tensorrt-yolo 4.3.1

Your YOLO Deployment Powerhouse. With the synergy of TensorRT Plugins, CUDA Kernels, and CUDA Graphs, experience lightning-fast inference speeds.

🚀 TensorRT YOLO

TensorRT-YOLO is an inference acceleration project that supports YOLOv3, YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOv9, YOLOv10, YOLO11, PP-YOLOE and PP-YOLOE+ using NVIDIA TensorRT for optimization. The project not only integrates the TensorRT plugin to enhance post-processing effects but also utilizes CUDA kernel functions and CUDA graphs to accelerate inference. TensorRT-YOLO provides support for both C++ and Python inference, aiming to deliver a fast and optimized object detection solution.

✨ Key Features

• Support for YOLOv3, YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOv9, YOLOv10, YOLO11, PP-YOLOE and PP-YOLOE+
• Support Detect and OBB Detect models
• Support for ONNX static and dynamic export, as well as TensorRT inference
• Integration of TensorRT plugin for accelerated post-processing
• Utilization of CUDA kernel functions for accelerated preprocessing
• Utilization of CUDA graphs for accelerated inference process
• Support for inference in both C++ and Python
• Command-line interface for quick export and inference
• One-click Docker deployment

🛠️ Requirements

• Recommended CUDA version >= 11.6
• Recommended TensorRT version >= 8.6

📦 Usage Guide

• Quick Compile and Install

• Export Models using CLI

• Model Inference Examples

• Video Analysis Example

📺 BiliBili

• 【TensorRT-YOLO】你的YOLO快速部署工具

• 【TensorRT-YOLO】TensorRT 自定义插件加速 YOLO OBB 部署演示

• 【TensorRT-YOLO】接入 VideoPipe 演示

• 【TensorRT-YOLO】CUDA Graphs 加速推理

• 【TensorRT-YOLO】3.0 Docker 部署演示

☕ Buy the Author a Coffee

Open source projects require effort. If this project has been helpful to you, consider buying the author a coffee. Your support is the greatest motivation for the developer to keep maintaining the project!

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📄 License

TensorRT-YOLO is licensed under the GPL-3.0 License, an OSI-approved open-source license that is ideal for students and enthusiasts, fostering open collaboration and knowledge sharing. Please refer to the LICENSE file for more details.

Thank you for choosing TensorRT-YOLO; we encourage open collaboration and knowledge sharing, and we hope you comply with the relevant provisions of the open-source license.

📞 Contact

For bug reports and feature requests regarding TensorRT-YOLO, please visit GitHub Issues!