968 Open source projects that are alternatives of or similar to CAP_augmentation

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

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

TFslim based semantic segmentation models, modular&extensible boutique design

Lane Detection in Low-light Conditions Using an Efficient Data Enhancement : Light Conditions Style Transfer (IV 2020)

Mix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021 Oral)

Tensorflow 2.3.0 implementation of DeepLabV3-Plus

Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

Flood-Filling Networks for instance segmentation in 3d volumes.

Cell Detection with PyTorch.

Unofficial implemention of lanenet model for real time lane detection using deep neural network model https://maybeshewill-cv.github.io/lanenet-lane-detection/

Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs

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.)

PyTorch extensions for fast R&D prototyping and Kaggle farming

Medical image preprocessing and augmentation toolkit for deep learning

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.

CNNs for semantic segmentation using Keras library

Test Time Augmentation (TTA) wrapper for computer vision tasks: segmentation, classification, super-resolution, ... etc.

Training & Quantization of embedded friendly Deep Learning / Machine Learning / Computer Vision models

Keras-tensorflow implementation of PersonLab (https://arxiv.org/abs/1803.08225)

Sandbox for training deep learning networks

Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).

PyTorch re-implementation of DeepMask

Mask R-CNN, FPN, LinkNet, PSPNet and UNet with multiple backbone architectures support readily available

👉 CARLA resources such as tutorial, blog, code and etc https://github.com/carla-simulator/carla

A High Level Python Library to empower students, developers to build applications and systems enabled with computer vision capabilities.

🔥🔥Official Repository for Multi-Human-Parsing (MHP)🔥🔥

Image Test Time Augmentation with PyTorch!

LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)

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

Catalyst.Segmentation

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

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

Code for ICCV2019 paper "InstaBoost: Boosting Instance Segmentation Via Probability Map Guided Copy-Pasting"

End-to-end one-class instance segmentation based on U-Net architecture for Data Science Bowl 2018 in Kaggle

A framework for training segmentation models in pytorch on labelme annotations with pretrained examples of skin, cat, and pizza topping segmentation

Unsupervised instance segmentation via active robot interaction

CCNet: Criss-Cross Attention for Semantic Segmentation (TPAMI 2020 & ICCV 2019).

CRF-RNN PyTorch version http://crfasrnn.torr.vision

Tensorflow implementation : U-net and FCN with global convolution

Collection of computer vision models, ready to be included in a JVM project

BCDU-Net : Medical Image Segmentation

The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919

An awesome semantic segmentation model that runs in real time

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

Semi-Supervised Video Object Segmentation (VOS) with Tensorflow. Includes implementation of *MaskRNN: Instance Level Video Object Segmentation (NIPS 2017)* as part of the NIPS Paper Implementation Challenge.

Chainer Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

The 4th place and the fastest solution of the Lyft Perception Challenge (Image semantic segmentation with PyTorch)

Official Pytorch Code of KiU-Net for Image Segmentation - MICCAI 2020 (Oral)

Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]

IJCAI2020 & IJCV 2020 🌇 Unsupervised Scene Adaptation with Memory Regularization in vivo

Semantic segmentation for classifying road. "Fully Convolutional Networks for Semantic Segmentation (2015)" implemented using TF

Be Driven 🚘

Code and dataset for the IJCAI 2021 paper "Document-level Relation Extraction as Semantic Segmentation".

Segmentation models with pretrained backbones. PyTorch.

Pytorch code for semantic segmentation using ERFNet

A native Tensorflow implementation of semantic segmentation according to Multi-Scale Context Aggregation by Dilated Convolutions (2016). Optionally uses the pretrained weights by the authors.

Grid-GCN for Fast and Scalable Point Cloud Learning

Paper notes in deep learning/machine learning and computer vision