Convert LabelMe format into YoloV7 format for instance segmentation.
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 .
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 estructureIf 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
If you want to contribute you can make a donation at https://www.buymeacoffee.com/tlaloc, thanks in advance