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j-min commited on Jul 21

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 ## Summary
 LayoutBench-COCO is a diagnostic benchmark that examines layout-guided image generation models on arbitrary, unseen layouts.
-Instead of [LayoutBench](https://huggingface.co/datasets/j-min/layoutbench), LayoutBench-COCO consists of OOD layouts of real objects and suports zero-shot evaluation.
 LayoutBench-COCO measures 4 skills (Number, Position, Size, Combination), whose objects are from [MS COCO](https://cocodataset.org/).
 The new 'combination’ split consists of layouts with two objects in different spatial relations, and the remaining three splits are similar to those of LayoutBench.

 ## Summary
 LayoutBench-COCO is a diagnostic benchmark that examines layout-guided image generation models on arbitrary, unseen layouts.
+Unlike [LayoutBench](https://huggingface.co/datasets/j-min/layoutbench), LayoutBench-COCO consists of OOD layouts of real objects and suports zero-shot evaluation.
 LayoutBench-COCO measures 4 skills (Number, Position, Size, Combination), whose objects are from [MS COCO](https://cocodataset.org/).
 The new 'combination’ split consists of layouts with two objects in different spatial relations, and the remaining three splits are similar to those of LayoutBench.