labelme-to-yolo
Convert LabelMe Annotation Format to YOLO Annotation Format for Segmentation
Science Score: 44.0%
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✓CITATION.cff file
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✓codemeta.json file
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○Scientific vocabulary similarity
Low similarity (8.6%) to scientific vocabulary
Keywords
Repository
Convert LabelMe Annotation Format to YOLO Annotation Format for Segmentation
Basic Info
- Host: GitHub
- Owner: Tlaloc-Es
- Language: Python
- Default Branch: master
- Homepage: https://pypi.org/project/labelme-to-yolo/
- Size: 66.4 KB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Topics
Metadata Files
README.md
LabelMe to Yolo
Convert LabelMe format into Ultralytics Yolo format for instance segmentation.
Installation 
You can install labelme-to-yolo from Pypi. It's going to install the library itself and its prerequisites as well.
bash
pip install labelme2yolo
You can install labelme2yolo from its source code.
bash
git clone https://github.com/Tlaloc-Es/labelme-to-yolo.git
cd labelme2yolo
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
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
└── project.yml
Donation
If you want to contribute you can make a donation at https://www.buymeacoffee.com/tlaloc, thanks in advance
Owner
- Name: Tlaloc-Es
- Login: Tlaloc-Es
- Kind: user
- Repositories: 3
- Profile: https://github.com/Tlaloc-Es
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - family-names: Tlaloc-Es title: "labelme-to-yolo" version: 0.1.0 date-released: 2024-29-12
GitHub Events
Total
- Push event: 6
- Create event: 1
Last Year
- Push event: 6
- Create event: 1
Packages
- Total packages: 1
-
Total downloads:
- pypi 33 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 2
- Total maintainers: 1
pypi.org: labelme-to-yolo
A tool to convert LabelMe dataset annotations into YOLO format for instance segmentation.
- Homepage: https://github.com/Tlaloc-Es/labelme-to-yolo
- Documentation: https://labelme-to-yolo.readthedocs.io/
- License: MIT
-
Latest release: 0.2.0
published about 1 year ago
Rankings
Maintainers (1)
Dependencies
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