirements.txt
```
## Miniconda
If you have [Miniconda
installed](http://conda.pydata.org/docs/install/quick.html#miniconda-quick-install-requirements),
you can simply run
```bash
./bin/install.sh
```
to install all dependencies (including TensorFlow and nauty/pynauty) in a new
conda environment with name ``.
For configuration and usage of the install script, run:
```bash
./bin/install.sh --help
```
To install Miniconda, run
```bash
./bin/conda.sh
```
and add `~/.miniconda/bin` to your path.
## Running tests
Install the test requirements:
```bash
pip install -r requirements_test.txt
```
Run the test suite:
```bash
./bin/test.sh
```
## Package structure
* `bin`: Shell scripts to test and install.
* `data`: Contains the datasets and helper methods to access and write
datasets.
* `grapher`: Graph generating algorithms.
* `model`: Wrapper for learning CNNs based on a simple JSON network structure
file.
* `networks`: Contains all network structures that were used for training and
evaluation.
* `patchy`: PatchySan implementation.
* `segmentation.algorithm`: Segmentation algorithms.
* `segmentation`: Extracts segment features and spatial neighborhood
information based on a given segmentation.
[build-image]: https://travis-ci.org/rusty1s/graph-based-image-classification.svg?branch=master
[build-url]: https://travis-ci.org/rusty1s/graph-based-image-classification
[coverage-image]: https://img.shields.io/codecov/c/github/rusty1s/graph-based-image-classification.svg
[coverage-url]: https://codecov.io/github/rusty1s/graph-based-image-classification?branch=master
[requirements-image]: https://requires.io/github/rusty1s/graph-based-image-classification/requirements.svg?branch=master
[requirements-url]: https://requires.io/github/rusty1s/graph-based-image-classification/requirements/?branch=master
[code-climate-image]: https://codeclimate.com/github/rusty1s/graph-based-image-classification/badges/gpa.svg
[code-climate-url]: https://codeclimate.com/github/rusty1s/graph-based-image-classification
[code-climate-issues-image]: https://codeclimate.com/github/rusty1s/graph-based-image-classification/badges/issue_count.svg
[code-climate-issues-url]: https://codeclimate.com/github/rusty1s/graph-based-image-classification/issues