SHI-Labs / OneFormer

OneFormer: One Transformer to Rule Universal Image Segmentation, arxiv 2022 / CVPR 2023
https://praeclarumjj3.github.io/oneformer
MIT License
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Class labels Issue #106

Closed Aki-Tomoya closed 6 months ago

Aki-Tomoya commented 7 months ago

When I use the coco dataset (133 classes) to make predictions on my images, I find that it merges some of the targets. For example, for three houses, it outputs building-other-merged. while this is a correct answer, I would like it to output one category for each identified target, i.e., for three houses, it outputs building three times. another example, the model will merge pavement and road as pavement-other-merged But I want it to output road and pavement. what should I do? Thanks in advance!