Harxis yang's starred repositories
UltraPixel
Implementation of UltraPixel: Advancing Ultra-High-Resolution Image Synthesis to New Peaks
BeyondTextConstraint
The official implementation of CVPR2024 paper:"Beyond Textual Constraints: Learning Novel Diffusion Conditions with Fewer Examples"
X-AnyLabeling
Effortless data labeling with AI support from Segment Anything and other awesome models.
IP-Adapter
The image prompt adapter is designed to enable a pretrained text-to-image diffusion model to generate images with image prompt.
stablediffusion
High-Resolution Image Synthesis with Latent Diffusion Models
ConvNeXt-V2
Code release for ConvNeXt V2 model
Swin-Transformer
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
Winner_ECCV20_TAO
1st Place Solution to ECCV-TAO-2020: Detect and Represent Any Object for Tracking
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.
ultralytics
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
LabelAnyLandmarks
A simple labelling tool for landmarks/keypoints on 2D images.
Deep3DFaceRecon_pytorch
Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set (CVPRW 2019). A PyTorch implementation.
Algorithms
剑指Offer(第二版)/程序员代码面试指南(第2版)/LeetCode/LintCode
Python-Offer
《剑指Offer》面试题Python实现
CodingInterviewChinese2
剑指offer第二版 python代码
Coding4Interviews
Leetcode、剑指Offer——名企面试官精讲典型编程题
GradAttack
GradAttack is a Python library for easy evaluation of privacy risks in public gradients in Federated Learning, as well as corresponding mitigation strategies.
loss-landscape
Code for visualizing the loss landscape of neural nets
stylegan2_pytorch
A Pytorch implementation of StyleGAN2
ccf-deadlines
⏰ Collaboratively track deadlines of conferences recommended by CCF (Website, Python Cli, Wechat Applet) / If you find it useful, please star this project, thanks~