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A simple tool for labeling object bounding boxes in images specially adapted for the Yolo Algorithm and multi-class classification.

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BBox-Label-Tool

A simple tool for labeling object bounding boxes in images, implemented with Python Tkinter. This forked version is adapted for the Yolo Algorithm and creates XML files and permitts multi-class classification.

Screenshot: Label Tool

Data Organization

LabelTool
|
|--main.py # source code for the tool
|
|--Images/ # direcotry containing the images to be labeled, all images must have ".jpg" extension, case sensitive!
|
|--Labels/ # direcotry for the labeling results, will contain the ".xml" files

Environment

  • python 2.7
  • python PIL (Pillow)

Run

$ python main.py

Usage

  1. The current tool requires that the images to be labeled reside in /Images/001, /Images/002, etc. You will need to modify the code if you want to label images elsewhere.
  2. Input a folder number (e.g, 1, 2, 5...), and click Load. The images in the folder, along with a few example results will be loaded.
  3. To create a new bounding box, first write the correct class of the object, then left-click to select the first vertex. Moving the mouse to draw a rectangle, and left-click again to select the second vertex.
  • To cancel the bounding box while drawing, just press <Esc>.
  • To delete a existing bounding box, select it from the listbox, and click Delete.
  • To delete all existing bounding boxes in the image, simply click ClearAll.
  1. After finishing one image, click Next to advance. Likewise, click Prev to reverse. Or, input an image id and click Go to navigate to the speficied image.
  • Be sure to click Next after finishing a image, or the result won't be saved.

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A simple tool for labeling object bounding boxes in images specially adapted for the Yolo Algorithm and multi-class classification.

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