cqu20160901 / yoloworld-onnx-tensorRT-rknn-horizonLinks
yoloworld 的onnx、tensorRT、rknn、horizon 部署,通用各种平台和芯片。
☆22Updated last year
Alternatives and similar repositories for yoloworld-onnx-tensorRT-rknn-horizon
Users that are interested in yoloworld-onnx-tensorRT-rknn-horizon are comparing it to the libraries listed below
Sorting:
- Easy Training Official YOLOv11、YOLOv10、YOLOv8、YOLOv7、YOLOv6、YOLOv5 and Prune all_model using Torch-Pruning!☆90Updated last week
- RT-DETRv2 tensorrt C++ 部署☆21Updated 9 months ago
- 🚀🚀🚀YOLOC is Combining different modules to build an different Object detection model.Including YOLOv3、YOLOv4、Scaled_YOLOv4、YOLOv5、YOLO…☆73Updated 3 years ago
- yolov8 旋转目标检测部署,瑞芯微RKNN芯片部署、地平线Horizon芯片部署、TensorRT部署☆29Updated last year
- ☆12Updated 3 months ago
- A quick TensorRT deoloyment solution for YOLOv8.☆39Updated last year
- ☆29Updated 8 months ago
- [TIP 24] The offical implementation of Efficient Small Object Detection on High-Resolution Images☆79Updated 2 months ago
- Multi-thread tracking of YOLOv5 and ByteTrack implemented by C++, accelerated by TensorRT. YOLOv5 和 ByteTrack 的多线 程追踪 C++ 实现, 使用 TensorRT …☆73Updated last month
- 使用TensorRT加速YOLOv8-Seg,完整的后端框架,包括Http服务器,Mysql数据库,ffmpeg视频推流等。☆85Updated last year
- Implementation of paper - DEYO: DETR with YOLO for End-to-End Object Detection☆96Updated last year
- This project showcases the deployment of the RT-DETR model using ONNXRUNTIME in C++ and Python.☆56Updated 2 years ago
- ☆22Updated 2 years ago
- ☆20Updated 2 years ago
- ☆27Updated 3 years ago
- DEYOv1.5☆25Updated last year
- yolov11(yolov8)尝试了7种不同的部署方法,并对每种方法的优势进行了简单总结。不同的平台、不同的时耗或CPU占用需求,总有一种方法是适用的。针对想入门部署的也是一个很好的参考学习资料。☆33Updated 6 months ago
- ☆29Updated 2 years ago
- 记录yolov5的TensorRT量化及推理代码,经实测可运行于Jetson平台☆19Updated 2 years ago
- ☆17Updated last year
- yolov11 的tensorRT C++ 部署,后处理使用cuda实现比较耗时的操作。☆42Updated 8 months ago
- ☆37Updated 11 months ago
- 🔥🔥 CVPR 2025 (Nashville TN) - The 4th Anti-UAV Workshop & Challenge 🥉☆68Updated last week
- 高效部署:YOLO X, V3, V4, V5, V6, V7, V8, EdgeYOLO TRT推理 ™️ ,前后处理均由CUDA核函数实现 CPP/CUDA🚀☆49Updated 2 years ago
- ☆99Updated 8 months ago
- rknn-3588部署yolov5,利用线程池实现npu推理加速;Deploying YOLOv5 on RKNN-3588, utilizing a thread pool to achieve NPU inference acceleration.☆74Updated 3 months ago
- 用OpenVINO对yolov8导出的onnx模型进行C++的推理, 任务包括图像分类, 目标识别和语义分割, 步骤包括图片前处理, 推理, NMS等☆70Updated last year
- yolov8n 部署版本,后处理用python语言和C++语言形式进行改写,便于移植不同平台(onnx、tensorRT、RKNN、Horzion)☆156Updated last year
- ☆99Updated last year
- ☆62Updated 10 months ago