A python library for visualizing Keras Artificial Neural Networks
Project description
![photo](https://i.imgur.com/DrZJOzy.png)
![photo](https://i.imgur.com/EHIoNoR.png)
# ANN Visualizer
[![PyPI version](https://badge.fury.io/py/ann_visualizer.png)](https://badge.fury.io/py/ann_visualizer)
A great visualization python library used to work with Keras. It uses python's graphviz library to create a presentable graph of the neural network you are building.
## Installation
### From Github
1. Download the `ann_visualizer` folder from the github repository.
2. Place the `ann_visualizer` folder in the same directory as your main python script.
### From pip
Use the following command:
```bash
pip install ann_visualizer
```
## Usage
```python
from ann_visualizer.visualize import ann_viz;
#Build your model here
ann_viz(model)
```
## Documentation
### ann_viz(model, view=True, filename="network.gv")
* `model` - The Keras Sequential model
* `view` - If True, it opens the graph preview after executed
* `filename` - Where to save the graph. (.gv file format)
## Example
```python
import keras;
from keras.models import Sequential;
from keras.layers import Dense;
network = Sequential();
#Hidden Layer#1
network.add(Dense(units=6,
activation='relu',
kernel_initializer='uniform',
input_dim=11));
#Hidden Layer#2
network.add(Dense(units=6,
activation='relu',
kernel_initializer='uniform'));
#Exit Layer
network.add(Dense(units=1,
activation='sigmoid',
kernel_initializer='uniform'));
from ann_visualizer.visualize import ann_viz;
ann_viz(network);
```
This will output:
![photo](https://i.imgur.com/ngThGlk.png)
## Contributions
This library is still unstable. Please report all bug to the issues section. It is currently tested with `python3.5`, but it should run just fine on any python3.
![photo](https://i.imgur.com/EHIoNoR.png)
# ANN Visualizer
[![PyPI version](https://badge.fury.io/py/ann_visualizer.png)](https://badge.fury.io/py/ann_visualizer)
A great visualization python library used to work with Keras. It uses python's graphviz library to create a presentable graph of the neural network you are building.
## Installation
### From Github
1. Download the `ann_visualizer` folder from the github repository.
2. Place the `ann_visualizer` folder in the same directory as your main python script.
### From pip
Use the following command:
```bash
pip install ann_visualizer
```
## Usage
```python
from ann_visualizer.visualize import ann_viz;
#Build your model here
ann_viz(model)
```
## Documentation
### ann_viz(model, view=True, filename="network.gv")
* `model` - The Keras Sequential model
* `view` - If True, it opens the graph preview after executed
* `filename` - Where to save the graph. (.gv file format)
## Example
```python
import keras;
from keras.models import Sequential;
from keras.layers import Dense;
network = Sequential();
#Hidden Layer#1
network.add(Dense(units=6,
activation='relu',
kernel_initializer='uniform',
input_dim=11));
#Hidden Layer#2
network.add(Dense(units=6,
activation='relu',
kernel_initializer='uniform'));
#Exit Layer
network.add(Dense(units=1,
activation='sigmoid',
kernel_initializer='uniform'));
from ann_visualizer.visualize import ann_viz;
ann_viz(network);
```
This will output:
![photo](https://i.imgur.com/ngThGlk.png)
## Contributions
This library is still unstable. Please report all bug to the issues section. It is currently tested with `python3.5`, but it should run just fine on any python3.
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
ann_visualizer-1.3.tar.gz
(3.1 kB
view hashes)