delilovic / supervisely_yolo

Script to convert Supervisely to Yolo (Darknet) data structure/format and vice versa

supervisely_yolo.py

(Script to convert Supervisely to Yolo (Darknet) data structure/format and vice versa)

• If you convert from Yolo to Supervisely (supervisely_yolo -t y2s) then you need to install the OpenCV python package: pip install opencv-python

• You can specify the location of your source dataset using -p flag

  • example 1 => python supervisely_yolo.py -p C:\yolo -t y2s
  • example 2 => python supvervisely_yolo.py -p C:\Users\Delilovic\Desktop ([-t s2y] is not required as it is the default flag)

• You can specify if you want to skip copying images from the source to the destination dataset with the -s flag

  • WARNING: consider using this flag if you have a lot of images and might run out of space

• When downloading images from Supervisely, images get the extension attached to their names

  • e.g. downloading foo.jpg gets renamed as foo.jpg.jpg
  • this behaviour is handled by the supervisely_yolo.py script, but it also means you can not currently convert Supervisely data structure created by y2s flag back to Yolo data using the s2y flag (this shouldn't be a use case anyway but is worth mentioning here)

Required Folder Structure

• Please follow this structure strictly
  • you can not have two different Supervisely datasets at the moment (if you do, put everything into the dataset folder)
  • you can not have Yolo images and labels in one folder (if you do, separate them into labels and images folder)
  • data structure is case sensitive (e.g. yolo can not be Yolo)

Supervisely (-t s2y)

├── supervisely
    ├── meta.json
    └── dataset1
        ├── img
        │    ├── any_name.jpg or(.jpeg, .png)
        │    └── ...
        └── ann
            ├── any_name.json
            └── ...
    └── dataset2
        ├── img
        │    ├── any_name.jpg or(.jpeg, .png)
        │    └── ...
        └── ann
            ├── any_name.json
            └── ...

Yolo (-t y2s)

├── yolo
    ├── data.yaml
    ├── images
    │   ├── any_name.jpg or(.jpeg, .png)
    │   └── ...
    └── labels
        ├── any_name.txt
        └── ...

Contributions

• This is the first version and many updates will be required, everybody interested is gladly invited to contribute

supervisely_yolo's Issues

"There should be a folder "supervisely" at /home/myName/supervisely_yolo\"

I am trying to run the examples (both supervisely_to_yolo and reverse) and I get this error. I have copied of course the files from the example/ directory into the root, but this error still persists. One thing that is weird the the "" character at the end of the path name in the error message. My path is /home/myName/supervisely_yolo/...
The contents of this directory are :
~/supervisely_yolo$ dir
output: examples LICENSE README.md supervisely supervisely_yolo.py yolo
So as you can see, the two files (supervisely and yolo) are in the root directory.
That said, when running python3 supervisely_yolo.py It returns:
Error [meta.json not found] => There should be a folder "supervisely" at /home/myName/supervisely_yolo\

Any thoughts on this issue?

Converts only the first line in the txt file

Hi. Thanks for your code.

But it would be much more helpful if you can convert multiple bounding boxes. Your code converted only the first line of the YOLO annotation file.