idobrusin / BBox-Label-Tool

A simple tool for labeling object bounding boxes in images.

BBox-Label-Tool

Sample run with input and output folder set:

python main.py -l json_single_file -i "/home/dobrusii/Project/datasets/refexp_val_objects/refexp_data/images/all" -o "/home/dobrusii/Project/datasets/refexp_val_objects/refexp_data/"

# Alternative
python main.py -l json_single_file -i "/home/dobrusii/Project/datasets/table_objects_dataset/images/all" -o "/home/dobrusii/Project/datasets/table_objects_dataset"

Run for custom data set:

# Activate virtual env e.g. workon bbox_label
python main.py -l json_single_file -i "/vol/data/Documents/Uni/Master/2018-WS/Masterproject/datasets/table_objects_dataset/images/all" -o "/vol/data/Documents/Uni/Master/2018-WS/Masterproject/datasets/table_objects_dataset"

This is a fork of xiaqunfeng/BBox-Label-Tool with some added functionallity:

• Read / write visual genome annotations
• Allow arbitrary labels instead of pre-defined classes.

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

Screenshot:

Data Organization

LabelTool
|
|--main.py # source code for the tool
|
|--class.txt # your class-candidates file
|
|--Images/ # direcotry containing the images to be labeled
|
|--Labels/ # direcotry for the labeling results
|
|--Examples/ # direcotry for the example bboxes

Environment

▶ python3 --version
Python 3.6.5
▶ python3
>>> import PIL
>>> PIL.__version__
'4.2.1'

Run

▶ python3 main.py
3 images loaded from /Users/xiaqunfeng/deeplearning/video_detection/BBox-Label-Tool/Images/001
set label class to : cat
set label class to : dog
Image No. 1 saved
Image No. 2 saved

Usage

0. The current tool requires that :
   • The input images dir.
   • The output labels dir.
   • You can choose those dir by button Image input folder and Label output folder, or input dir name in entry.
1. Click Load Dir. The images to be labeled in the folder, along with an example results will be loaded. The labeled file directory will automatically created if it does not exist.
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.
• press 'p' to go prev image.
• press 'n' to go next image.

4. If the image doesn't fit on screen, the tool will resizes both the bounding box and image on loading and back again on saving.

5. For multi-class task, modify 'class.txt' with your own class-candidates and before labeling bbox, choose the 'Current Class' in the Combobox and make sure you click ComfirmClass button.

6. If the image filename is foo.var.baz.jpg, the labeled file name will be foo.var.baz.txt, not foo.txt .

7. Support multiple image formats: "*.JPEG", "*.jpeg", "*JPG", "*.jpg", "*.PNG", "*.png", "*.BMP", "*.bmp".

Original project address: BBox-Label-Tool