Metadata-Version: 2.1
Name: keras-visualizer
Version: 2.3
Summary: A Keras Model Visualizer
Home-page: https://github.com/lordmahyar/keras_visualizer
Author: Mahyar Amiri
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown

# Keras Visualizer
![PyPI](https://img.shields.io/pypi/v/keras-visualizer) ![GitHub repo size](https://img.shields.io/github/repo-size/lordmahyar/keras-visualizer)

A Python Library for Visualizing Keras Models.

[Keras Visualizer on GitHub](https://github.com/lordmahyar/keras-visualizer)\
[Keras Visualizer on PyPI](https://pypi.org/project/keras-visualizer/)\
[Keras Visualizer on Libraries.io](https://libraries.io/pypi/keras-visualizer)

## Dependencies

* keras
* graphviz
```python
sudo pip3 install keras
sudo apt-get install graphviz && pip3 install graphviz
```

## Installation


Use python package manager (pip) to install Keras Visualizer.
```bash
pip3 install keras-visualizer
```

## Usage
#### import
```python
from keras_visualizer import visualizer
```
#### function
```python
visualizer(model) # save model
visualizer(model, format='png') # save both model & image file for visualizing model
visualizer(model, format='png', view=True) # open image file after visualization
```

## Documentation
```python
visualizer(model, filename='graph', format=None, view=False)
```

* `model` : a Keras model instance.
* `filename` : where to save the visualization.
* `format` : file format to save 'pdf', 'png'.
* `view` : open file after process if True.

> **Note :**
> change `format='png'` or `format='pdf'` to save visualization file.
> use `view=True` to open visualization file.

## Example
you can use simple examples in `examples` directory.

### Example 1 :
```python
from keras import models, layers  
from keras_visualizer import visualizer  

model = models.Sequential([  
    layers.Dense(64, activation='relu', input_shape=(8,)),  
    layers.Dense(6, activation='softmax'),  
    layers.Dense(32),  
    layers.Dense(9, activation='sigmoid')])  

visualizer(model, format='png', view=True)
```
![example 1](https://github.com/lordmahyar/keras_visualizer/blob/master/examples/example1_output.png)

---

### Example 2 :
```python
from keras import models  
from keras.layers import Dense, Conv2D, MaxPooling2D, Flatten, Activation  
from keras_visualizer import visualizer  

model = models.Sequential()  
model.add(Conv2D(64, (3, 3), input_shape=(28, 28, 3), activation='relu'))  
model.add(MaxPooling2D((2, 2)))  
model.add(Flatten())  
model.add(Dense(3))  
model.add(Activation('sigmoid'))  
model.add(Dense(1))  

visualizer(model, format='png', view=True)
```
![example 2](https://github.com/lordmahyar/keras_visualizer/blob/master/examples/example2_output.png)

