===================================== 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
A deep learning framework for historical document image analysis
DIVA-DAF Description A deep learning framework for historical document image analysis. How to run Install dependencies # clone project git clone https
Voice of Pajlada with model and weights.
Pajlada TTS Stripped down version of ForwardTacotron (https://github.com/as-ideas/ForwardTacotron) with pretrained weights for Pajlada's (https://gith
Loopy belief propagation for factor graphs on discrete variables, in JAX!
PGMax implements general factor graphs for discrete probabilistic graphical models (PGMs), and hardware-accelerated differentiable loopy belief propagation (LBP) in JAX.
Finetune alexnet with tensorflow - Code for finetuning AlexNet in TensorFlow >= 1.2rc0
Finetune AlexNet with Tensorflow Update 15.06.2016 I revised the entire code base to work with the new input pipeline coming with TensorFlow = versio
LSTM-VAE Implementation and Relevant Evaluations
LSTM-VAE Implementation and Relevant Evaluations Before using any file in this repository, please create two directories under the root directory name
Siamese-nn-semantic-text-similarity - A repository containing comprehensive Neural Networks based PyTorch implementations for the semantic text similarity task
Siamese Deep Neural Networks for Semantic Text Similarity PyTorch A repository c
Easy-to-use,Modular and Extendible package of deep-learning based CTR models .
DeepCTR DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can
DeepMoCap: Deep Optical Motion Capture using multiple Depth Sensors and Retro-reflectors
DeepMoCap: Deep Optical Motion Capture using multiple Depth Sensors and Retro-reflectors By Anargyros Chatzitofis, Dimitris Zarpalas, Stefanos Kollias
This is an official implementation of "Polarized Self-Attention: Towards High-quality Pixel-wise Regression"
Polarized Self-Attention: Towards High-quality Pixel-wise Regression This is an official implementation of: Huajun Liu, Fuqiang Liu, Xinyi Fan and Don
DivNoising is an unsupervised denoising method to generate diverse denoised samples for any noisy input image. This repository contains the code to reproduce the results reported in the paper https://openreview.net/pdf?id=agHLCOBM5jP
DivNoising: Diversity Denoising with Fully Convolutional Variational Autoencoders Mangal Prakash1, Alexander Krull1,2, Florian Jug2 1Authors contribut
A framework for joint super-resolution and image synthesis, without requiring real training data
SynthSR This repository contains code to train a Convolutional Neural Network (CNN) for Super-resolution (SR), or joint SR and data synthesis. The met
Graph WaveNet apdapted for brain connectivity analysis.
Graph WaveNet for brain network analysis This is the implementation of the Graph WaveNet model used in our manuscript: S. Wein , A. Schüller, A. M. To
Pytorch based library to rank predicted bounding boxes using text/image user's prompts.
pytorch_clip_bbox: Implementation of the CLIP guided bbox ranking for Object Detection. Pytorch based library to rank predicted bounding boxes using t
Official implementation of "Motif-based Graph Self-Supervised Learning forMolecular Property Prediction"
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction Official Pytorch implementation of NeurIPS'21 paper "Motif-based Graph Se
Self-driving car env with PPO algorithm from stable baseline3
Self-driving car with RL stable baseline3 Most of the project develop from https://github.com/GerardMaggiolino/Gym-Medium-Post Please check it out! Th
Implementation of momentum^2 teacher
Momentum^2 Teacher: Momentum Teacher with Momentum Statistics for Self-Supervised Learning Requirements All experiments are done with python3.6, torch
Hard cater examples from Hopper ICLR paper
CATER-h Honglu Zhou*, Asim Kadav, Farley Lai, Alexandru Niculescu-Mizil, Martin Renqiang Min, Mubbasir Kapadia, Hans Peter Graf (*Contact: honglu.zhou
Code for our CVPR 2021 Paper "Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes".
Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes (CVPR 2021) Project page | Paper | Colab | Colab for Drawing App Rethinking Style
Edison AT is software Depression Assistant personal.
Edison AT Edison AT is software / program Depression Assistant personal. Feature: Analyze emotional real-time from face. Audio Edison(Comingsoon relea
MediaPipeのPythonパッケージのサンプルです。2020/12/11時点でPython実装のある4機能(Hands、Pose、Face Mesh、Holistic)について用意しています。
mediapipe-python-sample MediaPipeのPythonパッケージのサンプルです。 2020/12/11時点でPython実装のある以下4機能について用意しています。 Hands Pose Face Mesh Holistic Requirement mediapipe 0.