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Visualkeras is a Python package to help visualize Keras (either standalone or included in TensorFlow) neural network architectures. It allows easy styling to fit most needs. This module supports layered style architecture generation which is great for CNNs (Convolutional Neural Networks), and a graph style architecture, which works great for most models including plain feed-forward networks.
| Date | Stars |
|---|---|
| 2026-07-31 | 660 |
| 2026-08-01 | 660 |
| 2026-08-02 | 660 |
| 2026-08-06 | 660 |
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# visualkeras for Keras / TensorFlow
[](https://pypi.python.org/pypi/visualkeras)
[](https://pypi.python.org/pypi/visualkeras)
[-brightgreen)](https://github.com/paulgavrikov/visualkeras/actions/workflows/ci.yaml)
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[](https://github.com/paulgavrikov/visualkeras/actions/workflows/ci.yaml)
[](https://visualkeras.readthedocs.io/en/latest/?badge=latest)
Visualkeras is a Python package for visualizing Keras and TensorFlow model architectures. It supports several rendering styles, such as classic layered CNN diagrams, node-based visualizations, and LeNet-style visualizations. It is very easy to get started with visualkeras (see Quickstart), but also highly customizable for advanced users. For help in citing this project, refer [here](#citation-header).
## Installation
Install the latest published release:
```bash
pip install visualkeras
```
Install the latest `master` branch (potentially unstable):
```bash
pip install git+https://github.com/paulgavrikov/visualkeras
```
## Quick Start
```python
import visualkeras
model = ...
visualkeras.layered_view(model).show()
visualkeras.layered_view(model, to_file="model.png")
```
The recommended high-level API is `show(...)`, which selects a renderer by mode:
```python
import visualkeras
from tensorflow.keras import layers
from visualkeras.options import FunctionalOptions
img = visualkeras.show(
model,
mode="functional",
options=FunctionalOptions(
collapse_enabled=True,
collapse_rules=[
{"kind": "layer", "selector": layers.Dense, "repeat_count": 4},
{
"kind": "block",
"selector": [layers.Dense, layers.Dropout],
"repeat_count": 2,
"annotation_position": "below",
},
],
),
)
```
`show(...)` supports these modes:
- `layered`
- `graph`
- `functional`
- `lenet`
## Renderers
| Renderer | Best for | Entry point |
|---|---|---|
| Layered view | Sequential CNN-style diagrams | `visualkeras.layered_view(model)` |
| Graph view | General node-based visualizations | `visualkeras.graph_view(model)` |
| Functional view | Functional Keras models with multiple modalities, inputs, outputs, streams, etc.; this is the most flexible option | `visualkeras.functional_view(model)` |
| LeNet view | Classic feature map stack diagrams; inspired by [LeNet](https://en.wikipedia.org/wiki/LeNet) | `visualkeras.lenet_view(model)` |
## Examples
We provide basic examples here. Explamples with various options and customizations are covered in the documentation: <https://visualkeras.readthedocs.io/>.
### Layered view
```python
import tensorflow as tf
from tensorflow import keras
import visualkeras
model = keras.Sequential([
keras.layers.Input(shape=(28, 28, 1)),
keras.layers.Conv2D(32, (3, 3), activation="relu"),
keras.layers.MaxPooling2D((2, 2)),
keras.layers.Conv2D(64, (3, 3), activation="relu"),
keras.layers.Flatten(),
keras.layers.Dense(10, activation="softmax"),
])
visualkeras.layered_view(model).show()
```
### Graph view
```python
import tensorflow as tf
from tensorflow import keras
import visualkeras
model = Sequential([
Conv2D(32, (3, 3), activation='relu', input_shape=(28, 28, 1)),
MaxPooling2D((2, 2)),
Dense(10, activation='softmax')
])
visualkeras.graph_view(model)
```
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Martin Kubovčík · University of Ss. Cyril and Methodius in Trnava · Slovakia
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:8bdbd66f7efc65d0, llm:Description: 'Visualkeras is a Python package to help visualize Keras ... neural network architectures... supports layered style architecture generation ... graph style architecture'
matched fp:8bdbd66f7efc65d0, llm:Description: 'Visualkeras is a Python package to help visualize Keras ... neural network architectures... supports layered style architecture generation ... graph style architecture'
matched fp:8bdbd66f7efc65d0, llm:Description: 'Visualkeras is a Python package to help visualize Keras ... neural network architectures... supports layered style architecture generation ... graph style architecture'