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Help converting LabelMe Annotation Tool JSON format to YOLO text file format. If you've already marked your segmentation dataset by LabelMe, it's easy to use this tool to help converting to YOLO format dataset.

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Labelme2YOLO

Help converting LabelMe Annotation Tool JSON format to YOLO text file format. If you've already marked your segmentation dataset by LabelMe, it's easy to use this tool to help converting to YOLO format dataset.

Parameters Explain

--json_dir LabelMe JSON files folder path.

--val_size (Optional) Validation dataset size, for example 0.2 means 20% for validation and 80% for training. Default value is 0.1 .

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

--seg (Optional) Convert to YOLOv5 v7.0 instance segmentation dataset.

How to Use

1. Convert JSON files, split training and validation dataset by --val_size

Put all LabelMe JSON files under labelme_json_dir, and run this python command.

python labelme2yolo.py --json_dir /home/username/labelme_json_dir/ --val_size 0.2

Script would generate YOLO format dataset labels and images under different folders, for example,

# when specifying `--seg', "YOLODataset" will be "YOLODataset_seg"
/home/username/labelme_json_dir/YOLODataset/labels/train/
/home/username/labelme_json_dir/YOLODataset/labels/val/
/home/username/labelme_json_dir/YOLODataset/images/train/
/home/username/labelme_json_dir/YOLODataset/images/val/

/home/username/labelme_json_dir/YOLODataset/dataset.yaml

2. Convert JSON files, split training and validation dataset by folder

If you already split train dataset and validation dataset for LabelMe by yourself, please put these folder under labelme_json_dir, for example,

/home/username/labelme_json_dir/train/
/home/username/labelme_json_dir/val/

Put all LabelMe JSON files under labelme_json_dir. Script would read train and validation dataset by folder. Run this python command.

python labelme2yolo.py --json_dir /home/username/labelme_json_dir/

Script would generate YOLO format dataset labels and images under different folders, for example,

# when specifying `--seg', "YOLODataset" will be "YOLODataset_seg"
/home/username/labelme_json_dir/YOLODataset/labels/train/
/home/username/labelme_json_dir/YOLODataset/labels/val/
/home/username/labelme_json_dir/YOLODataset/images/train/
/home/username/labelme_json_dir/YOLODataset/images/val/

/home/username/labelme_json_dir/YOLODataset/dataset.yaml

3. Convert single JSON file

Put LabelMe JSON file under labelme_json_dir. , and run this python command.

python labelme2yolo.py --json_dir /home/username/labelme_json_dir/ --json_name 2.json

Script would generate YOLO format text label and image under labelme_json_dir, for example,

/home/username/labelme_json_dir/2.text
/home/username/labelme_json_dir/2.png

Only tested on Centos 7/Python 3.6 environment.

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Help converting LabelMe Annotation Tool JSON format to YOLO text file format. If you've already marked your segmentation dataset by LabelMe, it's easy to use this tool to help converting to YOLO format dataset.

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