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Add bonsai guide for sleap docs (#2050)
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Co-authored-by: Shrivaths Shyam <[email protected]>
Co-authored-by: Liezl Maree <[email protected]>
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75 changes: 75 additions & 0 deletions docs/guides/bonsai.md
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(bonsai)=

# Using Bonsai with SLEAP

Bonsai is a visual language for reactive programming and currently supports SLEAP models.

:::{note}
Currently Bonsai supports only single instance, top-down and top-down-id SLEAP models.
:::

### Exporting a SLEAP trained model

Before we can import a trained model into Bonsai, we need to use the {code}`sleap-export` command to convert the model to a format supported by Bonsai. For example, to export a top-down-id model, the command is as follows:

```bash
sleap-export -m centroid/model/folder/path -m top_down_id/model/folder/path -e exported/model/path
```

Please refer to the {ref}`sleap-export` docs for more details on using the command.

This will generate the necessary `.pb` file and other information files required by Bonsai. In this example, these files were saved to the specified `exported/model/path` folder.

The `exported/model/path` folder will have a structure like the following:

```plaintext
exported/model/path
├── centroid_config.json
├── confmap_config.json
├── frozen_graph.pb
└── info.json
```

### Installing Bonsai and necessary packages

1. Install Bonsai. See the [Bonsai installation instructions](https://bonsai-rx.org/docs/articles/installation.html).

2. Download and add the necessary packages for Bonsai to run with SLEAP. See the official [Bonsai SLEAP documentation](https://github.com/bonsai-rx/sleap?tab=readme-ov-file#bonsai---sleap) for more information.

### Using Bonsai SLEAP modules

Once you have Bonsai installed with the required packages, you should be able to open the Bonsai application. The workflow must have a source module `FileCapture` which can be found in the toolbox search in the workflow editor. Provide the path to the video that was used to train the SLEAP model in the `FileName` field of the module.

![Bonsai FileCapture module](../_static/bonsai-filecapture.jpg)

#### Top-down model
The top-down model requires both the `PredictCentroids` and the `PredictPoses` modules.

The `PredictCentroids` module will predict the centroids of detections. There are two fields inside the `PredictCentroids` module: the `ModelFileName` field and the `TrainingConfig` field. The `TrainingConfig` field expects the path to the training config JSON file for the centroid model. The `ModelFileName` field expects the path to the `frozen_graph.pb` file in the `exported/model/path` folder.

![Bonsai PredictCentroids module](../_static/bonsai-predictcentroids.jpg)

The `PredictPoses` module will predict the instances of detections. Similar to the `PredictCentroid` module, there are two fields inside the `PredictPoses` module: the `ModelFileName` field and the `TrainingConfig` field. The `TrainingConfig` field expects the path to the training config JSON file for the centered instance model. The `ModelFileName` field expects the path to the `frozen_graph.pb` file in the `exported/model/path` folder.

![Bonsai PredictPoses module](../_static/bonsai-predictposes.jpg)

#### Top-Down-ID model
The `PredictPoseIdentities` module will predict the instances with identities. This module has two fields: the `ModelFileName` field and the `TrainingConfig` field. The `TrainingConfig` field expects the path to the training config JSON file for the top-down-id model. The `ModelFileName` field expects the path to the `frozen_graph.pb` file in the `exported/model/path` folder.

![Bonsai PredictPoseIdentities module](../_static/bonsai-predictposeidentities.jpg)

#### Single instance model
The `PredictSinglePose` module will predict the poses for single instance models. This module also has two fields: the `ModelFileName` field and the `TrainingConfig` field. The `TrainingConfig` field expects the path to the training config JSON file for the single instance model. The `ModelFileName` field expects the path to the `frozen_graph.pb` file in the `exported/model/path` folder.

### Connecting the modules
Right-click on the `FileCapture` module and select **Create Connection**. Now click on the required SLEAP module to complete the connection.

![Bonsai module connection ](../_static/bonsai-connection.jpg)

Once it is done, the workflow in Bonsai will look something like the following:

![Bonsai.SLEAP workflow](../_static/bonsai-workflow.jpg)

Now you can click the green start button to run the workflow and you can add more modules to analyze and visualize the results in Bonsai.

For more documentation on various modules and workflows, please refer to the [official Bonsai docs](https://bonsai-rx.org/docs/articles/editor.html).
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{ref}`remote-inference` when you trained models and you want to run inference on a different machine using a **command-line interface**.

## SLEAP with Bonsai

{ref}`bonsai` when you want to analyze the trained SLEAP model to visualize the poses, centroids and identities for further visual analysis.

```{toctree}
:hidden: true
:maxdepth: 2
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colab
custom-training
remote
bonsai
```

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