feat: Import yolo polygons. Includes conversion from bboxes to polygons if user is wishing to transition dataset. #257
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…s files and asserts
| [images.append(f'{dir_pth}/{img}') for img in dir_imgs] | ||
| if len(dir_lbls) > 0: | ||
| [labels.append(f'{dir_pth}/{lbl}') for lbl in dir_lbls] | ||
| for image, label in zip(images, labels): |
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There's no certainty that the images and labels lists will be in the same order, something like for image, label in zip(sorted(images), sorted(labels)) does the trick.
| # verify if current labels are boxes | ||
| # scan labels list for first non-empty label, peek contents, determine label type | ||
| for label in labels: | ||
| with open(labels[0]) as f: |
| else: | ||
| break # non-empty label found | ||
| logger.info(f'sample label: {sample_lbl}') | ||
| if len(sample_lbl) < 7: # Polygons expected to consist of 7 items. At least three x,y pairs + class |
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I could be wrong here, but I believe that sample_lbl will contain a list of strings, each one being the line of the label file (where lines are separate objects). To test whether the sample label has less than 7 fields you should test something like if len(sample_lbl[0].split(' ')) < 7
makseq
changed the title
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After careful consideration, we’ve determined that this is more of an improvement than a critical bug. Additionally, it seems to be an outdated request and hasn’t garnered much interest from the community. For these reasons, we will be closing this issue. We will continue developing the converter library as a part of Label Studio SDK. We appreciate your understanding and encourage you to submit your feedback, questions and suggestions here: |
Hi
This PR seamlessly integrates with the current yolo.py imports module.
Based on the yolo_type option, it modifies the content of the task json correspondingly.
Further, it allows: