yaoqingyuan's starred repositories
tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.
label-studio
Label Studio is a multi-type data labeling and annotation tool with standardized output format
The-Art-of-Linear-Algebra
Graphic notes on Gilbert Strang's "Linear Algebra for Everyone"
tfjs-models
Pretrained models for TensorFlow.js
go-proxy-bingai
用 Vue3 和 Go 搭建的微软 New Bing 演示站点,拥有一致的 UI 体验,支持 ChatGPT 提示词,国内可用。
tfjs-examples
Examples built with TensorFlow.js
TNN
TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.
tuning_playbook_zh_cn
一本系统地教你将深度学习模型的性能最大化的战术手册。
Yolo-Fastest
:zap: Based on yolo's ultra-lightweight universal target detection algorithm, the calculation amount is only 250mflops, the ncnn model size is only 666kb, the Raspberry Pi 3b can run up to 15fps+, and the mobile terminal can run up to 178fps+
scikit-learn-intelex
Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application
awesome-ncnn
😎 A Collection of Awesome NCNN-based Projects
Exposure_Correction
Project page of the paper "Learning Multi-Scale Photo Exposure Correction" (CVPR 2021).
label-studio-ml-backend
Configs and boilerplates for Label Studio's Machine Learning backend
vs-tools-for-ai
Visual Studio Tools for AI is a free Visual Studio extension to build, test, and deploy deep learning / AI solutions. It seamlessly integrates with Azure Machine Learning for robust experimentation capabilities, including but not limited to submitting data preparation and model training jobs transparently to different compute targets. Additionally, it provides support for custom metrics and run history tracking, enabling data science reproducibility and auditing. Enterprise ready collaboration, allow to securely work on project with other people.
ncnn-webassembly-yolov5
Deploy YOLOv5 in your web browser with ncnn and webassembly
TFJS-object-detection
Real-time custom object detection in the browser using tensorflow.js
ncnn-webassembly-nanodet
Deploy nanodet, the super fast and lightweight object detection, in your web browser with ncnn and webassembly
EfficientNet-Lite
Pytorch implementation of EfficientNet-lite. ImageNet pre-trained models are provided.
ncnn-webassembly-scrfd
Deploy SCRFD, an efficient high accuracy face detection approach, in your web browser with ncnn and webassembly
ncnn-webassembly-portrait-segmentation
Portrait segmentation in your web browser with ncnn and webassembly
mnn-yolov5
Imported from https://gitee.com/techshoww/mnn-yolov5.
Remake-detection
2019年大创项目和2019年新苗人才计划项目,针对翻拍的图片进行检测与识别,主要使用lbp算法,前期准确率在80.08%左右,后不断扩大优化图片数据库,准确率提升到97.4%结题。