BBox-Label-Tool: Darkflow Annotations

A simple tool for labeling object bounding boxes in images, implemented with Python Tkinter.

Changes in this fork:

• Besides the .txt file. Save the annotations as an .xml file with the format of PASCAL VOC. As expected by Darkflow, the Tensorflow translation of Darknet's YOLO: Real-Time Object Detection.
• Button to show/hide bounding box number. This helps in the case the data set nees to be modified, removing or redoing several boxes.
• Support multiple file extensions: ".jpg", ".jpeg", ".JPG", ".JPEG"
• Do not crash if there is no Examples/ for the loaded dir. Is good to have them, but is not mandatory.

Screenshot:

Data Organization

LabelTool
|
|--main.py # source code for the tool
|
|--Images/ # directory containing the images to be labeled
|
|--Labels/ # directory for the labeling results
|
|--Examples/ # directory for the example bboxes
|
|--AnnotationsXML/ # directory for the labeling results to be used by Darkflow

Environment

• python 2.7
• python PIL (Pillow)

Run

$ python main.py

Usage

0. 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.
1. 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.
2. To create a new bounding box, 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.

3. 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.