Huntersdeng / CXX-DeepLearning-Inference
A unified and extensible pipeline for deep learning model inference with C++. Now support yolov8, yolov9, clip, and nanosam. More models will be updated soon.
☆12Updated last year
Alternatives and similar repositories for CXX-DeepLearning-Inference:
Users that are interested in CXX-DeepLearning-Inference are comparing it to the libraries listed below
- FastSAM 部署版本，便于移植不同平，部署简单、运行速度快。☆18Updated 11 months ago
- C++ TensorRT Implementation of NanoSAM☆38Updated last year
- 分别使用OpenCV、ONNXRuntime部署CenterNet目标检测，包含C++和Python两个版本的程序☆9Updated 2 years ago
- segmentation algorithm yolact use tensorrt deploy☆14Updated 3 years ago
- This is a repository to practice multi-thread programming in C++☆24Updated last year
- 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☆27Updated 11 months ago
- pose estimation code with deepstream and yolo-pose☆13Updated 2 years ago
- tensorrt sahi yolo 目标检测☆46Updated 3 weeks ago
- ☆44Updated 2 years ago
- ☆19Updated 2 years ago
- RT-DETRv2 tensorrt C++ 部署☆16Updated 6 months ago
- NanoTrack(@HonglinChu), C++ TensorRT deployment. MAX 250 FPS!☆24Updated last year
- learn TensorRT from scratch🥰☆14Updated 7 months ago
- ☆18Updated 2 years ago
- yolov8seg 瑞芯微 rknn 板端 C++部署，使用平台 rk3588。☆24Updated 11 months ago
- An onnx-based quantitation tool.☆71Updated last year
- DETR tensor去除推理过程无用辅助头+fp16部署再次加速+解决转tensorrt 输出全为0问题的新方法。☆12Updated last year
- YoloV10 NPU for the RK3566/68/88☆14Updated 10 months ago
- This project provides simple code and demonstrates how to use the TensorRT C++ API and ONNX to deploy PaddleOCR text recognition model.☆41Updated 2 years ago
- Python scripts performing Open Vocabulary Object Detection using the YOLO-World model in ONNX. And Export the ONNX model for AXera's NPU☆12Updated 7 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☆62Updated last year
- Quantize yolov5 using pytorch_quantization.🚀 🚀🚀☆14Updated last year
- 搜藏的希望的代码片段☆13Updated last year
- 跟着Tensorrt_pro学习各种知识☆39Updated 2 years ago
- 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。☆21Updated 3 months ago
- based on the yolov8，provide pt-onnx-tensorrt transcode and infer code by c++☆59Updated 2 years ago
- 对 tensorRT_Pro 开源项目理解☆20Updated 2 years ago
- a simple lightweight large language model pipeline framework.☆24Updated last week
- yolov8obb 旋转目标检测部署rknn的C++代码☆17Updated 9 months ago
- Speed up image preprocess with cuda when handle image or tensorrt inference☆67Updated last month