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The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Segment Anything in Medical Images

SAM-Med3D: An Efficient General-purpose Promptable Segmentation Model for 3D Volumetric Medical Image

Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch

计算机保研简历与文书实用模板

This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.

Code of "ResDiff: Combining CNN and Diffusion Model for Image Super-Resolution"

某校 每日上报打卡助手，支持使用 Github Actions 定时任务在线自动打卡，且支持打卡后用微信消息、电子邮件通知打卡结果。