需 ONNXRuntime >= 1.22.0,版本不匹配会编译或加载失败;CUDA/TensorRT/CoreML 等后端要额外开对应 cargo feature(如 -F cuda、-F tensorrt-full);模型默认从 HuggingFace/GitHub 自动下载,首次运行需联网。
usls
jamjamjonMIT活跃维护基于 Rust 和 ONNXRuntime 的计算机视觉与视觉语言模型库,集成 YOLO、FastVLM、OCR、SAM 等模型,方便在 Rust 项目中直接做目标检测、分割和图文理解。
A Rust library integrated with ONNXRuntime, providing a collection of Computer Vison and Vision-Language models such as YOLO, FastVLM, and more.
cargo run -r --example yolo -- --task detect --ver 26 --scale n --dtype fp16CPU 可直接运行;GPU 侧支持 CUDA、TensorRT、TensorRT-RTX、CoreML、OpenVINO、DirectML 等执行提供器,README 未给出具体显存要求。
基于 ONNXRuntime 的 Rust 视觉与视觉语言模型推理库,统一跑 YOLO、SAM、FastVLM 等 50+ 模型
基于 Rust 和 ONNXRuntime 的计算机视觉与视觉语言模型库,集成 YOLO、FastVLM、OCR、SAM 等模型,方便在 Rust 项目中直接做目标检测、分割和图文理解。
核心能力
- 统一 Model trait,用 run()/forward() 做推理并返回统一 Y 输出
- 内置自动下载 HuggingFace/GitHub 模型并缓存、解析路径
- 支持图像、目录、视频、摄像头、流等多种输入组合
- 提供 DataLoader、Annotator、Viewer 全流程组件
- 支持 FP32/FP16/INT8/Q4/BNB4 等多种精度与动态 batch
容易踩的坑
- v0.2.0-alpha.3最新正式版2026-02-05 · 2026-02-05 13:34 UTC
What's Changed
- v0.2.0-alpha1 by @jamjamjon in https://github.com/jamjamjon/usls/pull/185
- update by @jamjamjon in https://github.com/jamjamjon/usls/pull/187
- update by @jamjamjon in https://github.com/jamjamjon/usls/pull/188
- feat: upgrade ort to v2.0.0-rc11 and add NvTensorRT-RTX ep by @jamjamjon in https://github.com/jamjamjon/usls/pull/189
- feat(yolo): add YOLO26 models by @jamjamjon in https://github.com/jamjamjon/usls/pull/193
- fix: CUDA Image Processor device compatibility and performance by @jamjamjon in https://github.com/jamjamjon/usls/pull/205
- Add BiRefNet and YOLOE-26-Prompt-Free models by @jamjamjon in https://github.com/jamjamjon/usls/pull/207
- Add YOLOE-26 prompt-free and prompt-based models by @jamjamjon in https://github.com/jamjamjon/usls/pull/208
- chore: change default static input shapes for coreml by @wep21 in https://github.com/jamjamjon/usls/pull/206
- Change default visual encoder dtype to int4 by @killzoner in https://github.com/jamjamjon/usls/pull/214
- feat: Add YOLOE-26-prompt-based by @jamjamjon in https://github.com/jamjamjon/usls/pull/217
- fix: dynamic batch pose estimation for trt by @wep21 in https://github.com/jamjamjon/usls/pull/216
- Add MoboleGaze model and update docs by @jamjamjon in https://github.com/jamjamjon/usls/pull/223
- Add PP-DocLayout-V1/V2 model by @jamjamjon in https://github.com/jamjamjon/usls/pull/224
- Add RF-DETR models by @jamjamjon in https://github.com/jamjamjon/usls/pull/225
- Update docs by @jamjamjon in https://github.com/jamjamjon/usls/pull/228
- Update trt-ep setting by @jamjamjon in https://github.com/jamjamjon/usls/pull/229
- Add PP-Doclayout-V3 by @jamjamjon in https://github.com/jamjamjon/usls/pull/233
- Add yolo26-det-int8 by @jamjamjon in https://github.com/jamjamjon/usls/pull/235
New Contributors
- @killzoner made their first contribution in https://github.com/jamjamjon/usls/pull/214
Full Changelog: https://github.com/jamjamjon/usls/compare/v0.1.11...v0.2.0-alpha.3
- v0.1.11v0.1.11 - Sam3-Image & Sam3-tracker2026-01-10 · 2026-01-10 14:11 UTC
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What's Changed
- Add sam3-image model by @jamjamjon in https://github.com/jamjamjon/usls/pull/164
- feat(sam3-image): add TensorRT support by @jamjamjon in https://github.com/jamjamjon/usls/pull/166
- refactor(sam3-image): code refine by @jamjamjon in https://github.com/jamjamjon/usls/pull/169
- Add SAM3 Python export and inference scripts by @jamjamjon in https://github.com/jamjamjon/usls/pull/172
- Add sam3-tracker and refactor style system by @jamjamjon in https://github.com/jamjamjon/usls/pull/177
- Introduce tracing by @jamjamjon in https://github.com/jamjamjon/usls/pull/178
- Split out HTTP(S) (ureq) and
imagedefault-formats into features by @glasgow-haskell-omelette in https://github.com/jamjamjon/usls/pull/165
Full Changelog: https://github.com/jamjamjon/usls/compare/v0.1.10...v0.1.11
- v0.1.10v0.1.10 – GroundingDINO multi-batch inference, mm-gdino/llmdet integration & new class-name post-processing2025-11-22 · 2025-11-22 12:30 UTC
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What's Changed
- feat(gdino): add multi-batch inference support; integrate mm-gdino … by @jamjamjon in https://github.com/jamjamjon/usls/pull/162
Full Changelog: https://github.com/jamjamjon/usls/compare/v0.1.9...v0.1.10
New Supported ONNX Model
- gdino-base
- gdino-tiny
- llmdet-base
- llmdet-large
- llmdet-tiny
- mm-gdino-base-all
- mm-gdino-base-o365v1-goldg-v3det
- mm-gdino-large-all
- mm-gdino-large-o365v2-oiv6-goldg
- mm-gdino-tiny-o365v1-goldg-grit-v3det
- mm-gdino-tiny-o365v1-goldg-grit
- mm-gdino-tiny-o365v1-goldg-v3det
- mm-gdino-tiny-o365v1-goldg
- v0.1.9v0.1.9 - Add RT-DETRv42025-11-17 · 2025-11-17 16:05 UTC
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What's Changed
- Make Y elements public and remove fake optimizations by @numfin in https://github.com/jamjamjon/usls/pull/160
- Add RT-DETRv4 by @jamjamjon in https://github.com/jamjamjon/usls/pull/161
New Contributors
- @numfin made their first contribution in https://github.com/jamjamjon/usls/pull/160
Full Changelog: https://github.com/jamjamjon/usls/compare/v0.1.8...v0.1.9
- v0.1.8Add RAM & RAM++ models 2025-11-04 · 2025-11-04 16:15 UTC
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What's Changed
- Add RAM & RAM++ models by @jamjamjon in https://github.com/jamjamjon/usls/pull/158
Full Changelog: https://github.com/jamjamjon/usls/compare/v0.1.7...v0.1.8
用户点评
登录用户的真实使用记录,可按版本和硬件筛选还没有人点评。第一个说出真实体验的人最有价值。
usls is a cross-platform Rust library powered by ONNX Runtime for efficient inference of SOTA vision and vision-language models (typically under 1B parameters).
🌟 Highlights
- ⚡ High Performance: Multi-threading, SIMD, and CUDA-accelerated processing
- ✨ Cross-Platform: Linux, macOS, Windows with ONNX Runtime execution providers (CUDA, TensorRT, CoreML, OpenVINO, DirectML, etc.)
- 🎯 Precision Support: FP32, FP16, INT8, UINT8, Q4, Q4F16, BNB4, and more
- 🛠️ Full-Stack Suite:
DataLoader,Annotator, andViewerfor complete workflows - 🏗️ Unified API: Single
Modeltrait inference withrun()/forward()/encode_images()/encode_texts()and unifiedYoutput - 📥 Auto-Management: Automatic model download (HuggingFace/GitHub), caching and path resolution
- 📦 Multiple Inputs: Image, directory, video, webcam, stream and combinations
- 🌱 Model Ecosystem: 50+ SOTA vision and VLM models
🚀 Quick Start
Run the YOLO-Series demo to explore models with different tasks, precision and execution providers:
- Tasks:
detect,segment,pose,classify,obb - Versions:
v5,v6,v7,v8,v9,v10,11,12,v13,26 - Scales:
n,s,m,l,x - Precision:
fp32,fp16,q8,int8,q4,q4f16,bnb4, and more - Execution Providers:
CPU,CUDA,TensorRT,TensorRT-RTX,CoreML,OpenVINO, and more
cargo run -r --example yolo -- --task detect --ver 26 --scale n --dtype fp16
cargo run -r -F cuda --example yolo -- --task segment --ver 11 --scale m --device cuda:0 --processor-device cuda:0
cargo run -r -F tensorrt-full --example yolo -- --device tensorrt:0 --processor-device cuda:0
cargo run -r -F nvrtx-full --example yolo -- --device nvrtx:0 --processor-device cuda:0
cargo run -r -F coreml --example yolo -- --device coreml
cargo run -r -F openvino -F ort-load-dynamic --example yolo -- --device openvino:CPU
Environment: NVIDIA RTX 3060Ti (TensorRT-10.11.0.33, CUDA 12.8, TensorRT-RTX-1.3.0.35) / Intel i5-12400F
Setup: YOLO26 Detection, COCO2017-val (5,000 images), 640x640, Conf thresholds: [0.35, 0.3, ..]
Results are for rough reference only.
| Scale | EP | ImageProcessor | DType | Batch | Preprocess | Inference | Postprocess | Total |
|---|---|---|---|---|---|---|---|---|
| n | TensorRT | CUDA | FP16 | 1 | ~233µs | ~1.3ms | ~14µs | ~1.55ms |
| n | TensorRT-RTX | CUDA | FP32 | 1 | ~233µs | ~2.0ms | ~10µs | ~2.24ms |
| n | TensorRT-RTX | CUDA | FP16 | 1 | ❓ | ❓ | ❓ | ❓ |
| n | CUDA | CUDA | FP32 | 1 | ~233µs | ~5.0ms | ~17µs | ~5.25ms |
| n | CUDA | CUDA | FP16 | 1 | ~233µs | ~3.6ms | ~17µs | ~3.85ms |
| n | CUDA | CPU | FP32 | 1 | ~800µs | ~6.5ms | ~14µs | ~7.31ms |
| n | CUDA | CPU | FP16 | 1 | ~800µs | ~5.0ms | ~14µs | ~5.81ms |
| n | CPU | CPU | FP32 | 1 | ~970µs | ~20.5ms | ~14µs | ~21.48ms |
| n | CPU | CPU | FP16 | 1 | ~970µs | ~25.0ms | ~14µs | ~25.98ms |
| n | TensorRT | CUDA | FP16 | 8 | ~1.2ms | ~6.0ms | ~55µs | ~7.26ms |
| n | TensorRT | CPU | FP16 | 8 | ~18.0ms | ~25.5ms | ~55µs | ~43.56ms |
| m | TensorRT | CUDA | FP16 | 1 | ~233µs | ~3.6ms | ~14µs | ~3.85ms |
| m | TensorRT | CUDA | Int8 | 1 | ~233µs | ~2.6ms | ~14µs | ~2.84ms |
| m | CUDA | CUDA | FP32 | 1 | ~233µs | ~16.1ms | ~17µs | ~16.35ms |
| m | CUDA | CUDA | FP16 | 1 | ~233µs | ~8.8ms | ~17µs | ~9.05ms |
🔍 What's Next?
- 📖 Online Documentation
- 📚 API Reference
- 📦 Model Zoo
- 🚀 Examples
📦 Model Zoo
[!NOTE]
Status: ✅ Supported | ❓ Unknown | ❌ Not Supported For Now
🔍 All ONNX models are available from the ONNX Models Repository
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| YOLOv5 | Image ClassificationObject DetectionInstance Segmentation | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
| YOLOv6 | Object Detection | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
| YOLOv7 | Object Detection | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
| YOLOv8 | Object DetectionInstance SegmentationImage ClassificationOriented Object DetectionKeypoint Detection | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
| YOLO11 | Object DetectionInstance SegmentationImage ClassificationOriented Object DetectionKeypoint Detection | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
| YOLOv9 | Object Detection | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
| YOLOv10 | Object Detection | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
| YOLOv12 | Image ClassificationObject DetectionInstance Segmentation | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| YOLOv13 | Object Detection | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| YOLO26 | Object DetectionInstance SegmentationImage ClassificationOriented Object DetectionKeypoint Detection | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| BEiT | Image Classification | demo | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
| ConvNeXt | Image Classification | demo | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
| FastViT | Image Classification | demo | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
| MobileOne | Image Classification | demo | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
| DeiT | Image Classification | demo | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
| RAM | Image Tagging | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| RAM++ | Image Tagging | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| RT-DETRv1 | Object Detection | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| RT-DETRv2 | Object Detection | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| RT-DETRv4 | Object Detection | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| RF-DETR | Object Detection | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| PP-PicoDet | Object Detection | demo | ❌ | ❓ | ✅ | ❌ | ❌ | ❌ | ❌ |
| D-FINE | Object Detection | demo | ✅ | ❓ | ✅ | ❌ | ❌ | ❌ | ❌ |
| DEIM | Object Detection | demo | ✅ | ❓ | ✅ | ❌ | ❌ | ❌ | ❌ |
| DEIMv2 | Object Detection | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| SAM | Segment Anything | demo | ✅ | ❓ | ✅ | ❌ | ❌ | ❌ | ❌ |
| SAM-HQ | Segment Anything | demo | ✅ | ❓ | ✅ | ❌ | ❌ | ❌ | ❌ |
| MobileSAM | Segment Anything | demo | ✅ | ❓ | ✅ | ❌ | ❌ | ❌ | ❌ |
| EdgeSAM | Segment Anything | demo | ✅ | ❓ | ✅ | ❌ | ❌ | ❌ | ❌ |
| YOLOE-v8/11-Prompt-Free | Open-Set Detection And Segmentation | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| YOLOE-26-Prompt-Free | Open-Set Detection And Segmentation | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| FastSAM | Instance Segmentation | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| EdgeCrafter (ECDetSeg) | Instance Segmentation | demo | ❓ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
| SAM2 | Segment Anything | demo | ✅ | ❓ | ✅ | ❌ | ❌ | ❌ | ❌ |
| SAM3-Tracker | Segment Anything | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| BiRefNet - COD | Camouflaged Object Detection | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| BiRefNet - DIS | Dichotomous Image Segmentation | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| BiRefNet - HRSOD | High-Resolution Salient Object Detection | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| BiRefNet - Massive | Multi-Dataset Robust Segmentation | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| RMBG | Image SegmentationBackground Removal | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| BEN2 | Image SegmentationBackground Removal | demo | ✅ | ❓ | ✅ | ✅ | ❌ | ❌ | ❌ |
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| MobileGaze | Eye Gaze Estimation | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| MODNet | Image Matting | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ❌ | ❌ |
| MediaPipe Selfie | Image Segmentation | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ❌ | ❌ |
| BiRefNet - Portrait | Portrait Background Removal | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| BiRefNet - Matting | Portrait Matting & Background Removal | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| BiRefNet - HR Matting | High-Resolution Portrait Matting | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| BiRefNet - General | General Purpose Segmentation | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| BiRefNet - HR General | High-Resolution General Segmentation | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| BiRefNet - Lite General | Lightweight General Segmentation (2K) | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| BiRefNet - General Tiny | Lightweight General Segmentation with Swin-V1-Tiny | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| GroundingDINO | Open-Set Detection With Language | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| MM-GDINO | Open-Set Detection With Language | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| LLMDet | Open-Set Detection With Language | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| OWLv2 | Open-Set Object Detection | demo | ✅ | ❓ | ✅ | ✅ | ❌ | ❌ | ❌ |
| YOLO-World | Open-Set Detection With Language | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| YOLOE-Prompt-Based | Open-Set Detection And Segmentation | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| YOLOE-26-Prompt-Based | Open-Set Detection And Segmentation | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| SAM3-Image | Open-Set Detection And Segmentation | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| ByteTrack | Multi-Object Tracking | demo | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ |
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| Swin2SR | Image Restoration | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| APISR | Anime Super-Resolution | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| RTMPose | Keypoint Detection | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| DWPose | Keypoint Detection | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| RTMW | Keypoint Detection | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| RTMO | Keypoint Detection | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ❌ |
| ECPose | Keypoint Detection | demo | ✅ | ❓ | ✅ | ✅ | ❌ | ❌ | ❌ |
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| DB (PaddleOCR det v4 / v5) | Text Detection | demo | ✅ | ❓ | ✅ | ✅ | ❌ | ❌ | ❌ |
| FAST | Text Detection | demo | ✅ | ❓ | ✅ | ✅ | ❌ | ❌ | ❌ |
| LinkNet | Text Detection | demo | ✅ | ❓ | ✅ | ✅ | ❌ | ❌ | ❌ |
| SVTR (PaddleOCR rec v4 / v5) | Text Recognition | demo | ✅ | ❓ | ✅ | ✅ | ❌ | ❌ | ❌ |
| TrOCR | Text Recognition | demo | ✅ | ❓ | ✅ | ✅ | ❌ | ❌ | ❌ |
| SLANet (PaddleOCR tab v4 / v5) | Table Recognition | demo | ✅ | ❓ | ✅ | ✅ | ❌ | ❌ | ❌ |
| DocLayout-YOLO | Object Detection | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ❌ | ❌ |
| PP-DocLayout-v1-Plus-L | Object Detection | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |
| PP-DocLayout-v2 | Object Detection | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| PP-DocLayout-v3 | Object Detection | demo | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| BLIP | Image Captioning | demo | ✅ | ❓ | ✅ | ❓ | ❌ | ❌ | ❌ |
| Florence2 | A Variety of Vision Tasks | demo | ✅ | ❓ | ✅ | ✅ | ❌ | ❌ | ❌ |
| Moondream2 | Open-Set Object DetectionOpen-Set Keypoints DetectionImage CaptioningVisual Question Answering | demo | ✅ | ❓ | ❌ | ❌ | ✅ | ✅ | ❌ |
| SmolVLM | Visual Question Answering | demo | ✅ | ❓ | ✅ | ❓ | ❓ | ❓ | ❓ |
| SmolVLM2 | Visual Question Answering | demo | ✅ | ❓ | ✅ | ❓ | ❓ | ❓ | ❓ |
| FastVLM | Vision Language Models | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| CLIP | Vision-Language Embedding | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| jina-clip-v1 | Vision-Language Embedding | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| jina-clip-v2 | Vision-Language Embedding | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| mobileclip | Vision-Language Embedding | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| SigLIP | Vision-Language Embedding | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| SigLIPv2 | Vision-Language Embedding | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| DINOv2 | Vision Embedding | demo | ✅ | ❓ | ✅ | ❌ | ❌ | ❌ | ❌ |
| DINOv3 | Vision Embedding | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| DepthAnything v1 | Monocular Depth Estimation | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| DepthAnything v2 | Monocular Depth Estimation | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| DepthPro | Monocular Depth Estimation | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Depth-Anything-3 | MonocularMetricMulti-View | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Model | Task / Description | Demo | Dynamic Batch | TensorRT | FP32 | FP16 | Q8 | Q4f16 | BNB4 |
|---|---|---|---|---|---|---|---|---|---|
| Sapiens | Foundation for Human Vision Models | demo | ✅ | ❓ | ✅ | ✅ | ✅ | ✅ | ✅ |
| YOLOPv2 | Panoptic Driving | demo | ✅ | ❓ | ✅ | ❌ | ❌ | ❌ | ❌ |
🤝 Contributing
This is a personal project maintained in spare time, so progress on performance optimization and new model support may vary.
We highly welcome PRs for model optimization! If you have expertise in specific models and can help optimize their interfaces or post-processing, your contributions would be invaluable. Feel free to open an issue or submit a pull request for suggestions, bug reports, or new features.
🙏 Acknowledgments
-
This project is built on top of ort (ONNX Runtime for Rust), which provides seamless Rust bindings for ONNX Runtime. Special thanks to the
ortmaintainers. -
Special thanks to @kadu-v for the jamtrack-rs project, which inspired our ByteTracker implementation
Thanks to all the open-source libraries and their maintainers that make this project possible. See Cargo.toml for a complete list of dependencies.
📜 License
This project is licensed under LICENSE.