Tiger's repositories
NEU-DET-with-yolov8
The dataset I am using is NEU-DET, which uses yolov8 and its improved models (including Coordinate Attention and Swin Transformer) for defect detection
deep-learning-for-image-processing
deep learning for image processing including classification and object-detection etc.
Auto-GPT
An experimental open-source attempt to make GPT-4 fully autonomous.
gpt_academic
为GPT/GLM提供图形交互界面，特别优化论文阅读润色体验，模块化设计支持自定义快捷按钮&函数插件，支持代码块表格显示，Tex公式双显示，新增Python和C++项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持清华chatglm等本地模型
yoloair
🔥🔥🔥YOLOv5, YOLOv6, YOLOv7, YOLOv8, PPYOLOE, YOLOX, YOLOR, YOLOv4, YOLOv3, Transformer, Attention, TOOD and Improved-YOLOv5-YOLOv7... Support to improve backbone, neck, head, loss, IoU, NMS and other modules🚀
mobilenetv3
mobilenetv3 with pytorch，provide pre-train model
nnUNet
深度学习图像分割nnUnet
Pytorch-UNet
深度学习图像分割U-Net-Pytorch
DFireDataset
D-Fire: an image data set for fire and smoke detection.
winxin-app-watch-life.net
微慕小程序开源版-WordPress版微信小程序
zrender
A lightweight graphic library providing 2d draw for Apache ECharts
fire-smoke-detect-yolov4
fire-smoke-detect-yolov4-yolov5 and fire-smoke-detection-dataset 火灾检测，烟雾检测
developer-roadmap
Interactive roadmaps, guides and other educational content to help developers grow in their careers.
Datasets
all kinds of datasets
drawio-desktop
Official electron build of draw.io
miniprogram-demo
微信小程序组件 / API / 云开发示例
3Dircadb_Use_Unet
Use U-net for 3Dircadb
PaddleSeg
3D-医学图像分割-Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.
ssmp
spring boot with mybatis-plus
2.2-1
k-均值
xiaoChengXu_ks_node
小程序课程设计
DeepLearning-MuLi-Notes
Notes about courses Dive into Deep Learning by Mu Li
dataset
医学影像数据集列表
yolov5-dnn-cpp-python-v2
用opencv的dnn模块做yolov5目标检测，包含C++和Python两个版本的程序，优化后的
pytorch-3dunet
3D U-Net model for volumetric semantic segmentation written in pytorch
Face-swiping-Time-Attendance-System
毕设项目，系统设计为教师端和学生端，主要包括刷脸签到、课程管理、考勤管理等功能模块。
pythontest
Test code for python