BasicAI now supports custom model integration via API, tailored to meet your unique model annotation requirements.

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1. Create a Model

Head to the Model Center - My Models and click the + Create button.

Under the tab By Myself, fill in the following information:

• Model Name: Input the name of your model, which can be edited later.
• Data Type: Currently, BasicAI only supports custom models targeting Image data and Point Cloud Data (PCDs) in LiDAR Fusion data.
• Task Type: Select whether to detect objects or segment data. The Detection mode exclusively supports 2D bounding box annotation for Image data and cuboid (3D box) annotation for PCDs in LiDAR Fusion data.
• Thumbnail: Optionally upload a cover image of the model (max 5MB).

Click OK to complete creation.

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2. Set up the Model

2.1 Model Configuration

First, click the edit icon to input your model API URL. The Request Method is fixed as POST.

BasicAI will send a data sample from your team datasets to test the model connection. An example Request Body will be automatically provided in JSON format (read-only). Optionally, you can input Authorization in the Header if needed.

Then, click the Test Connection button. You will see the Request Status and the Response. If you encounter any errors, please follow the instructions provided in the prompt.

Upon successful testing, click Save.

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For more information, please review the API Reference.

2.2 Class Configuration

Click Config Classesto match the ID with the model Class.

• ID: The class or label in your API response.
• Class: The class name shown for the model in BasicAI.

You can switch between Edit by row or Edit by text in the top right corner of the pop-up window.

• Edit by row: Input the corresponding ID and Class at each row.
• Edit by text: Input “ID,Name” for each pair.

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Remember to save.

Click OK to save your edits. Otherwise, the changes will be lost.

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3. Run the Model

The icons next to the Model and Class Configuration indicate their status. When both turn green, you can click Run Model at the top right corner. The model running process is similar to Pre-trained Models.

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Be cautious to delete.

Deleting the model will remove the model itself and all associated model run results in the dataset. Objects directly generated in tools will not be affected.