# OpenNetwork (opennetwork)
***Visit https://opennetwork.dezors.com***
A tiny developer suite for MLOps-oriented model authoring and loading. It lets you:
- `opennetwork.setmodel()` — open the **Playground** (web view) to design your model.
- `opennetwork.getmodel("model.json")` — load a JSON graph into a **Keras Functional** model.
- `opennetwork.init()` — quickstart banner.
> Default Playground: https://opennetwork.dezors.com/playground
## Install
```bash
pip install opennetwork
# or, to enable building Keras models:
pip install "opennetwork[keras]"
# optional native window instead of browser:
pip install "opennetwork[webview]"
```
## Python API
```python
import opennetwork as onn
onn.init()
onn.setmodel() # opens the Playground in a window/browser
# Build from JSON (returns tf.keras.Model if TensorFlow is installed)
model = onn.getmodel("model.json")
# If TensorFlow is not installed, you can still validate the graph:
model, extras = onn.getmodel("model.json", return_extras=True)
print(extras["inserted"]) # e.g., auto-added Flatten when Dense follows Conv2D
```
### CLI
```bash
opennetwork init
opennetwork setmodel
opennetwork getmodel path/to/model.json
```
## JSON schema (minimal)
```json
{
"id": "string",
"name": "string",
"layers": [
{
"id": "unique-id",
"type": "input|conv2d|dense|flatten|dropout|maxpool2d|batchnorm|activation|softmax_output",
"name": "optional",
"params": { "..." : "layer-params" },
"connections": ["next-layer-id", "..."],
"weights": [...], // optional
"biases": [...] // optional
}
]
}
```
- The graph is built **topologically**.
- If a `Dense` follows a convolutional/tensor output, a `Flatten` is **auto-inserted** (configurable).
- `softmax_output` is interpreted as a final `Activation("softmax")`.
- Unknown or missing shapes will be handled best-effort; for guaranteed results, include an explicit `Input` layer with `params.input_shape`.
## License
Apache 2.0
Under OpenNetwork @ Dezors 2025.
https://dezors.com - for more
# Social Link
https://x.com/DezorsTweets
https://www.linkedin.com/company/dezors
https://github.com/Dezors-Service-And-Consultancy/
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"description": "# OpenNetwork (opennetwork)\r\n***Visit https://opennetwork.dezors.com***\r\n\r\nA tiny developer suite for MLOps-oriented model authoring and loading. It lets you:\r\n\r\n- `opennetwork.setmodel()` \u2014 open the **Playground** (web view) to design your model. \r\n- `opennetwork.getmodel(\"model.json\")` \u2014 load a JSON graph into a **Keras Functional** model. \r\n- `opennetwork.init()` \u2014 quickstart banner.\r\n\r\n> Default Playground: https://opennetwork.dezors.com/playground\r\n\r\n## Install\r\n\r\n```bash\r\npip install opennetwork\r\n# or, to enable building Keras models:\r\npip install \"opennetwork[keras]\"\r\n# optional native window instead of browser:\r\npip install \"opennetwork[webview]\"\r\n```\r\n\r\n## Python API\r\n\r\n```python\r\nimport opennetwork as onn\r\n\r\nonn.init()\r\nonn.setmodel() # opens the Playground in a window/browser\r\n\r\n# Build from JSON (returns tf.keras.Model if TensorFlow is installed)\r\nmodel = onn.getmodel(\"model.json\")\r\n\r\n# If TensorFlow is not installed, you can still validate the graph:\r\nmodel, extras = onn.getmodel(\"model.json\", return_extras=True)\r\nprint(extras[\"inserted\"]) # e.g., auto-added Flatten when Dense follows Conv2D\r\n```\r\n\r\n### CLI\r\n\r\n```bash\r\nopennetwork init\r\nopennetwork setmodel\r\nopennetwork getmodel path/to/model.json\r\n```\r\n\r\n## JSON schema (minimal)\r\n\r\n```json\r\n{\r\n \"id\": \"string\",\r\n \"name\": \"string\",\r\n \"layers\": [\r\n {\r\n \"id\": \"unique-id\",\r\n \"type\": \"input|conv2d|dense|flatten|dropout|maxpool2d|batchnorm|activation|softmax_output\",\r\n \"name\": \"optional\",\r\n \"params\": { \"...\" : \"layer-params\" },\r\n \"connections\": [\"next-layer-id\", \"...\"],\r\n \"weights\": [...], // optional\r\n \"biases\": [...] // optional\r\n }\r\n ]\r\n}\r\n```\r\n\r\n- The graph is built **topologically**.\r\n- If a `Dense` follows a convolutional/tensor output, a `Flatten` is **auto-inserted** (configurable).\r\n- `softmax_output` is interpreted as a final `Activation(\"softmax\")`.\r\n- Unknown or missing shapes will be handled best-effort; for guaranteed results, include an explicit `Input` layer with `params.input_shape`.\r\n\r\n## License\r\n\r\nApache 2.0\r\n\r\nUnder OpenNetwork @ Dezors 2025.\r\n\r\nhttps://dezors.com - for more \r\n\r\n# Social Link \r\n\r\nhttps://x.com/DezorsTweets\r\nhttps://www.linkedin.com/company/dezors \r\nhttps://github.com/Dezors-Service-And-Consultancy/\r\n",
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