按任务分类的模型

库中的每个系列,由 v1.7.0 模型注册表生成:22 类任务下共 115 个系列。

目标检测

47 个系列

为目标画出边界框,也是这个库最主要的任务。

⭐RF-DETR

n, s, m, l for detection and oriented boxes; n through xx for segmentation; x for pose

⭐YOLOv9

yolo9: t, s, m, c at 640 px; yolo9_p2: t, s at 640 px

D-FINE

n, s, m, l, x at 640 px

DEIM

deim: n, s, m, l, x at 640 px

EdgeCrafter

s, m, l, x at 640 px

RT-DETR

rtdetr: r18, r34, r50, r50m, r101, l, x at 640 px; rtdetrv2: r18, r34, r50, r50m, r101 at 640 px; rtdetrv4: s, m, l, x at 640 px

TinyFormer
YOLO-NAS

s, m, l at 640 px

Dome-DETR

s, m, l at 800 px

PicoDet

s, m, l at 320 to 640 px

PP-YOLOE

s, m, l, x at 640 px

RTMDet

t, s, m, l, x at 640 px

YOLOv7

b at 640 px

YOLOX

n, t, s, m, l, x at 416 to 640 px

Florence-2

base, large at 768 px

Gemma 4

e2b, e4b at 896 px

Grounding DINO

t, b at 800 px

InternVL3

1b, 2b, 8b at 448 px

Kosmos-2

224 at 224 px

LFM2-VL

450m, 3b at 512 px

LibreMODUS
LocateAnything

3b at 2500 px

Moondream

2, 3 at 384 to 512 px

North Micro Vision
OMDet-Turbo

t at 640 px

OV-DEIM

s, m, l at 640 px

OWLv2

b16, l14 at 960 to 1008 px

Qwen3-VL

2b, 4b, 8b at 1024 px

SenseNova-Vision

7b at 1024 px

SmolVLM2

500m at 512 px

WeVisOne-VL

2b, 4b at 1440 px

CenterNet

resdcn18, dla34 at 512 px

Deformable DETR

r50ss, r50ssdc5, r50, r50refine, r50twostage at 800 px

DETR

r50, r50dc5, r101, r101dc5 at 800 px

DINO-DETR

r50, r50s5, swinl at 800 px

EfficientDet
Faster R-CNN

n, s, m, l at 320 to 800 px

FCOS

r50 at 800 px

LW-DETR

t, s, m, l, x at 640 px

Mask R-CNN

r50 at 800 px

RetinaNet

r50, r50v2 at 800 px

SSD

300 at 300 px

YOLOv1

t, b at 448 px

YOLOv2

t, b at 416 to 608 px

YOLOv3

t, b, spp at 416 to 608 px

YOLOv4

t, b at 416 to 608 px

实例分割

15 个系列

为每个实例输出掩码,而不只是边界框。

⭐RF-DETR

n, s, m, l for detection and oriented boxes; n through xx for segmentation; x for pose

D-FINE

n, s, m, l, x at 640 px

EdgeCrafter

s, m, l, x at 640 px

RTMDet

t, s, m, l, x at 640 px

MobileSAM

tiny at 1024 px

PicoSAM3

pico at 96 px

SAM

base, large, huge at 1024 px

SAM 3

large at 1008 px

SenseNova-Vision

7b at 1024 px

WeVisOne-VL

2b, 4b at 1440 px

EoMT

s, b, l at 512 px

Mask R-CNN

r50 at 800 px

关键点

7 个系列

为每个检测到的实例输出骨架和关键点。

⭐RF-DETR

n, s, m, l for detection and oriented boxes; n through xx for segmentation; x for pose

EdgeCrafter

s, m, l, x at 640 px

YOLO-NAS

s, m, l at 640 px

SenseNova-Vision

7b at 1024 px

DEKR

w32 at 640 px

图像分类

15 个系列

为整张图像给出一个标签,同时也是其他任务的主干网络。

ConvNeXt

t, s, b at 224 px

ConvNeXt V2
DINOv2

n, s, m, l at 518 px

EfficientNetV2

b0, b1, b2, b3 at 224 to 300 px

MobileNetV4

s, m, l at 224 to 256 px

ResNet

18, 34, 50, 101 at 224 px

V-JEPA 2

l256, h256, g256, g384 at 256 to 384 px

Perception Encoder
AlexNet

b at 224 px

Swin Transformer

t, s, b, l at 224 px

VGG

16, 19, 16bn, 19bn at 224 px

ViT

ti, s, b, l at 224 px

DeiT

t, s, b at 224 px

旋转框

4 个系列

带角度的边界框,适用于航拍图像等非水平对齐的目标。

⭐RF-DETR

n, s, m, l for detection and oriented boxes; n through xx for segmentation; x for pose

RT-DETR

rtdetr: r18, r34, r50, r50m, r101, l, x at 640 px; rtdetrv2: r18, r34, r50, r50m, r101 at 640 px; rtdetrv4: s, m, l, x at 640 px

YOLO-NAS

s, m, l at 640 px

深度估计

8 个系列

从单张图像估计每个像素的距离。

LibreMODUS
SenseNova-Vision

7b at 1024 px

Depth Anything 3

l at 504 px

Depth Anything V2

s, b, l, g at 518 px

Marigold V2

b at 1024 px

MiDaS

s, l at 256 to 384 px

ZipDepth

b, bnpu at 384 px

语义分割

10 个系列

为每个像素分配类别,但不区分实例。

DINOv2

n, s, m, l at 518 px

LingBot-Vision
PP-LiteSeg
SegFormer
DeepLabv3
EoMT

s, b, l at 512 px

FCN

r50, r101 at 520 px

PIDNet

s, m, l at 1024 px

全景分割

2 个系列

一次前向同时输出语义和实例掩码。

SenseNova-Vision

7b at 1024 px

EoMT

s, b, l at 512 px

点检测与计数

9 个系列

用中心点代替边界框,轻到可以跑在单片机上。

Florence-2 grounding

base, large at 768 px

LocateAnything

3b at 2500 px

Molmo2

4b, 8b at 378 px

Moondream

2, 3 at 384 to 512 px

Qwen3-VL grounding

2b, 4b, 8b at 1024 px

SenseNova-Vision

7b at 1024 px

ShowUI

2b at 1344 px

WeVisOne-VL

2b, 4b at 1440 px

文字识别

3 个系列

在图像中定位并读出文字。

SenseNova-Vision

7b at 1024 px

WeVisOne-VL

2b, 4b at 1440 px

PP-OCRv5

t, l at 960 px

特征向量

7 个系列

用于检索、聚类和相似度搜索的向量。

DINOv2

n, s, m, l at 518 px

V-JEPA 2

l256, h256, g256, g384 at 256 to 384 px

Perception Encoder
LeVJEPA

l at 224 px

LibreFaceRec

视线估计

1 个系列

判断人正在看向哪里。

L2CS-Net

r18, r34, r50, r101, r152 at 448 px

边缘检测

3 个系列

轮廓与边界。

LibreMODUS
DexiNed

b at 352 px

TEED

t at 352 px

表面法线

3 个系列

每个表面朝向哪个方向。

LibreMODUS
Marigold V2

b at 1024 px

MoGe-2

s, b, l at 518 px

抠图

5 个系列

Alpha 通道抠图,连发丝和边缘一起保留。

WeVisOne-VL

2b, 4b at 1440 px

BEN2

b at 1024 px

BiRefNet

t, l at 1024 px

FeyNobg

l at 1024 px

ViTMatte

s at 512 px

图像修复

7 个系列

去噪、去模糊和超分辨率。

NAFNet

s, l at 256 px

HVI-CIDNet

t at 256 px

QuickSRNet

m2 at 64 px

Real-ESRGAN

x4, x2, x4t at 64 px

SwinIR

s, m, l at 64 px

三维网格

1 个系列

从图像重建三维几何。

SAM 3D Body

d3, h at 512 px

Robot policies

Robot policies

1 个系列

Action chunks from camera observations and robot state.

LibreVLA

smolvla: base at 512 px; act_policy: base at 224 px; diffusion_policy: base at 224 px

Albedo

Albedo

1 个系列

Intrinsic surface color in linear RGB.

Marigold V2

b at 1024 px

3D detection

3D detection

4 个系列

Camera-frame cuboids from a single image.

DetAny3D

h at 896 px

FCOS3D

r101 at 1600 px

WildDet3D

l at 1008 px

Image generation

Image generation

2 个系列

An image from a text prompt, with the seed that makes it again.

FLUX.2 klein

4b at 1024 px

SANA-Sprint
3D generation

3D generation

1 个系列

The whole object as 3D Gaussian splats, from one picture of it.

Speridlabs Idol