Split (1)

train · 658 rows

model_id stringlengths 12 92	model_card stringlengths 166 900k	model_labels listlengths 2 250
nvidia/segformer-b1-finetuned-ade-512-512	# SegFormer (b1-sized) model fine-tuned on ADE20k SegFormer model fine-tuned on ADE20k at resolution 512x512. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this repository](http...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...
jonathandinu/face-parsing	# Face Parsing ![example image and output](demo.png) [Semantic segmentation](https://huggingface.co/docs/transformers/tasks/semantic_segmentation) model fine-tuned from [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) with [CelebAMask-HQ](https://github.com/switchablenorms/CelebAMask-HQ) for face parsing. For a...	[ "background", "skin", "nose", "eye_g", "l_eye", "r_eye", "l_brow", "r_brow", "l_ear", "r_ear", "mouth", "u_lip", "l_lip", "hair", "hat", "ear_r", "neck_l", "neck", "cloth" ]
facebook/mask2former-swin-tiny-coco-instance	# Mask2Former Mask2Former model trained on COCO instance segmentation (tiny-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookresearch/...	[ "person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrell...
facebook/mask2former-swin-large-ade-semantic	# Mask2Former Mask2Former model trained on ADE20k semantic segmentation (large-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookresear...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...
isjackwild/segformer-b0-finetuned-segments-skin-hair-clothing	# Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1). ## Mod...	[ "background", "skin", "hair", "clothing" ]
facebook/detr-resnet-101-panoptic	# DETR (End-to-End Object Detection) model with ResNet-101 backbone DEtection TRansformer (DETR) model trained end-to-end on COCO 2017 panoptic (118k annotated images). It was introduced in the paper [End-to-End Object Detection with Transformers](https://arxiv.org/abs/2005.12872) by Carion et al. and first released ...	[ "n/a", "person", "traffic light", "cardboard", "carpet", "ceiling-other", "ceiling-tile", "cloth", "clothes", "clouds", "counter", "cupboard", "curtain", "fire hydrant", "desk-stuff", "dirt", "door-stuff", "fence", "floor-marble", "floor-other", "floor-stone", "floor-tile",...
facebook/detr-resnet-50-dc5-panoptic	# DETR (End-to-End Object Detection) model with ResNet-50 backbone (dilated C5 stage) DEtection TRansformer (DETR) model trained end-to-end on COCO 2017 panoptic (118k annotated images). It was introduced in the paper [End-to-End Object Detection with Transformers](https://arxiv.org/abs/2005.12872) by Carion et al. a...	[ "n/a", "person", "traffic light", "cardboard", "carpet", "ceiling-other", "ceiling-tile", "cloth", "clothes", "clouds", "counter", "cupboard", "curtain", "fire hydrant", "desk-stuff", "dirt", "door-stuff", "fence", "floor-marble", "floor-other", "floor-stone", "floor-tile",...
facebook/detr-resnet-50-panoptic	# DETR (End-to-End Object Detection) model with ResNet-50 backbone DEtection TRansformer (DETR) model trained end-to-end on COCO 2017 panoptic (118k annotated images). It was introduced in the paper [End-to-End Object Detection with Transformers](https://arxiv.org/abs/2005.12872) by Carion et al. and first released i...	[ "n/a", "person", "traffic light", "cardboard", "carpet", "ceiling-other", "ceiling-tile", "cloth", "clothes", "clouds", "counter", "cupboard", "curtain", "fire hydrant", "desk-stuff", "dirt", "door-stuff", "fence", "floor-marble", "floor-other", "floor-stone", "floor-tile",...
facebook/maskformer-swin-base-ade	# MaskFormer MaskFormer model trained on ADE20k semantic segmentation (base-sized version, Swin backbone). It was introduced in the paper [Per-Pixel Classification is Not All You Need for Semantic Segmentation](https://arxiv.org/abs/2107.06278) and first released in [this repository](https://github.com/facebookresear...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road, route", "bed", "window ", "grass", "cabinet", "sidewalk, pavement", "person", "earth, ground", "door", "table", "mountain, mount", "plant", "curtain", "chair", "car", "water", "painting, picture", "sofa", "...
facebook/maskformer-swin-base-coco	# MaskFormer MaskFormer model trained on COCO panoptic segmentation (base-sized version, Swin backbone). It was introduced in the paper [Per-Pixel Classification is Not All You Need for Semantic Segmentation](https://arxiv.org/abs/2107.06278) and first released in [this repository](https://github.com/facebookresearch...	[ "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrell...
facebook/maskformer-swin-large-ade	# MaskFormer MaskFormer model trained on ADE20k semantic segmentation (large-sized version, Swin backbone). It was introduced in the paper [Per-Pixel Classification is Not All You Need for Semantic Segmentation](https://arxiv.org/abs/2107.06278) and first released in [this repository](https://github.com/facebookresea...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road, route", "bed", "window ", "grass", "cabinet", "sidewalk, pavement", "person", "earth, ground", "door", "table", "mountain, mount", "plant", "curtain", "chair", "car", "water", "painting, picture", "sofa", "...
facebook/maskformer-swin-large-coco	# MaskFormer MaskFormer model trained on COCO panoptic segmentation (large-sized version, Swin backbone). It was introduced in the paper [Per-Pixel Classification is Not All You Need for Semantic Segmentation](https://arxiv.org/abs/2107.06278) and first released in [this repository](https://github.com/facebookresearc...	[ "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrell...
facebook/maskformer-swin-small-ade	# MaskFormer MaskFormer model trained on ADE20k semantic segmentation (small-sized version, Swin backbone). It was introduced in the paper [Per-Pixel Classification is Not All You Need for Semantic Segmentation](https://arxiv.org/abs/2107.06278) and first released in [this repository](https://github.com/facebookresea...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road, route", "bed", "window ", "grass", "cabinet", "sidewalk, pavement", "person", "earth, ground", "door", "table", "mountain, mount", "plant", "curtain", "chair", "car", "water", "painting, picture", "sofa", "...
facebook/maskformer-swin-small-coco	# MaskFormer MaskFormer model trained on COCO panoptic segmentation (small-sized version, Swin backbone). It was introduced in the paper [Per-Pixel Classification is Not All You Need for Semantic Segmentation](https://arxiv.org/abs/2107.06278) and first released in [this repository](https://github.com/facebookresearc...	[ "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrell...
facebook/maskformer-swin-tiny-ade	# MaskFormer MaskFormer model trained on ADE20k semantic segmentation (tiny-sized version, Swin backbone). It was introduced in the paper [Per-Pixel Classification is Not All You Need for Semantic Segmentation](https://arxiv.org/abs/2107.06278) and first released in [this repository](https://github.com/facebookresear...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road, route", "bed", "window ", "grass", "cabinet", "sidewalk, pavement", "person", "earth, ground", "door", "table", "mountain, mount", "plant", "curtain", "chair", "car", "water", "painting, picture", "sofa", "...
facebook/maskformer-swin-tiny-coco	# MaskFormer MaskFormer model trained on COCO panoptic segmentation (tiny-sized version, Swin backbone). It was introduced in the paper [Per-Pixel Classification is Not All You Need for Semantic Segmentation](https://arxiv.org/abs/2107.06278) and first released in [this repository](https://github.com/facebookresearch...	[ "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrell...
microsoft/beit-base-finetuned-ade-640-640	# BEiT (base-sized model, fine-tuned on ADE20k) BEiT model pre-trained in a self-supervised fashion on ImageNet-21k (14 million images, 21,841 classes) at resolution 224x224, and fine-tuned on [ADE20k](http://sceneparsing.csail.mit.edu/) (an important benchmark for semantic segmentation of images) at resolution 640x...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...
microsoft/beit-large-finetuned-ade-640-640	# BEiT (large-sized model, fine-tuned on ADE20k) BEiT model pre-trained in a self-supervised fashion on ImageNet-21k (14 million images, 21,841 classes) at resolution 224x224, and fine-tuned on [ADE20k](https://huggingface.co/datasets/scene_parse_150) (an important benchmark for semantic segmentation of images) at r...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...
Intel/dpt-large-ade	# DPT (large-sized model) fine-tuned on ADE20k The model is used for semantic segmentation of input images such as seen in the table below: \| Input Image \| Output Segmented Image \| \| --- \| --- \| \| ![input image](https://cdn-uploads.huggingface.co/production/uploads/641bd18baebaa27e0753f2c9/cG0alacJ4MeSL18CneD2u.p...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...
nvidia/segformer-b0-finetuned-ade-512-512	# SegFormer (b0-sized) model fine-tuned on ADE20k SegFormer model fine-tuned on ADE20k at resolution 512x512. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this repository](http...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...
nvidia/segformer-b0-finetuned-cityscapes-1024-1024	# SegFormer (b0-sized) model fine-tuned on CityScapes SegFormer model fine-tuned on CityScapes at resolution 1024x1024. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this reposi...	[ "road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
nvidia/segformer-b0-finetuned-cityscapes-512-1024	# SegFormer (b4-sized) model fine-tuned on CityScapes SegFormer model fine-tuned on CityScapes at resolution 512x1024. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this reposit...	[ "road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
nvidia/segformer-b0-finetuned-cityscapes-640-1280	# SegFormer (b5-sized) model fine-tuned on CityScapes SegFormer model fine-tuned on CityScapes at resolution 640x1280. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this reposit...	[ "road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
nvidia/segformer-b0-finetuned-cityscapes-768-768	# SegFormer (b0-sized) model fine-tuned on CityScapes SegFormer model fine-tuned on CityScapes at resolution 768x768. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this reposito...	[ "road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
nvidia/segformer-b1-finetuned-cityscapes-1024-1024	# SegFormer (b1-sized) model fine-tuned on CityScapes SegFormer model fine-tuned on CityScapes at resolution 1024x1024. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this reposi...	[ "road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
nvidia/segformer-b2-finetuned-ade-512-512	# SegFormer (b2-sized) model fine-tuned on ADE20k SegFormer model fine-tuned on ADE20k at resolution 512x512. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this repository](http...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...
nvidia/segformer-b2-finetuned-cityscapes-1024-1024	# SegFormer (b2-sized) model fine-tuned on CityScapes SegFormer model fine-tuned on CityScapes at resolution 1024x1024. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this reposi...	[ "road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
nvidia/segformer-b3-finetuned-ade-512-512	# SegFormer (b3-sized) model fine-tuned on ADE20k SegFormer model fine-tuned on ADE20k at resolution 512x512. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this repository](http...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...
nvidia/segformer-b3-finetuned-cityscapes-1024-1024	# SegFormer (b3-sized) model fine-tuned on CityScapes SegFormer model fine-tuned on CityScapes at resolution 1024x1024. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this reposi...	[ "road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
nvidia/segformer-b4-finetuned-ade-512-512	# SegFormer (b4-sized) model fine-tuned on ADE20k SegFormer model fine-tuned on ADE20k at resolution 512x512. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this repository](http...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...
nvidia/segformer-b4-finetuned-cityscapes-1024-1024	# SegFormer (b4-sized) model fine-tuned on CityScapes SegFormer model fine-tuned on CityScapes at resolution 1024x1024. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this reposi...	[ "road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
nvidia/segformer-b5-finetuned-ade-640-640	# SegFormer (b5-sized) model fine-tuned on ADE20k SegFormer model fine-tuned on ADE20k at resolution 640x640. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this repository](http...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...
nvidia/segformer-b5-finetuned-cityscapes-1024-1024	# SegFormer (b5-sized) model fine-tuned on CityScapes SegFormer model fine-tuned on CityScapes at resolution 1024x1024. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this reposi...	[ "road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
tobiasc/segformer-b0-finetuned-segments-sidewalk	# SegFormer (b0-sized) model fine-tuned on Segments.ai sidewalk-semantic. SegFormer model fine-tuned on [Segments.ai](https://segments.ai) [`sidewalk-semantic`](https://huggingface.co/datasets/segments/sidewalk-semantic). It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation w...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
tobiasc/segformer-b3-finetuned-segments-sidewalk	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b3-finetuned-segments-sidewalk This model is a fine-tuned version of [nvidia/mit-b3](https://huggingface.co/nvidia/mit...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
nielsr/segformer-b0-finetuned-segments-sidewalk	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-finetuned-segments-sidewalk This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
nickmuchi/segformer-b4-finetuned-segments-sidewalk	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b4-finetuned-segments-sidewalk This model is a fine-tuned version of [nvidia/mit-b4](https://huggingface.co/nvidia/mit...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
nielsr/segformer-finetuned-sidewalk	# Segformer-b0, fine-tuned on Sidewalk This repository contains the weights of a `SegFormerForSemanticSegmentation` model. It was trained using the example script.	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
nielsr/sidewalk-semantic-demo	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # sidewalk-semantic-demo This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the None d...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
hufanyoung/segformer-b0-finetuned-segments-sidewalk-2	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-finetuned-segments-sidewalk-2 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/m...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
nielsr/segformer-trainer-test	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-trainer-test This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the segmen...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
nielsr/segformer-trainer-test-bis	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-trainer-test-bis This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the se...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
nielsr/segformer-finetuned-sidewalk-10k-steps	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-finetuned-sidewalk-50-epochs This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
Matthijs/deeplabv3-mobilevit-small	# MobileViT + DeepLabV3 (small-sized model) MobileViT model pre-trained on PASCAL VOC at resolution 512x512. It was introduced in [MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer](https://arxiv.org/abs/2110.02178) by Sachin Mehta and Mohammad Rastegari, and first released in [this rep...	[ "background", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow", "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor" ]
reannayang/segformer-b0-pavement	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-pavement This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the reannay...	[ "rumble strips", "tree", "through lane", "car", "grass", "curb" ]
jakka/segformer-b0-finetuned-segments-sidewalk-4	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-finetuned-segments-sidewalk-4 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/m...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
apple/deeplabv3-mobilevit-small	# MobileViT + DeepLabV3 (small-sized model) MobileViT model pre-trained on PASCAL VOC at resolution 512x512. It was introduced in [MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer](https://arxiv.org/abs/2110.02178) by Sachin Mehta and Mohammad Rastegari, and first released in [this rep...	[ "background", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow", "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor" ]
apple/deeplabv3-mobilevit-x-small	# MobileViT + DeepLabV3 (extra small-sized model) MobileViT model pre-trained on PASCAL VOC at resolution 512x512. It was introduced in [MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer](https://arxiv.org/abs/2110.02178) by Sachin Mehta and Mohammad Rastegari, and first released in [th...	[ "background", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow", "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor" ]
apple/deeplabv3-mobilevit-xx-small	# MobileViT + DeepLabV3 (extra extra small-sized model) MobileViT model pre-trained on PASCAL VOC at resolution 512x512. It was introduced in [MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer](https://arxiv.org/abs/2110.02178) by Sachin Mehta and Mohammad Rastegari, and first released ...	[ "background", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow", "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor" ]
malra/segformer-b0-finetuned-segments-sidewalk-4	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-finetuned-segments-sidewalk-4 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/m...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
malra/segformer-b5-segments-warehouse1	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b5-segments-warehouse1 This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on ...	[ "unlabeled", "klt_bin", "rack", "ceiling", "pillar", "wall", "floor", "sign", "box", "bracket", "barcode", "floor_decal", "fuse_box", "pallet", "lamp", "not-known-2", "wire", "fire_extinguisher", "crate", "cart" ]
jakka/segformer-b0-finetuned-warehouse-part-1-V2	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-finetuned-warehouse-part-1-V2 This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/m...	[ "unlabeled", "klt_bin", "rack", "ceiling", "pillar", "wall", "floor", "sign", "box", "bracket", "barcode", "floor_decal", "fuse_box", "pallet", "lamp", "not-known-2", "wire", "fire_extinguisher", "crate", "cart" ]
q2-jlbar/segformer-b0-finetuned-brooks-or-dunn	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-finetuned-brooks-or-dunn This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0...	[ "dunn", "other" ]
chainyo/segformer-sidewalk	# SegFormer (b0-sized) model fine-tuned on sidewalk-semantic dataset SegFormer model fine-tuned on segments/sidewalk-semantic at resolution 512x512. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and f...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
chainyo/segformer-b1-sidewalk	# SegFormer (b1-sized) model fine-tuned on sidewalk-semantic dataset SegFormer model fine-tuned on segments/sidewalk-semantic at resolution 512x512. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and f...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
Matthijs/deeplabv3_mobilenet_v2_1.0_513	# MobileNetV2 with DeepLabV3+ MobileNet V2 model pre-trained on PASCAL VOC at resolution 513x513. It was introduced in [MobileNetV2: Inverted Residuals and Linear Bottlenecks](https://arxiv.org/abs/1801.04381) by Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen. It was first released in [...	[ "background", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow", "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor" ]
userGagan/segformer-b0-finetuned-segments-sidewalk-2	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-finetuned-segments-sidewalk-2 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/m...	[ "sand", "soil", "bigrock" ]
imadd/segformer-b0-finetuned-segments-water-2	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-finetuned-segments-water-2 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-...	[ "water", "unlabeled" ]
sayakpaul/mit-b0-finetuned-sidewalk-semantic	<!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # mit-b0-finetuned-sidewalk-semantic This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an u...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
koushikn/segformer-finetuned-Maize-10k-steps-sem	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-finetuned-Maize-10k-steps-sem This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-...	[ "background", "maize" ]
plant/segformer-b5-finetuned-segments-instryde-foot-test	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b5-finetuned-segments-instryde-foot-test This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/...	[ "unlabeled", "foot" ]
kiheh85202/yolo	# DPT (large-sized model) fine-tuned on ADE20k Dense Prediction Transformer (DPT) model trained on ADE20k for semantic segmentation. It was introduced in the paper [Vision Transformers for Dense Prediction](https://arxiv.org/abs/2103.13413) by Ranftl et al. and first released in [this repository](https://github.com/i...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...
nishita/segformer-b0-finetuned-segments-sidewalk-2	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-finetuned-segments-sidewalk-2 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/m...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
shaheen1998/segformer-b0-finetuned-segments-sidewalk-2	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-finetuned-segments-sidewalk-2 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/m...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
kasumi222/segformer-b0-finetuned-busigt2	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-finetuned-busigt2 This model is a fine-tuned version of [nvidia/mit-b1](https://huggingface.co/nvidia/mit-b1) on th...	[ "unlabeled", "maligno", "benigno" ]
lapix/segformer-b3-finetuned-ccagt-400-300	# SegFormer (b3-sized) model fine-tuned on CCAgT dataset SegFormer model fine-tuned on CCAgT dataset at resolution 400x300. It was introduced in the paper [Semantic Segmentation for the Detection of Very Small Objects on Cervical Cell Samples Stained with the {AgNOR} Technique](https://doi.org/10.2139/ssrn.4126881) b...	[ "background", "nucleus", "cluster", "satellite", "nucleus_out_of_focus", "overlapped_nuclei", "non_viable_nucleus", "leukocyte_nucleus" ]
zoheb/mit-b5-finetuned-sidewalk-semantic	# SegFormer (b5-sized) model fine-tuned on sidewalk-semantic dataset. SegFormer model fine-tuned on SegmentsAI [`sidewalk-semantic`](https://huggingface.co/datasets/segments/sidewalk-semantic). It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://a...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
matnun/segformer-b0-finetuned-segments-sidewalk-2	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-finetuned-segments-sidewalk-2 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/m...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
irfan-noordin/segformer-b0-finetuned-segments-sidewalk-oct-22	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-finetuned-segments-sidewalk-oct-22 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvi...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
google/deeplabv3_mobilenet_v2_1.0_513	# MobileNetV2 with DeepLabV3+ MobileNet V2 model pre-trained on PASCAL VOC at resolution 513x513. It was introduced in [MobileNetV2: Inverted Residuals and Linear Bottlenecks](https://arxiv.org/abs/1801.04381) by Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen. It was first released in [...	[ "background", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow", "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor" ]
shi-labs/oneformer_ade20k_swin_large	# OneFormer OneFormer model trained on the ADE20k dataset (large-sized version, Swin backbone). It was introduced in the paper [OneFormer: One Transformer to Rule Universal Image Segmentation](https://arxiv.org/abs/2211.06220) by Jain et al. and first released in [this repository](https://github.com/SHI-Labs/OneForme...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road, route", "bed", "window ", "grass", "cabinet", "sidewalk, pavement", "person", "earth, ground", "door", "table", "mountain, mount", "plant", "curtain", "chair", "car", "water", "painting, picture", "sofa", "...
shi-labs/oneformer_cityscapes_swin_large	# OneFormer OneFormer model trained on the Cityscapes dataset (large-sized version, Swin backbone). It was introduced in the paper [OneFormer: One Transformer to Rule Universal Image Segmentation](https://arxiv.org/abs/2211.06220) by Jain et al. and first released in [this repository](https://github.com/SHI-Labs/OneF...	[ "road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
shi-labs/oneformer_coco_swin_large	# OneFormer OneFormer model trained on the COCO dataset (large-sized version, Swin backbone). It was introduced in the paper [OneFormer: One Transformer to Rule Universal Image Segmentation](https://arxiv.org/abs/2211.06220) by Jain et al. and first released in [this repository](https://github.com/SHI-Labs/OneFormer)...	[ "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrell...
shi-labs/oneformer_ade20k_dinat_large	# OneFormer OneFormer model trained on the ADE20k dataset (large-sized version, Dinat backbone). It was introduced in the paper [OneFormer: One Transformer to Rule Universal Image Segmentation](https://arxiv.org/abs/2211.06220) by Jain et al. and first released in [this repository](https://github.com/SHI-Labs/OneForm...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road, route", "bed", "window ", "grass", "cabinet", "sidewalk, pavement", "person", "earth, ground", "door", "table", "mountain, mount", "plant", "curtain", "chair", "car", "water", "painting, picture", "sofa", "...
shi-labs/oneformer_coco_dinat_large	# OneFormer OneFormer model trained on the COCO dataset (large-sized version, Dinat backbone). It was introduced in the paper [OneFormer: One Transformer to Rule Universal Image Segmentation](https://arxiv.org/abs/2211.06220) by Jain et al. and first released in [this repository](https://github.com/SHI-Labs/OneFormer...	[ "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrell...
shi-labs/oneformer_cityscapes_dinat_large	# OneFormer OneFormer model trained on the Cityscapes dataset (large-sized version, Dinat backbone). It was introduced in the paper [OneFormer: One Transformer to Rule Universal Image Segmentation](https://arxiv.org/abs/2211.06220) by Jain et al. and first released in [this repository](https://github.com/SHI-Labs/One...	[ "road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
shi-labs/oneformer_ade20k_swin_tiny	# OneFormer OneFormer model trained on the ADE20k dataset (tiny-sized version, Swin backbone). It was introduced in the paper [OneFormer: One Transformer to Rule Universal Image Segmentation](https://arxiv.org/abs/2211.06220) by Jain et al. and first released in [this repository](https://github.com/SHI-Labs/OneFormer...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road, route", "bed", "window ", "grass", "cabinet", "sidewalk, pavement", "person", "earth, ground", "door", "table", "mountain, mount", "plant", "curtain", "chair", "car", "water", "painting, picture", "sofa", "...
mattmdjaga/segformer_b2_clothes	# Segformer B2 fine-tuned for clothes segmentation SegFormer model fine-tuned on [ATR dataset](https://github.com/lemondan/HumanParsing-Dataset) for clothes segmentation but can also be used for human segmentation. The dataset on hugging face is called "mattmdjaga/human_parsing_dataset". **[Training code](https://git...	[ "background", "hat", "hair", "sunglasses", "upper-clothes", "skirt", "pants", "dress", "belt", "left-shoe", "right-shoe", "face", "left-leg", "right-leg", "left-arm", "right-arm", "bag", "scarf" ]
facebook/mask2former-swin-base-coco-instance	# Mask2Former Mask2Former model trained on COCO instance segmentation (base-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookresearch/...	[ "person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrell...
turcuciprian/segformer-b0-finetuned-segments-sidewalk-2	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-finetuned-segments-sidewalk-2 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/m...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
optimum/segformer-b0-finetuned-ade-512-512	# SegFormer (b0-sized) model fine-tuned on ADE20k SegFormer model fine-tuned on ADE20k at resolution 512x512. It was introduced in the paper [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://arxiv.org/abs/2105.15203) by Xie et al. and first released in [this repository](http...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...
facebook/mask2former-swin-small-coco-instance	# Mask2Former Mask2Former model trained on COCO instance segmentation (small-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookresearch...	[ "person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrell...
mnosouhi96/segformer-b0-finetuned-segments-sidewalk-2	<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # segformer-b0-finetuned-segments-sidewalk-2 This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/m...	[ "unlabeled", "flat-road", "flat-sidewalk", "flat-crosswalk", "flat-cyclinglane", "flat-parkingdriveway", "flat-railtrack", "flat-curb", "human-person", "human-rider", "vehicle-car", "vehicle-truck", "vehicle-bus", "vehicle-tramtrain", "vehicle-motorcycle", "vehicle-bicycle", "vehicle...
facebook/mask2former-swin-large-coco-instance	# Mask2Former Mask2Former model trained on COCO instance segmentation (large-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookresearch...	[ "person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrell...
facebook/mask2former-swin-base-coco-panoptic	# Mask2Former Mask2Former model trained on COCO panoptic segmentation (base-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookresearch/...	[ "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrell...
facebook/mask2former-swin-large-coco-panoptic	# Mask2Former Mask2Former model trained on COCO panoptic segmentation (large-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookresearch...	[ "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrell...
facebook/mask2former-swin-small-coco-panoptic	# Mask2Former Mask2Former model trained on COCO panoptic segmentation (small-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookresearch...	[ "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrell...
facebook/mask2former-swin-tiny-coco-panoptic	# Mask2Former Mask2Former model trained on COCO panoptic segmentation (tiny-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookresearch/...	[ "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrell...
facebook/mask2former-swin-tiny-cityscapes-panoptic	# Mask2Former Mask2Former model trained on Cityscapes panoptic segmentation (tiny-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookres...	[ "road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
facebook/mask2former-swin-large-cityscapes-panoptic	# Mask2Former Mask2Former model trained on Cityscapes panoptic segmentation (large-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookre...	[ "road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
facebook/mask2former-swin-small-cityscapes-panoptic	# Mask2Former Mask2Former model trained on Cityscapes panoptic segmentation (small-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookre...	[ "road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
facebook/mask2former-swin-large-cityscapes-semantic	# Mask2Former Mask2Former model trained on Cityscapes semantic segmentation (large-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookre...	[ "road", "sidewalk", "building", "wall", "fence", "pole", "traffic light", "traffic sign", "vegetation", "terrain", "sky", "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
facebook/mask2former-swin-large-mapillary-vistas-semantic	# Mask2Former Mask2Former model trained on Mapillary Vistas semantic segmentation (large-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/face...	[ "bird", "ground animal", "curb", "fence", "guard rail", "barrier", "wall", "bike lane", "crosswalk - plain", "curb cut", "parking", "pedestrian area", "rail track", "road", "service lane", "sidewalk", "bridge", "building", "tunnel", "person", "bicyclist", "motorcyclist", ...
facebook/mask2former-swin-large-mapillary-vistas-panoptic	# Mask2Former Mask2Former model trained on Mapillary Vistas panoptic segmentation (large-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/face...	[ "bird", "ground animal", "curb", "fence", "guard rail", "barrier", "wall", "bike lane", "crosswalk - plain", "curb cut", "parking", "pedestrian area", "rail track", "road", "service lane", "sidewalk", "bridge", "building", "tunnel", "person", "bicyclist", "motorcyclist", ...
facebook/mask2former-swin-small-cityscapes-instance	# Mask2Former Mask2Former model trained on Cityscapes instance segmentation (small-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookre...	[ "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
facebook/mask2former-swin-tiny-cityscapes-instance	# Mask2Former Mask2Former model trained on Cityscapes instance segmentation (tiny-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookres...	[ "person", "rider", "car", "truck", "bus", "train", "motorcycle", "bicycle" ]
facebook/mask2former-swin-large-ade-panoptic	# Mask2Former Mask2Former model trained on ADE20k panoptic segmentation (large-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookresear...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...
facebook/mask2former-swin-base-ade-semantic	# Mask2Former Mask2Former model trained on ADE20k semantic segmentation (base-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookresearc...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...
facebook/mask2former-swin-base-IN21k-ade-semantic	# Mask2Former Mask2Former model trained on ADE20k semantic segmentation (base-IN21k version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookresearc...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...
facebook/mask2former-swin-small-ade-semantic	# Mask2Former Mask2Former model trained on ADE20k semantic segmentation (small-sized version, Swin backbone). It was introduced in the paper [Masked-attention Mask Transformer for Universal Image Segmentation ](https://arxiv.org/abs/2112.01527) and first released in [this repository](https://github.com/facebookresear...	[ "wall", "building", "sky", "floor", "tree", "ceiling", "road", "bed ", "windowpane", "grass", "cabinet", "sidewalk", "person", "earth", "door", "table", "mountain", "plant", "curtain", "chair", "car", "water", "painting", "sofa", "shelf", "house", "sea", "mirror...

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