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.

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.

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

Effortless data labeling with AI support from Segment Anything and other awesome models.

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

📈 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

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

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

Medical Image Segmentation with Diffusion Model

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

Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™

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