tomascanivari/mask2former-swin-large-coco-instance-finetuned-buildings
Image Segmentation
•
0.2B
•
Updated
•
7
image_info
dict | annotations
listlengths 1
202
| PIL_image
imagewidth (px) 512
512
| PIL_annotation
imagewidth (px) 512
512
|
|---|---|---|---|
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] |
This dataset is a processed verison of the dataset of the Kaggle competition: https://www.kaggle.com/competitions/building-extraction-generalization-2024/. The original train and validation images and COCO annotations were resized to (512, 512). Then from the segmentations on the COCO annotations, a PIL_annotation file was created for each sample in which the Red channel corresponds to the semantic segmentation mask and the Green channel to the instance segmentation mask. A PIL_image file is also delivered in the dataset for each sample, so it can be downloaded directly without the need of local files.
Note: in the test split, the 'annotations' and 'PIL_annotations' columns are placeholders.
Each split includes:
image_info: original coco metadata with filename, width, and height annotations: original coco annotations formatPIL_image: image PIL_annotation: masks