Tlaloc-Es / labelme2yolov7segmentation

Conver labelme annotation format to yolov7 annotation format for segmentation.

LabelMe2Yolov7Segmentation

Convert LabelMe format into YoloV7 format for instance segmentation.

Instalation

You can install labelme2yolov7segmentation from Pypi. It's going to install the library itself and its prerequisites as well.

pip install labelme2yolov7segmentation

You can install labelme2yolov7segmentation from its source code.

git clone https://github.com/Tlaloc-Es/labelme2yolov7segmentation.git
cd labelme2yolov7segmentation
pip install -e .

Usage

First of all, make your dataset with LabelMe, after that call to the following command

labelme2yolo --source-path /labelme/dataset --output-path /another/path

The arguments are:

• --source-path: That indicates the path where are the json output of LabelMe and their images, both will have been in the same folder
• --output-path: The path where you will save the converted files and a copy of the images following the yolov7 folder estructure

Expected output

If you execute the following command:

labelme2yolo --source-path /labelme/dataset --output-path /another/datasets

You will get something like this

datasets
├── images
│   ├── train
│   │   ├── img_1.jpg
│   │   ├── img_2.jpg
│   │   ├── img_3.jpg
│   │   ├── img_4.jpg
│   │   └── img_5.jpg
│   └── val
│       ├── img_6.jpg
│       └── img_7.jpg
├── labels
│   ├── train
│   │   ├── img_1.txt
│   │   ├── img_2.txt
│   │   ├── img_3.txt
│   │   ├── img_4.txt
│   │   └── img_5.txt
│   └── val
│       ├── img_6.txt
│       └── img_7.txt
├── labels.txt
├── test.txt
└── train.txt

Donation

If you want to contribute you can make a donation at https://www.buymeacoffee.com/tlaloc, thanks in advance