===================================== README: Inpainting based PatchMatch ===================================== @Author: Younesse ANDAM @Contact: [email protected] Description: This project is a personal implementation of an algorithm called PATCHMATCH that restores missing areas in an image. The algorithm is presented in the following paper PatchMatch A Randomized Correspondence Algorithm for Structural Image Editing by C.Barnes,E.Shechtman,A.Finkelstein and Dan B.Goldman ACM Transactions on Graphics (Proc. SIGGRAPH), vol.28, aug-2009 For more information please refer to http://www.cs.princeton.edu/gfx/pubs/Barnes_2009_PAR/index.php Copyright (c) 2010-2011 Requirements ============ To run the project you need to install Opencv library and link it to your project. Opencv can be download it here http://opencv.org/downloads.html How to use =========== The project accepts two images 1- The original image 2- The pruned image you can delete a part of interest in the image. The algorithm will patch the remaining image to give a natural result. The project contains some example of images to try it. You may find them in image_files. After choosing the image file, enter the paths of those image files in main.c char fileNameInput[50] = YOUR_PATH_HERE_OF_ORIGINAL_IMAGE; char fileNameMasked[50] = YOUR_PATH_HERE_OF_PRUNED_IMAGE; Enjoy!!
Randomized Correspondence Algorithm for Structural Image Editing
Overview
Python Environment for Bayesian Learning
Pebl is a python library and command line application for learning the structure of a Bayesian network given prior knowledge and observations. Pebl in
PyTorch implementations of Generative Adversarial Networks.
This repository has gone stale as I unfortunately do not have the time to maintain it anymore. If you would like to continue the development of it as
PiRapGenerator - Make anyone rap the digits of pi
PiRapGenerator Make anyone rap the digits of pi (sample files are of Ted Nivison
The official PyTorch implementation of recent paper - SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training
This repository is the official PyTorch implementation of SAINT. Find the paper on arxiv SAINT: Improved Neural Networks for Tabular Data via Row Atte
Easy to use Python camera interface for NVIDIA Jetson
JetCam JetCam is an easy to use Python camera interface for NVIDIA Jetson. Works with various USB and CSI cameras using Jetson's Accelerated GStreamer
R interface to fast.ai
R interface to fastai The fastai package provides R wrappers to fastai. The fastai library simplifies training fast and accurate neural nets using mod
Code to accompany our paper "Continual Learning Through Synaptic Intelligence" ICML 2017
Continual Learning Through Synaptic Intelligence This repository contains code to reproduce the key findings of our path integral approach to prevent
This repo is a PyTorch implementation for Paper "Unsupervised Learning for Cuboid Shape Abstraction via Joint Segmentation from Point Clouds"
Unsupervised Learning for Cuboid Shape Abstraction via Joint Segmentation from Point Clouds This repository is a PyTorch implementation for paper: Uns
A multi-entity Transformer for multi-agent spatiotemporal modeling.
baller2vec This is the repository for the paper: Michael A. Alcorn and Anh Nguyen. baller2vec: A Multi-Entity Transformer For Multi-Agent Spatiotempor
Graph Self-Supervised Learning for Optoelectronic Properties of Organic Semiconductors
SSL_OSC Graph Self-Supervised Learning for Optoelectronic Properties of Organic Semiconductors
An Implicit Function Theorem (IFT) optimizer for bi-level optimizations
iftopt An Implicit Function Theorem (IFT) optimizer for bi-level optimizations. Requirements Python 3.7+ PyTorch 1.x Installation $ pip install git+ht
Python scripts for performing lane detection using the LSTR model in ONNX
ONNX LSTR Lane Detection Python scripts for performing lane detection using the Lane Shape Prediction with Transformers (LSTR) model in ONNX. Requirem
Re-implementation of 'Grokking: Generalization beyond overfitting on small algorithmic datasets'
Re-implementation of the paper 'Grokking: Generalization beyond overfitting on small algorithmic datasets' Paper Original paper can be found here Data
Official implementation for the paper "Attentive Prototypes for Source-free Unsupervised Domain Adaptive 3D Object Detection"
Attentive Prototypes for Source-free Unsupervised Domain Adaptive 3D Object Detection PyTorch code release of the paper "Attentive Prototypes for Sour
Rule Extraction Methods for Interactive eXplainability
REMIX: Rule Extraction Methods for Interactive eXplainability This repository contains a variety of tools and methods for extracting interpretable rul
Optimal space decomposition based-product quantization for approximate nearest neighbor search
Optimal space decomposition based-product quantization for approximate nearest neighbor search Abstract Product quantization(PQ) is an effective neare
This repo contains implementation of different architectures for emotion recognition in conversations.
Emotion Recognition in Conversations Updates π₯ π₯ π₯ Date Announcements 03/08/2021 π π We have released a new dataset M2H2: A Multimodal Multiparty
Nvidia Semantic Segmentation monorepo
Paper | YouTube | Cityscapes Score Pytorch implementation of our paper Hierarchical Multi-Scale Attention for Semantic Segmentation. Please refer to t
The pytorch implementation of the paper "text-guided neural image inpainting" at MM'2020
TDANet: Text-Guided Neural Image Inpainting, MM'2020 (Oral) MM | ArXiv This repository implements the paper "Text-Guided Neural Image Inpainting" by L
[ICCV2021] Learning to Track Objects from Unlabeled Videos
Unsupervised Single Object Tracking (USOT) πΏ Learning to Track Objects from Unlabeled Videos Jilai Zheng, Chao Ma, Houwen Peng and Xiaokang Yang 2021