1125 Open source projects that are alternatives of or similar to Keras Icnet

Simple PyTorch implementations of U-Net/FullyConvNet (FCN) for image segmentation

Segmentation models with pretrained backbones. PyTorch.

Tensorflow 2 implementation of complete pipeline for multiclass image semantic segmentation using UNet, SegNet and FCN32 architectures on Cambridge-driving Labeled Video Database (CamVid) dataset.

[NeurIPS2021] Code Release of K-Net: Towards Unified Image Segmentation

Using a U-Net for image segmentation, blending predicted patches smoothly is a must to please the human eye.

FCN, U-Net models implementation in TensorFlow for fashion clothing parsing

EntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation

This is a fully convolutional neural net exercise to detect houses from aerial images.

proof-of-concept program that detects rail-track with semantic segmentation for autonomous train system

A curated list of resources focused on Machine Learning in Geospatial Data Science.

Semantic Image Segmentation using a Fully Convolutional Neural Network in TensorFlow

遥感图像的语义分割，基于深度学习，在Tensorflow框架下，利用TF.Keras，运行环境TF2.0+

ResUNet++, CRF, and TTA for segmentation of medical images (IEEE JBIHI)

An opensource lib. for vehicle vision applications (written by MATLAB), lane marking detection, road segmentation

Deep and Machine Learning for Microscopy

Semantically segment the road in the given image.

A Python Library for High-Level Semantic Segmentation Models based on TensorFlow and Keras with pretrained backbones.

4th place solution in Baidu Autonomous Driving Lane Segmentation

VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition (ICCV 2017)

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

High-performance Vision library in Python. Scale your research, not boilerplate.

RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation

Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, ContextNet, FPENet, etc.)

CRF-RNN Keras/Tensorflow version

常用的语义分割架构结构综述以及代码复现

PyTorch for Semantic Segmentation

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

Helper package with multiple U-Net implementations in Keras as well as useful utility tools helpful when working with image semantic segmentation tasks. This library and underlying tools come from multiple projects I performed working on semantic segmentation tasks

A label tool aim to reduce semantic segmentation label time, rectangle and polygon annotation is supported

TensorFlow implementation of ENet, trained on the Cityscapes dataset.

Be Driven 🚘

A paper list of RGBD semantic segmentation (processing)

This project is made in Matlab Platform and it detects whether a person has cancer or not by taking into account his/her mammogram.

This is a repository for a semantic segmentation inference API using the OpenVINO toolkit

Semantic Segmentation of Underwater Imagery: Dataset and Benchmark. #IROS2020

InstantDL: An easy and convenient deep learning pipeline for image segmentation and classification

Keras BiseNet architecture implementation

Deep Learning for Computer Vision (CommE 5052) in NTU

FCN for Semantic Image Segmentation achieving 68.5 mIoU on PASCAL VOC

🚘 Easiest Fully Convolutional Networks

Tensorflow implementation : U-net and FCN with global convolution

Medical image processing in Python

Winning solution for the Kaggle TGS Salt Identification Challenge.

CVPR 2021 论文和开源项目合集

PyTorch extensions for fast R&D prototyping and Kaggle farming

Implementation of efficient graph-based image segmentation as proposed by Felzenswalb and Huttenlocher [1] that can be used to generate oversegmentations.

PyTorch implementation of DeepLabV3, trained on the Cityscapes dataset.

A PyTorch implementation for V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

Source code for the MICCAI 2016 Paper "Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional NeuralNetworks and 3D Conditional Random Fields"

Catalyst.Segmentation

Full web grabcut example using opencvjs

Model for document segmentation trained on the midv-500-models dataset.

Ipython Notebooks for solving problems like classification, segmentation, generation using latest Deep learning algorithms on different publicly available text and image data-sets.

Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.

Semantic Segmentation Architectures Implemented in PyTorch

GUI based Smart Sudoku Solver that tries to extract a sudoku puzzle from a photo and solve it

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

A c++ trainable semantic segmentation library based on libtorch (pytorch c++). Backbone: ResNet, ResNext. Architecture: FPN, U-Net, PAN, LinkNet, PSPNet, DeepLab-V3, DeepLab-V3+ by now.