Open matejfric opened 1 year ago
Similarly, I am unable to load CVAT-exported "COCO 1.0"-formatted datasets with detectron2's COCO data loader. There is no indication of why the annotations are unusable; the images are just dropped without explanation. The data looks fine when loading it manually using pycocotools.
[12/05 01:13:47 d2.data.datasets.coco]: Loaded 100 images in COCO format from dataset/annotations/instances_default.json [12/05 01:13:47 d2.data.build]: Removed 100 images with no usable annotations. 0 images left.
I am facing the same issue; has there been a resolution yet?
Same here
same
I am having the same issue, anyone figured out what is wrong with COCO annotations exported from CVAT?
I'm trying to apply instance segmentation to images of the wood piles:
The dataset I'm using was annotated in CVAT and then exported to COCO 1.0 format. The problem is that in most cases the "iscrowd" parameter is set to 1 (true), and when there are no cases with the "iscrowd" parameter set to 0, the training fails with an error. Please see Logs and Google Colab notebook in sections below.
Note that when there are some "iscrowd": 0 attributes in the exported annotations, the training successfuly finishes, but the number of instances in the training log is equal to the number of instances with "iscrowd" attribute set to zero.
So the question is: Is this a desirable behaviour? Can I do something about it? I would be grateful for any suggestions. Given the nature of my data and the difficulty of annotating it, I would like to train the model on as many instances as possible.
Instructions To Reproduce the Issue:
Please see this notebook on Google Colab
Logs or other relevant observations:
This is the output when there are no cases with the "iscrowd" parameter set to 0.
If I manually change at least one of the "iscrowd" attributes to 0 (false), another error is raised:
Environment: