Creating a project

Create a new project

To create a project, navigate to AI Models on the main sidebar, and click Create a new project. Fill in the name and description as prompted

Adding images to the project

Please read our documentation on Data best practices to make sure you are including the best images possible for training.
After creating the project, you will be prompted to add images.
When adding images, please note that images will be cropped into 1000x1000 tiles. This allows for easier labeling for you. Once a model is trained, it can be run on any size image.
Using the Upload files for labeling option, you can import images from a variety of sources, including your computer. This process is similar to that of uploading files through the Filesystem.
Selecting Choose from Biodock Filesystem from above will display the image folders you have in the Filesystem. Once the desired folder is selected, you will need to click "OK" and the data will be added automatically to the AI model project.
Illustration of selected "Kidney tissue images" folder from the Biodock Filesystem.
After all of the images have been added to the project, you will be on the Project Dashboard.

Project navigation

You'll notice 4 tabs on the left hand side, including Dashboard, Manage Data, Train/Deploy, and Settings. Find a brief explanation of the four sections below.
Manage Data
Train / Deploy
The Project Dashboard is the primary screen of the project, and where most of your time will be spent. The Dashboard summarizes the project and its progress, and is the entry point into creating annotations. From here, clicking any of the images will move you into the labeler.
In Manage Data, you can view all the images added to the project here, as well as add more data via Add Files to the Project. We also display helpful tips, errors and warnings about the type of data that you add to help you get optimal results from training.
The third page is Train / Deploy. After you finish annotation, this page helps you submit annotated images for AI training. This page also shows the status of your training jobs and helps you move your pipelines into an active state.
Finally, the Settings page gives you access to your project's settings, including adding new users to the project, changing the projects name and description, and deleting projects.