Comments (4)
Everything is correct here. These are examples of special kind of annotations called "crowd regions". The annotations has field 'iscrowd' set to 1. They represent groups of objects (that are usually hard to split) rather than a single instance. You can find more information about the crowd regions in COCO data format page. Note that original COCO data for instance segmentation has the same regions as well.
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Got it. Thanks. The annotations still look very weird though, especially 000000005586.png.
Another question: I insert assert semantic.min() > 0
at line 34 on semantic_data.py
and the scripts fails from the start. So not all pixels are annotated?
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You are right. Some pixels do not have labels at all. They were not annotated or they belong to the stuff categories that we are ignoring. Please see coco panoptic evaluation (click on "merged or ignored") for more details about ignored categories.
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Got it. Thanks!
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Related Issues (20)
- evaluation
- KeyError: 'color' when running panoptic2detection_coco_format.py HOT 2
- Instance ID encoding discrepancy HOT 1
- Detection to Panoptic Segmenetaion Converter creates blank images and no segmenetation coordinates HOT 1
- How to specify instance mask in coco panoptic annotation format?
- where I can get images info in JSON file for COCO2017 datasets?
- Panoptic To Segmentation Converter Bug
- How to create pixel wise class-agnostic image segmentation? HOT 1
- Error when extracting semantic segmentation json from panoptic segmentation json HOT 2
- overlapping between annotations HOT 3
- How to use the result of panoptic segmentation to caculate the evaluation result of PQ metric data?
- how to visualize results for panoptic segmentation on test set
- TypeError: Object of type int64 is not JSON serializable HOT 16
- panoptic_coco_categories.json not found
- Does this work also with polygones, or only with RLE format? HOT 1
- ZeroDivisionError: division by zero
- About the stuff categories annotation.
- convert custom dataset to panoptic coco format
- KeyError when using detection2panoptic_coco_format
- How to make a panoramic segmentation dataset that contains both thing and stuff? HOT 1
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