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Hunter's Projects

basicsr icon basicsr

Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.

dalle2-pytorch icon dalle2-pytorch

Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch

diffusers icon diffusers

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch

dive_into_deep_learning icon dive_into_deep_learning

✔️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。

face_sr icon face_sr

Algorithms for face super resolution implemented in Pytorch.

fs-ncsr icon fs-ncsr

"FS-NCSR: Increasing Diversity of the Super-Resolution Space via Frequency Separation and Noise-Conditioned Normalizing Flow" (CVPRW 2022)

hat icon hat

Arxiv2022 - Activating More Pixels in Image Super-Resolution Transformer

labelimg icon labelimg

LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data.

lam icon lam

Local AtrrLocal Attribution Maps (LAM)

leetcode-master icon leetcode-master

《代码随想录》LeetCode 刷题攻略:200道经典题目刷题顺序,共60w字的详细图解,视频难点剖析,50余张思维导图,支持C++,Java,Python,Go,JavaScript等多语言版本,从此算法学习不再迷茫!🔥🔥 来看看,你会发现相见恨晚!🚀

mapsr_gan icon mapsr_gan

Official implementation of the paper 'Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution' in CVPR 2022

mmocr icon mmocr

OpenMMLab Text Detection, Recognition and Understanding Toolbox

mmyolo icon mmyolo

OpenMMLab YOLO series toolbox and benchmark. Implemented RTMDet, RTMDet-Rotated,YOLOv5, YOLOv6, YOLOv7, YOLOv8,YOLOX, PPYOLOE, etc.

modelscope icon modelscope

ModelScope: bring the notion of Model-as-a-Service to life.

segment-anything icon segment-anything

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.

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