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* **[roboflow/rf-detr-medium](https://huggingface.co/Roboflow/rf-detr-medium)**: rf-detr is an end-to-end object detection model that combines ideas from lw-detr and deformable detr: a dinov2-with-registers-style vit backbone (with an rf-detr windowing pattern for efficient attention), a multi-scale projector between the encoder and decoder, and a multi-scale deformable detr decoder for fast convergence and strong accuracy-latency tradeoffs.
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* **[mobile ui design detection](https://huggingface.co/datasets/mrtoy/mobile-ui-design)** by **[mrtoy](https://huggingface.co/mrtoy)**: this dataset is designed for object detection tasks focused on detecting elements in mobile ui designs. the target objects include text, images, and groups. the dataset contains mobile ui images with object detection bounding boxes, class labels, and localization information.
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* **[roboflow/rf-detr-medium](https://huggingface.co/Roboflow/rf-detr-medium)**: rf-detr is an end-to-end object detection model that combines ideas from lw-detr and deformable detr: a dinov2-with-registers-style vit backbone (with an rf-detr windowing pattern for efficient attention), a multi-scale projector between the encoder and decoder, and a multi-scale deformable detr decoder for fast convergence and strong accuracy-latency tradeoffs.
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* **[mobile ui design detection[dataset]](https://huggingface.co/datasets/mrtoy/mobile-ui-design)** by **[mrtoy](https://huggingface.co/mrtoy)**: this dataset is designed for object detection tasks focused on detecting elements in mobile ui designs. the target objects include text, images, and groups. the dataset contains mobile ui images with object detection bounding boxes, class labels, and localization information.
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