How to transfer yolo *.txt （the new segment） to *.json（labelme labeled segment）?

[KroitAax]

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How to transfer yolo *.txt （the new segment） to *.json（labelme labeled segment）?I hope everyone can give some tips, thank you.

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[glenn-jocher]

@KroitAax you can use the "labelme" Python library to convert YOLOv5 .txt annotation files to .json files. Labelme is a popular annotation tool that allows you to label, visualize, and convert annotations.

First, make sure you have the Labelme library installed. You can install it using pip:

pip install labelme

Once installed, you can run the following command to convert your YOLOv5 .txt files to .json:

labelme_convert yolo your_annotation_folder --json_dir converted_json_folder

Replace your_annotation_folder with the folder where your YOLOv5 .txt annotation files are located, and converted_json_folder with the folder where you want to store the converted .json files.

This command will convert each YOLOv5 .txt file into a .json file in the specified output directory.

Please note that the accuracy of the conversion will depend on the consistency and accuracy of the annotations in your YOLO .txt files.

I hope this helps! Let me know if you have any further questions.

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[DiogoFerreira77]

@KroitAax you can use the "labelme" Python library to convert YOLOv5 .txt annotation files to .json files. Labelme is a popular annotation tool that allows you to label, visualize, and convert annotations.

First, make sure you have the Labelme library installed. You can install it using pip:

pip install labelme

Once installed, you can run the following command to convert your YOLOv5 .txt files to .json:

labelme_convert yolo your_annotation_folder --json_dir converted_json_folder

Replace your_annotation_folder with the folder where your YOLOv5 .txt annotation files are located, and converted_json_folder with the folder where you want to store the converted .json files.

This command will convert each YOLOv5 .txt file into a .json file in the specified output directory.

Please note that the accuracy of the conversion will depend on the consistency and accuracy of the annotations in your YOLO .txt files.

I hope this helps! Let me know if you have any further questions.

I did that but it gives me the following error:
labelme_convert : The term 'labelme_convert' is not recognized as the name of a cmdlet, function, script file, or
operable program. Check the spelling of the name, or if a path was included, verify that the path is correct and try
again.
At line:1 char:1

• labelme_convert yolo C:\Users\diogo.ferreira\Desktop\Diogo_part2\labe ...

•   + CategoryInfo          : ObjectNotFound: (labelme_convert:String) [], CommandNotFoundException
    + FullyQualifiedErrorId : CommandNotFoundException
  
  

I created 2 virtual envs where one I did exactly like you said, and another that I used to install labelme from https://github.com/labelmeai/labelme. Both gave me the same error

[haozi04]

@KroitAax you can use the "labelme" Python library to convert YOLOv5 .txt annotation files to .json files. Labelme is a popular annotation tool that allows you to label, visualize, and convert annotations.

First, make sure you have the Labelme library installed. You can install it using pip:

pip install labelme

Once installed, you can run the following command to convert your YOLOv5 .txt files to .json:

labelme_convert yolo your_annotation_folder --json_dir converted_json_folder

Replace your_annotation_folder with the folder where your YOLOv5 .txt annotation files are located, and converted_json_folder with the folder where you want to store the converted .json files.

This command will convert each YOLOv5 .txt file into a .json file in the specified output directory.

Please note that the accuracy of the conversion will depend on the consistency and accuracy of the annotations in your YOLO .txt files.

I hope this helps! Let me know if you have any further questions.

Sounds like garbage generated from GPTs.

[Abonia1]

Hello,
Recently I was searching for similar functionality.I haven't find anything for segmentation task.

So, I have recently released open source, yolosegment2labelme is a library designed to transform YOLO segmentation masks into a format compatible with annotation tools such as LabelMe and Anylabeling, simplifying the annotation process for image segmentation tasks.

pip install yolosegment2labelme

Hope this helps.

[glenn-jocher]

Hello @Abonia1,

Thanks for sharing your solution with the community! It's great to see such initiatives that help bridge functionalities between different tools. Users looking for converting YOLO segmentation masks to LabelMe compatible formats might find your library very useful. Keep up the good work! 🚀

For everyone else following this thread, please make sure to review the library and test it with sample data to ensure compatibility with your specific requirements. Happy coding!