github-actions[bot]
commented
2 days ago 👋 Hello @Manny-SF, thank you for your interest in make-sense - free to use online tool for labelling photos! 🏷️
🐞 Bug reports
If you noticed that make-sense is not working properly, please provide us with as much information as possible. To make your life easier, we have prepared a bug report template containing all the relevant details. We know, we ask for a lot... However, please believe that knowing all that extra information - like the type of browser you use or the version of node you have installed - really helps us to solve your problems faster and more efficiently. 😉
💬 Get in touch
If you've been trying to contact us but for some reason we haven't responded to your issue yet, don't hesitate to get back to us on Gitter or Twitter.
💻 Local setup
# clone repository
git clone https://github.com/SkalskiP/make-sense.git
# navigate to main dir
cd make-sense
# install dependencies
npm install
# serve with hot reload at localhost:3000
npm startTo ensure proper functionality of the application locally, an npm 8.x.x and node.js v16.x.x versions are required. More information about this problem is available in the #16 issue.
Description: I would like to request a feature that allows users to copy all labels (bounding boxes, annotations, etc.) from one image and paste them onto another image. This would be especially helpful for AI training datasets where multiple images contain the same elements (e.g., identical menus, objects in similar positions). Manually re-drawing these labels across several images can be time-consuming and error-prone.
Use Case: For example, when training a model to recognize UI components or menus that appear consistently across multiple images, having the ability to duplicate labels from one image to another would streamline the process significantly. Instead of manually redrawing bounding boxes for each new image, users could simply copy existing labels and paste them into the new image, then make any necessary adjustments.
Proposed Functionality:
Copy Labels: Provide a button or keybinding to allow users to select and copy all labels from the current image. Paste Labels: Allow users to paste the copied labels onto a new image, preserving the positioning and classification. Optional Adjustments: After pasting, users can manually adjust the bounding boxes if there are small differences between images. Persistence: Ensure that the copy-paste functionality works across different image editing sessions within the tool. Benefits:
Saves time when working with similar images. Reduces the risk of mislabeling or inconsistencies across images. Improves efficiency when preparing AI training datasets. Thank you for considering this feature!