The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."

✂️ Automated high-quality background removal framework for an image using neural networks. ✂️

🔥🔥🔥TensorRT for YOLOv8、YOLOv8-Pose、YOLOv8-Seg、YOLOv8-Cls、YOLOv7、YOLOv6、YOLOv5、YOLONAS......🚀🚀🚀CUDA IS ALL YOU NEED.🍎🍎🍎

The Tensorflow, Keras implementation of U-net, V-net, U-net++, UNET 3+, Attention U-net, R2U-net, ResUnet-a, U^2-Net, TransUNET, and Swin-UNET with optional ImageNet-trained backbones.

This repo contains code and a pre-trained model for clothes segmentation.

Demonstration using Google Colab to show how U-2-NET can be used for Background Removal, Changing Backgrounds, Bounding Box Creation, Salient Feature Highlighting and Salient Object Cropping.

Huggingface cloth segmentation using U2NET

Removebg is a library that effortlessly integrates the U2Net model, allowing users to easily remove backgrounds from images in their Android apps.

U-2-Net: U Square Net - Modified for paired image training of style transfer

Python GUI for Interactive Image Background Removal using locally running AI point and click models such as Segment Anything and automatic whole-image models such as BiRefNet and Rembg

Nested U-Net with two-level skip connections for speech enhancement

基于显著性目标检测的非特定类别图像分割-中国大学生服务外包创新创业大赛

胃癌恶性病变组织检测

A framework to quickly generate high-quality stylized clothing from style images. The framework gives users the option to stylize only selected components. It uses Saliency guided style transfer to generate high-quality outputs.

Copy objects from real life and directly paste them on a background image using only your phone's camera

基于u2net网络进行简单修改使其部署到rk3588板子上

Implementation of the paper "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection" in TensorFlow.

U2Net + ISNet GT encoder, training base on ssim loss, iou loss and bce loss，experimented on tooth segmentation on panoramic X-ray images.

Neural networks do line art stylization

Full-stack augmented reality and AI-powered virtual garment try-on system for e-commerce. Combines real-time AR preview with ML-powered photo-realistic virtual try-on using state-of-the-art deep learning models.