Comments (3)
Hello I understand your requirement @vincentlux . I have done some special work to handle images that don't have any annotations but it sounds like it is not working perfectly yet. Including a reference to the image in the coco file output sounds like the ideal behavior to me too.
Could you possibly share the dataset that you are using for testing (and your code as well) so that I can make sure it works for that type of dataset?
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Thanks for the quick reply! I currently don't have a public dataset with background images in hand... I want to add images without annotations because I am trying to add background images to object detection models to reduce False Positive cases. Adding this to YOLOv5 dataset is easy (just copy/paste images to the ./images folder), but then I got the problem I mentioned when converting to coco data format...
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Hello @vincentlux. I think this will work if you create an empty annotation files for each of the images. For example if you add background1.jpg create an annotation file called background1.txt. The file can be empty, with no labels.
Can you try that?
I read that link that you provided above and I think that even the yolo models will require the empty annotation files in order to include the background images when training. I saw a comment that said "No labels are required for background images." I think that means that no labels are required within the annotation files but the annotation files are still required.
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Related Issues (20)
- Crash when converting an image from COCO to YOLO that has no annotation in it HOT 1
- AttributeError: 'DataFrame' object has no attribute 'append' HOT 4
- is CreateML json format supported? HOT 5
- Error when i transform a COCO dataset to a YOLO dataset with segmentation = true and cat_id_index = 0 HOT 3
- It's possible to import YOLO segmentation dataset? HOT 2
- Annotation ids in '/content/test/img/coco128.json' are not unique! HOT 1
- StratifiedGroupShuffleSplit results in Empty DataFrame HOT 3
- yolo class label is unsorted HOT 1
- cat_id_index for yolov5 to coco format HOT 1
- how to edit yolo label with imported txt labels ? HOT 1
- UnboundLocalError: local variable 'categories' referenced before assignment HOT 2
- how to split YOLO datasets to train/val. Not train/val/test HOT 1
- Verbosity or progress bar HOT 5
- AssertionError: Output shape does not match input shape. Data loss has occured. HOT 4
- ShowClassSplits returning empty dataframe for YoloV5
- Class categories not correct after conversion from coco to yolo format. HOT 3
- Add tqdm to setup.py HOT 2
- Update Readme examples HOT 1
- Issue using both segmentation=True and cat_id_index=0 HOT 2
- YOLOv5 class index starts from 1 HOT 4
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