Comments (9)
Hi, check this PR please: #46
absolutely spot on. i -really- dig label studio and this removes the last block for integration for me. thank you thank you thank you. can you provide a base structure for the dataset? obj.data, obj.names, img/imagelist.jpgs + img/txtlist.txts ?
**update on that, you get the notes.json by exporting from your project or you can manually make it by something like this:
{
"categories": [
{
"id": 0,
"name": "classname1"
},
{
"id": 1,
"name": "classname2"
},
{
"id": 2,
"name": "classname3"
}
],
"info": {
"year": 2021,
"version": "1.0",
"contributor": "Label Studio"
}
}
Additionally, place your txts in a labels dir and your images in an images dir near notes.json.
@makseq have you had a go at using yolo as a ml backend? just curious.
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@haviduck This is yolo structure.
I've updated codes, please, pull the latest changes.
- Now categories are taken from classes.txt (instead of notes.json).
- Labeling config for the project will be generated automatically.
YOLO export example:
images - 1.jpg - 2.jpg - ... labels - 1.txt - 2.txt classes.txt
classes.txt example
Airplane Car
perfect, thank you! im seeing some discrepancies, but i will do more research, before making a claim. thanks for swift and good support.
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issue was with my own shitty pseudolabeling :) works great, thanks a bunch!
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@haviduck PRs are highly appreciated!
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Hi, check this PR please: #46
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@smoreface I've added YOLO => LS Json format converter (see #46).
I would like to add this into our docs, what do you think about it? I'd even add this to our blog post about YOLO.
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@haviduck This is yolo structure.
I've updated codes, please, pull the latest changes.
- Now categories are taken from classes.txt (instead of notes.json).
- Labeling config for the project will be generated automatically.
YOLO export example:
images
- 1.jpg
- 2.jpg
- ...
labels
- 1.txt
- 2.txt
classes.txt
classes.txt example
Airplane
Car
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@haviduck Waiting for your feedback and details :)
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im not gonna complain about open source stuff, but some quick feedback, adding local storage along with a labelstudio json file isnt super intuitive. i found myself mounting my images then connecting them via the storace connector. the image url had a ?d paramater that my converted json didnt honor. its just a matter of search and replace, but it was a bit unclear until then. i couldnt sync the mount AND upload the json as it would duplicate tasks. id be more than happy to push a pr or help out if needed, just some feedback.
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Related Issues (20)
- Export polygons as PNG mask
- Python directions in README are wrong HOT 1
- YOLO, COCO export error
- Are there any Plans to support Object Tracking formats?
- Export of OCR task into COCO and YOLO doesn't work HOT 2
- Export to YOLO format for Video Annotation Doesn't work.
- Export columns selection
- What is the correct way to convert bbox from label studio to LayoutLMv3Processor bbox format?
- Oriented Bounding Box HOT 1
- RectangleLabels : x,y values inconsistent HOT 1
- YOLO import to LS doesnt import labels HOT 2
- The iter_from_dir that uses`json.load` in method convert_to_voc does not open the json file.
- bug in "iter_from_json_file" method
- export to yolov8 format HOT 4
- CONLL Conversion drops NER labels from token classification
- How to make YOLO RAW tag output format be converted to pre-annotated
- Unable to convert multi-class instance segmentation dataset from YOLO TXT format HOT 1
- Why can't I use BrushLabel and export it to VOC?
- It can not handle COCO type datasets that don't have segmentation annotations HOT 1
- Trying to import a Pascal VOC dataset type and it does not work HOT 1
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