image-segmentation

Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

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

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

[CAAI AIR'24] Bilateral Reference for High-Resolution Dichotomous Image Segmentation

📈 目前最大的工业缺陷检测数据库及论文集 Constantly summarizing open source dataset and critical papers in the field of surface defect research which are of great importance.

Accelerated deep learning R&D

The collection of pre-trained, state-of-the-art AI models for ailia SDK

Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation

Generic U-Net Tensorflow implementation for image segmentation

PyTorch extensions for fast R&D prototyping and Kaggle farming

Adapting Meta AI's Segment Anything to Downstream Tasks with Adapters and Prompts

Using Diffusion Models to Segment/Reconstruct Organs from Medical Images [AAAI Most influential Paper]

Build, train, optimize, and run computer vision models locally, from raw images to live inference. Open source, optimized for Intel XPU (CPU-only and CUDA also supported).

Automatically find issues in image datasets and practice data-centric computer vision.

Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/

UNet model with VGG11 encoder pre-trained on Kaggle Carvana dataset

PyTorch implementation of UNet++ (Nested U-Net).