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为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&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chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, m…
Deep Learning Book Chinese Translation
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
You like pytorch? You like micrograd? You love tinygrad! ❤️
deep learning for image processing including classification and object-detection etc.
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
✔（已完结）最全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】
Practice your pandas skills!
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
Curated list of chatgpt prompts from the top-rated GPTs in the GPTs Store. Prompt Engineering, prompt attack & prompt protect. Advanced Prompt Engineering papers.
A collection of loss functions for medical image segmentation
Segment Anything in Medical Images
Pytorch implementation of U-Net, R2U-Net, Attention U-Net, and Attention R2U-Net.
This repository includes the official project of TransUNet, presented in our paper: TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.
✔️李沐 【动手学深度学习】课程学习笔记：使用pycharm编程，基于pytorch框架实现。
💻深度学习实战：手写数字识别、Discuz验证码识别、垃圾分类、语义分割
3D U-Net model for volumetric semantic segmentation written in pytorch
ECCV 2024 论文和开源项目合集，同时欢迎各位大佬提交issue，分享ECCV 2024论文和开源项目
[ECCVW 2022] The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"
Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"
Implementation of different kinds of Unet Models for Image Segmentation - Unet , RCNN-Unet, Attention Unet, RCNN-Attention Unet, Nested Unet