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Welcome to the LabelLab Wiki!
LabelLab is an image analysis and classification platform for machine learning (ML) researchers. Originally built to classify images of elephants, it has been developed over the years and is now a full-fledged ML utility tool that is able to classify all kinds of images and carry out a number of ML-related tasks in a project-based manner while teaming up with other researchers.
- The user can create a project and add other users as collaborators.
- Inside a project, multiple actions can be performed such as -
- Uploading images in batches
- Creating new labels
- Labelling the uploaded images
- Creating and training different kinds of models
- Using the image path tracking feature on labeled images
- Each collaborator can be assigned one or more roles such as images, labels, models, admin, etc which will allow that collaborator to perform tasks specific to that role.
- On basis of their roles, the collaborators are divided into various teams.
- Each team has a chat system to discuss the assigned tasks and progress on the project.
- The project also has an activity tracking system recording all progress in it, which can be filtered by team, project member, category, and entity.
- Besides that, the user can also upload images outside a project and run classifications against a trained model.