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
[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://huggingface.co/proxy/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... |
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