labelme2yolo 0.2.1

This script converts the JSON format output by LabelMe to the text format required by YOLO serirs.

Labelme2YOLO

Labelme2YOLO is a powerful tool for converting LabelMe's JSON format to YOLOv5 dataset format. This tool can also be used for YOLOv5/YOLOv8 segmentation datasets, if you have already made your segmentation dataset with LabelMe, it is easy to use this tool to help convert to YOLO format dataset.

New Features

• export data as yolo polygon annotation (for YOLOv5 & YOLOV8 segmentation)
• Now you can choose the output format of the label text. The two available alternatives are polygon and bounding box bbox.

Performance

Labelme2YOLO is implemented in Rust, which makes it significantly faster than equivalent Python implementations. In fact, it can be up to 100 times faster, allowing you to process large datasets more efficiently.

Installation

pip install labelme2yolo

Arguments

--json_dir LabelMe JSON files folder path.

--val_size (Optional) Validation dataset size, for example 0.2 means 20% for validation.

--test_size (Optional) Test dataset size, for example 0.1 means 10% for Test.

--json_name (Optional) Convert single LabelMe JSON file.

--output_format (Optional) The output format of label.

--label_list (Optional) The pre-assigned category labels.

How to Use

1. Converting JSON files and splitting training, validation datasets

You may need to place all LabelMe JSON files under labelme_json_dir and then run the following command:

labelme2yolo --json_dir /path/to/labelme_json_dir/

This tool will generate dataset labels and images with YOLO format in different folders, such as

/path/to/labelme_json_dir/YOLODataset/labels/train/
/path/to/labelme_json_dir/YOLODataset/labels/val/
/path/to/labelme_json_dir/YOLODataset/images/train/
/path/to/labelme_json_dir/YOLODataset/images/val/
/path/to/labelme_json_dir/YOLODataset/dataset.yaml

2. Converting JSON files and splitting training, validation, and test datasets with --val_size and --test_size

You may need to place all LabelMe JSON files under labelme_json_dir and then run the following command:

labelme2yolo --json_dir /path/to/labelme_json_dir/ --val_size 0.15 --test_size 0.15

This tool will generate dataset labels and images with YOLO format in different folders, such as

/path/to/labelme_json_dir/YOLODataset/labels/train/
/path/to/labelme_json_dir/YOLODataset/labels/test/
/path/to/labelme_json_dir/YOLODataset/labels/val/
/path/to/labelme_json_dir/YOLODataset/images/train/
/path/to/labelme_json_dir/YOLODataset/images/test/
/path/to/labelme_json_dir/YOLODataset/images/val/
/path/to/labelme_json_dir/YOLODataset/dataset.yaml

How to build package/wheel

pip install maturin
maturin develop

License

labelme2yolo is distributed under the terms of the MIT license.