Model Hub

The Model Hub screen is where you create and manage your Models. The key elements in the Model Hube are:

Import Existing Model: allows you to specify the location of an existing model to import.
Add New Model: creates a new model.
Selection: selects all models in the list. You can also select individual models. Making selections displays actions (3a) that you can perform for the selected models(s):
- Favourite: tags the model as a favourite.
- Delete: removes the model from the Model Hub and from storage.
- Open: opens the model in the Modeling Tool.
- GitHub: exports the model to your GitHub account.
Name: lists the names of each model.
Status: lists the current status of each model:
- Waiting: training has not yet started, PerceptiLabs is waiting for the model to be run.
- Training: the model is training; a progress bar will be shown indicating the current progress.
- Validation: the Model is in the validation phase of the training.
- Paused: the training is paused.
- Stop: the training was stopped early.
- Training Complete: the training completely finished.
Exported: indicates whether the model has been exported or not. Hovering the mouse pointer over this will show you where the file was exported.
Training Time: the amount of time that the training took to complete.
Last Modified: the date when the model was last saved.
Management Buttons: allows you to delete, open models, and export your model to your GitHub account.

Model Creation

Click + to create a new model:

This displays the New Model popup where you select a model template to base your model on. The name (1) you specify for the model will become the name of the directory where the model.json file is stored. The model path (2) specifies the absolute path where the model directory will be created. This path defaults to ~/Documents/PerceptiLabs/Default.

You can create the model within the (default) project directory or you can create it in any other location.

Upon completing the popup, PerceptiLabs will create the directory with the model.json file on disk, and the model will be listed on the Model Hub screen. PerceptiLabs will also automatically save the project that contains the model. Any time you save the model, PerceptiLabs will update the model's model.json file.

Model Import

You can import an existing model by specifying a local directory or GitHub repo where a model.json file is located. This can be performed by clicking the import button on the Model Hub (shown in the screenshot below) or by selecting File > Import Model and specifying the location.