Labelme2YOLO
Forked from rooneysh/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 v7.0 segmentation)
- Now you can choose the output format of the label text. The two available alternatives are
polygonand bounding box (bbox).
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 0.2 means 20% 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, 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
2. Converting JSON files and splitting training and validation datasets by folders
If you have split the LabelMe training dataset and validation dataset on your own, please put these folders under labelme_json_dir as shown below:
/path/to/labelme_json_dir/train/
/path/to/labelme_json_dir/val/
This tool will read the training and validation datasets by folder. You may run the following command to do this:
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
How to build package/wheel
- install hatch
- Run the following command:
hatch build
License
labelme2yolo is distributed under the terms of the MIT license.
1 maintainer
Metadata
1 maintainer
Release files for labelme2yolo 0.1.4
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Total release size: 24.5 kB
Release files / labelme2yolo-0.1.4.tar.gz
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