Comment on page
Automatically add labels to your images.
You can access the AI-assistant via a tab in your project detail page. The AI-assistant allows you to automatically add labels to the images in your project based on the convolutional neural network (CNN) provided by DATAGYM. We offer you 80+ classes (ex., car, person, traffic light, etc.) to detect objects in your images. With a few click you can define which classes you need for your project and the respective labels will be added to your images. Thereby, you can pre-label the images to reduce the workload for your team and speed up the overall labeling process. Here you can see the full list of classes supported by our CNN.
Use the label-mapping table to define which objects you want to pre-label in your project. Therefore, you select a class from our CNN in the first column and a geometry from your label configuration in the second column. Thereby, you can can assign the classes to the objects you want to find in your project. Please note that only bounding box geometries can be used for the pre-labeling.
You need at least one bounding box in you label config to configure the pre-labeling functionality.
You can assign multiple classes to the same label configuration entry. In the example above, the classes
truckare both assigned to the
Vehiclegeometry. Thereby, all cars and trucks will be labeled as vehicles in your project.
The buttons on top of the page allow you to start and stop the pre-labeling process. The pre-labeling only considers images in tasks that are in the WAITING state. Make sure to move all task from BACKLOG to WAITING before you start the pre-labeling process.
After starting the process, a progress bar will keep you updated about the number of images that have already been labeled. Use the stop button to cancel the pre-labeling process. You can stop the pre-labeling process at any time and update the label mapping as you like before you continue.
After the pre-label process finished, you can see the total number of images/tasks in your project that were labeled.
Please note that tasks in your project are pre-labeled only once. You have to add or reconnect a specific dataset to start a new pre-labeling for the corresponding tasks.
If an image was pre-labeled it is marked with a light-blue clipboard icon as shown in the image.
Pre-labeling counts towards the AI-assistance limit of your pricing plan. For every pre-labeled image your remaining AI-assistance limit for this month will be reduced by one. If you try to label more images than you have Ai-assistance remaining you will be notified and can stop the process to reconsider the images you want to pre-label.
If your remaining AI-assistance reaches zero, the start button is disabled and you won't be able to further pre-label images.