Mass Labeling of Classification Images

For a classification project with thousands of images per class, is there any good way to annotate large groups of images? I am uploading images without a label and they all have the same class, but there doesn’t seem to be a way to select all the images and apply a single label to them all at once. Any help here? I’ve used other platforms in which I could search a file by name or upload/load images methodically where I can simply apply a label to an entire sorted group.

Based on the information provided in the extracts, Roboflow currently does not support the ability to mass assign labels to bulk sets of images. However, there are a few features and workarounds that might help speed up your annotation process:

  1. Keyboard Shortcuts: Roboflow provides keyboard shortcuts to speed up the annotation process. For example, you can use the numbers on your keypad to select a label, enter to replace it with a label name, and use your mouse to click to the next image. However, there seems to be an issue with the keyboard shortcuts that the Roboflow team is aware of and working to fix. In the meantime, you can use the tab key to navigate to the next image after labeling. The sequence to label something with the first label is: 1, enter, tab, right. Source

  2. Upload Batches: Roboflow organizes datasets into batches. Each time you upload a new set of images, a batch is automatically created to group them together. This feature allows you to divide and conquer the labeling task amongst your team by chunking your upload into separate batches. Source

  3. Label Assist: Roboflow Annotate comes with a tool called Label Assist that can recommend new annotations based on the model you have selected as your assistant. This could potentially speed up your annotation process if your images contain objects that are part of the Microsoft COCO dataset or any of the 50,000+ public trained models on Roboflow Universe. Source

Remember to choose a specific name that encompasses all of the classes of your dataset when creating an annotation group. This will help you manage your dataset library as it grows. Source

I hope this helps! If you have any other questions, feel free to ask.


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