PyYAT

Semi-Automatic Yolo Annotation Tool In Python

PyYAT

Using this tool, we can annotate bounding boxes for image annotation in YOLO format. It uses YOLOv3-608 weights to pre-annotate the bounding boxes in images. It reduces time and efforts in annotating large datasets by upto 90%.

About the repository

• 'yolo_annotation_tool.py' : Main file to load images one-by-one from the dataset, and then annotate them.
• 'recognize_objects.py' : Object recognition class for pre-annotating images before manual annotation process.
• 'config.ini' : Edit data folder, output folder and label file path according to your preference. 'annotation_index' is automatically updated based on index of the last saved annotated image.
• 'labels.csv' : List of all the classes to be annotated.
• '/models' : It contains YOLOv3-608 weights (to be downloaded), cfg and coco.names files.
• '/data' : Sample of input images to be annotated
• '/output' : Sample of output files after annotation.

Usage:

python yolo_annotation_tool.py

Key buttons:

• 'S' : Save annotations
• 'L' : Change current class of labeling
• 'Esc' : Exit the code

Input images

Image 1	Image 2	Image 3

Output images (Pre-annotation)

Image 1	Image 2	Image 3