Boosting's repositories
BGAQRCode-Android
QRCode 扫描二维码、扫描条形码、相册获取图片后识别、生成带 Logo 二维码、支持微博微信 QQ 二维码扫描样式
Face-Detector-1MB-with-landmark
1M人脸检测模型(含关键点)
hayoou_safe_driving_android
YOLOV4 tiny + lane detect in Android with 8 FPS!
hms-scan-demo
Sample code for demonstrating Huawei HMS ScanKit capabilities. It illustrates how to help developers quickly build code scanning capabilities.
leetcode-1
LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)
LeetCode-Go
✅ Solutions to LeetCode by Go, 100% test coverage, runtime beats 100% / LeetCode 题解
mmdetection-mini
mmdetection最小学习版
MobileNet-Yolo
MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops 420KB:fire::fire::fire:
mry-backend
本代码库为码如云后端代码。码如云是一个基于二维码的一物一码管理平台，可以为每一件“物品”生成一个二维码，手机扫码即可查看物品信息并发起相关业务操作，操作内容可由你自己定义，典型的应用场景包括固定资产管理、设备巡检以及物品标签等。在技术上，码如云是一个无代码平台，全程采用DDD、整洁架构和事件驱动架构**完成开发。
mry-frontend
本代码库为码如云前端代码。码如云是一个基于二维码的一物一码管理平台，可以为每一件“物品”生成一个二维码，手机扫码即可查看物品信息并发起相关业务操作，操作内容可由你自己定义，典型的应用场景包括固定资产管理、设备巡检以及物品标签等。在技术上，码如云是一个无代码平台，全程采用DDD、整洁架构和事件驱动架构**完成开发。
opencv-mobile
The minimal opencv for Android, iOS, ARM Linux, Windows, Linux, MacOS, WebAssembly
opencv_3rdparty
OpenCV - 3rdparty
Paddle-Lite
Multi-platform high performance deep learning inference engine (『飞桨』多平台高性能深度学习预测引擎）
PISR
An official implementation of "Learning with Privileged Information for Efficient Image Super-Resolution" (ECCV2020) in PyTorch.
pytorch_classification
利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码
Pytorch_Retinaface
Retinaface get 80.99% in widerface hard val using mobilenet0.25.
RCAN
PyTorch code for our ECCV 2018 paper "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"
ScaledYOLOv4
:fire::fire::fire: Scaled-YOLOv4训练自己的数据集详细教程PDF，关于paper解读请联系小编获取PDF文档
Swin-Transformer
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
Swin-Transformer-Semantic-Segmentation
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.
Yolo-Fastest
:zap: Yolo universal target detection model combined with EfficientNet-lite, the calculation amount is only 230Mflops(0.23Bflops), and the model size is 1.3MB
Yolo-FastestV2
:zap: Based on Yolo's low-power, ultra-lightweight universal target detection algorithm, the parameter is only 250k, and the speed of the smart phone mobile terminal can reach ~300fps+
YOLObile
This is the implementation of YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design
YOLOV3-NANO
YOLOV3-NANO-Tensorflow
YOLOv5_NCNN
🍅 Ncnn deployment on mobile,support:YOLOv5s,YOLOv4-tiny,MobileNetV2-YOLOv3-nano,Simple-Pose,Yolact,ChineseOCR-lite,ENet,Landmark106,DBFace,MBNv2-FCN,MBNv3-Seg-small and NanoDet on camera.