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Direct Labeling Control

With the recent addition of Direct Media labeling it’s now easier than ever to rapidly label images. However with the improvement comes an increased likelihood of careless labeling and poor ground truth labels. To help Admins account for this, we’ve added the ability to limit user access to direct labeling by project. With this access control, Admins can limit users to task based labeling only. This is especially useful with new employees or third party labeling teams who have yet to prove their labels will be consistent with the Defect book. rbac_label When adding new users to a private project (Settings>Invite), you’ll see a series of checked access controls under “Project Permissions”. To revoke direct labeling access, simply uncheck “Direct label” and that user will no longer see the option to label images from the data browser. You can assign a labeling task to these users.

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Direct Image Labeling

When viewing viewing a single image you will see a new UI element at the top left. By default you will be in “View” mode but if you switch to “Label”, you can add GT labels directly to each image. This method will speed up your labeling but be warned, without a reviewer or agreement labeling, there is an increased chance of mislabeled images going unnoticed.

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Splits

We’ve moved split out of the Metadata section and made it an independent element. You can now adjust split directly in the image view. To Auto Split, from the data browser simply select the three vertical dots next to “Split” and then choose “Auto Split”.

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Classification Activation Heatmap

To help with classification error analysis, we’ve implemented a heatmap “visual explanation” for all classification models. Now when conducting error analysis, users’ can see the specific area of each image that caused it to be classified in a specific way. Here we can see the heatmap highlights the cracked portion of the cement square - this was the area of the image that caused the model to classify this example as “cracked”. You can learn more about the approach here.

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Training Hour Usage

You can now see your organizations per project GPU training usage by hours. To see how many hours you’ve spent training models during a month, choose Projects > View Projects. You’ll see the GPU hrs for the current and previous month listed next to each project.

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Pause Cloud Instances

From the device media page you can now pause cloud instances used for deployment. Simply navigate to Devices and choose the vertical three dots under actions on the right of the page.