# LabelMe2Yolov7Segmentation
This repository was designed in order to label images using [LabelMe](https://github.com/wkentaro/labelme) and transform to [YoloV7](https://github.com/WongKinYiu/yolov7) format for instance segmentation
## Instalation
`pip install labelme2yolov7segmentation`
## 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
```bash
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
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"description": "# LabelMe2Yolov7Segmentation\n\nThis repository was designed in order to label images using [LabelMe](https://github.com/wkentaro/labelme) and transform to [YoloV7](https://github.com/WongKinYiu/yolov7) format for instance segmentation\n\n## Instalation\n\n`pip install labelme2yolov7segmentation`\n\n## Usage\n\nFirst of all, make your dataset with LabelMe, after that call to the following command\n\n`labelme2yolo --source-path /labelme/dataset --output-path /another/path`\n\nThe arguments are:\n\n* `--source-path`: That indicates the path where are the json output of LabelMe and their images, both will have been in the same folder\n* `--output-path`: The path where you will save the converted files and a copy of the images following the yolov7 folder estructure\n\n### Expected output\n\nIf you execute the following command:\n\n`labelme2yolo --source-path /labelme/dataset --output-path /another/datasets`\n\nYou will get something like this\n\n```bash\ndatasets\n\u251c\u2500\u2500 images\n\u2502 \u251c\u2500\u2500 train\n\u2502 \u2502 \u251c\u2500\u2500 img_1.jpg\n\u2502 \u2502 \u251c\u2500\u2500 img_2.jpg\n\u2502 \u2502 \u251c\u2500\u2500 img_3.jpg\n\u2502 \u2502 \u251c\u2500\u2500 img_4.jpg\n\u2502 \u2502 \u2514\u2500\u2500 img_5.jpg\n\u2502 \u2514\u2500\u2500 val\n\u2502 \u251c\u2500\u2500 img_6.jpg\n\u2502 \u2514\u2500\u2500 img_7.jpg\n\u251c\u2500\u2500 labels\n\u2502 \u251c\u2500\u2500 train\n\u2502 \u2502 \u251c\u2500\u2500 img_1.txt\n\u2502 \u2502 \u251c\u2500\u2500 img_2.txt\n\u2502 \u2502 \u251c\u2500\u2500 img_3.txt\n\u2502 \u2502 \u251c\u2500\u2500 img_4.txt\n\u2502 \u2502 \u2514\u2500\u2500 img_5.txt\n\u2502 \u2514\u2500\u2500 val\n\u2502 \u251c\u2500\u2500 img_6.txt\n\u2502 \u2514\u2500\u2500 img_7.txt\n\u251c\u2500\u2500 labels.txt\n\u251c\u2500\u2500 test.txt\n\u2514\u2500\u2500 train.txt\n```\n\n## Donation\n\nIf you want to contribute you can make a donation at https://www.buymeacoffee.com/tlaloc, thanks in advance\n",
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