quarrying / quarrying-paper-notes
个人论文笔记
☆15Updated this week
Alternatives and similar repositories for quarrying-paper-notes:
Users that are interested in quarrying-paper-notes are comparing it to the libraries listed below
- Segmentation-Based Deep-Learning Approach for Surface-Defect Detection☆25Updated 4 years ago
- 分别使用OpenCV、ONNXRuntime部署多任务的yolov5目标检测+语义分割,包含C++和Python两个版本的程序☆30Updated 3 years ago
- 用opencv的dnn模块实现Yolo-Fastest的目标检测☆50Updated 4 years ago
- Include mobilenet series (v1,v2,v3...) and yolo series (yolov3,yolov4,...)☆33Updated 3 years ago
- 使用opencv的dnn模块做yolov4目标检测☆14Updated 4 years ago
- 使用opencv的dnn模块做YOLObile的目标检测☆17Updated 4 years ago
- OpenCV加载onnx实现SSD,YOLOV3,YOLOV5的推理☆24Updated 3 years ago
- 使用opencv部署DBNet文字检测,包含C++和Python两种版本的实现☆33Updated 3 years ago
- 98 landmark detection☆34Updated 4 years ago
- yolov5 with more backbone☆17Updated 2 years ago
- PyTorch implementation of MobileFaceNets☆19Updated 5 years ago
- 基于RetinaFace的目标检测方法,适用于人脸、缺陷、小目标、行人等☆107Updated 4 years ago
- TensorRT for RefineNet Segmentation☆12Updated 3 years ago
- 基于rknn的yolov5的cpp实现,包含各种依赖库,是一个完整工程,可直接编译运行☆19Updated 3 years ago
- Train Your Own DataSet for YOLACT and YOLACT++ Instance Segmentation Model!!!☆64Updated 5 years ago
- yolov5检测人脸和关键点,只依赖opencv库就可以运行,程序包含C++和Python两个版本的☆62Updated 3 years ago
- 模板匹配SSDA(序贯相似性)算法的python实现☆17Updated 4 years ago
- yolov5第四版☆15Updated 3 years ago
- 自然场景检测DBNet网络的tensorrt版本☆22Updated 4 years ago
- 使用retinaface完成车牌关键点检测,并在tensorRT下部署☆41Updated 3 years ago
- YOLOX 训练自己的数据集 TensorRT加速 详细教程☆40Updated 3 years ago
- yolov5+doublehead + MultiLabel+detection☆25Updated 2 years ago
- 分别使用OpenCV、ONNXRuntime部署YOLOV6目标检测,包含C++和Python两个版本的程序☆65Updated 2 years ago
- 【口罩佩戴检测数据训练 | 开源口罩检测数据集和预训练模型】Train D/CIoU_YOLO_V3 by darknet for object detection☆58Updated 4 years ago
- Segmentation-based deep-learning approach for surface-defect detection with pytorch☆24Updated 2 months ago
- joooogle / Automatic-labeling-of-instance-segmentation-Mask-Rcnn-in-static-background-base-on-labelme静态背景下实例分割数据集自动标注工具,基于Labelme改进。可以自动生成labelme格式的json文件。(注意:本程序只适用于大量图片基于静态背景)原理是:背景减除后得到高质量的二值图,计算连通域外轮廓坐标,再将信息写入json文件。☆12Updated 5 years ago
- Examples and tools for deep learning deployment☆56Updated 4 years ago
- 纯YOLO系列的人脸检测+106个关键点检测☆31Updated 4 years ago
- PP-YOLOE行人检测+HRNet人体骨骼关键点检测,使用ONNXRuntime部署,包含C++和Python两个版本的程序☆36Updated 2 years ago
- 无人机视角、多模态、模型剪枝、国产AI芯片部署☆38Updated 3 years ago