Image reconstruction done with untrained neural networks.

Overview

PyTorch Deep Image Prior

An implementation of image reconstruction methods from Deep Image Prior (Ulyanov et al., 2017) in PyTorch.

The point of the paper is to execute some common image manipulation tasks using neural networks untrained on data prior to use.

Architectures differ from those used in the actual paper. The authors use some specific networks for specific tasks. This repo uses a couple of alternative architectures to produce similar results. One where upsampling is done on the basis of pixel shuffling, and the other using transposed convolutions. Pixel shuffling results in some hotspots that do not disappear with further training.

Requirements

Python3 with PyTorch, torchvision and NumPy. CUDA and cuDNN are optional (settable within the script in a self-explanatory way) but strongly recommended.

To use

It's relatively easy to play around with the settings from within the scripts. To reproduce the results in the repo, do the following.

Make a directory to hold the network output:

mkdir output

Generate output images with:

python3 deep_image_prior.py

Consolidate output images into a training gif and sample some actual data with:

python3 parse_ec2_results.py

Results

Note that the images here have been downsampled for formatting sensibly in the README. Full sized samples are in the repo if you would like to have a closer look.

Training was done over 25k iterations on an Amazon GPU instance. Takes roughly an hour on 512x512 images.

Upsampling with transposed convolutions:

Note the grid like speckles during training. These are caused by convolutional kernels overlapping with one another during upsampling.

Ground truth Input Output Training
truth deconstructed actuals actuals

Upsampling with pixel shuffling:

No speckles, however there is a hotspot (in the out of focus region towards the bunny's behind) that becomes a black spot. The appearance of these hotspots seems commonplace through both architectures, but the extra smoothness given by the convolution transpose layers repairs these more effectively.

Ground truth Input Output Training
truth deconstructed actuals actuals
Owner
Atiyo Ghosh
Atiyo Ghosh
Plato: A New Framework for Federated Learning Research

a new software framework to facilitate scalable federated learning research.

System <a href=[email protected] Lab"> 192 Jan 05, 2023
RodoSol-ALPR Dataset

RodoSol-ALPR Dataset This dataset, called RodoSol-ALPR dataset, contains 20,000 images captured by static cameras located at pay tolls owned by the Ro

Rayson Laroca 45 Dec 15, 2022
A python script to lookup Passport Index Dataset

visa-cli A python script to lookup Passport Index Dataset Installation pip install visa-cli Usage usage: visa-cli [-h] [-d DESTINATION_COUNTRY] [-f]

rand-net 16 Oct 18, 2022
Vector.ai assignment

fabio-tests-nisargatman Low Level Approach: ###Tables: continents: id*, name, population, area, createdAt, updatedAt countries: id*, name, population,

Ravi Pullagurla 1 Nov 09, 2021
MANO hand model porting for the GraspIt simulator

Learning Joint Reconstruction of Hands and Manipulated Objects - ManoGrasp Porting the MANO hand model to GraspIt! simulator Yana Hasson, Gül Varol, D

Lucas Wohlhart 10 Feb 08, 2022
Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and Beyond

CRF - Conditional Random Fields A library for dense conditional random fields (CRFs). This is the official accompanying code for the paper Regularized

Đ.Khuê Lê-Huu 21 Nov 26, 2022
We propose a new method for effective shadow removal by regarding it as an exposure fusion problem.

Auto-exposure fusion for single-image shadow removal We propose a new method for effective shadow removal by regarding it as an exposure fusion proble

Qing Guo 146 Dec 31, 2022
Official implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"

DiscoGAN Official PyTorch implementation of Learning to Discover Cross-Domain Relations with Generative Adversarial Networks. Prerequisites Python 2.7

SK T-Brain 754 Dec 29, 2022
Create UIs for prototyping your machine learning model in 3 minutes

Note: We just launched Hosted, where anyone can upload their interface for permanent hosting. Check it out! Welcome to Gradio Quickly create customiza

Gradio 11.7k Jan 07, 2023
Perform Linear Classification with Multi-way Data

MultiwayClassification This is an R package to perform linear classification for data with multi-way structure. The distance-weighted discrimination (

Eric F. Lock 2 Dec 15, 2020
NeurIPS 2021 paper 'Representation Learning on Spatial Networks' code

Representation Learning on Spatial Networks This repository is the official implementation of Representation Learning on Spatial Networks. Training Ex

13 Dec 29, 2022
PyTorch implementation of Progressive Growing of GANs for Improved Quality, Stability, and Variation.

PyTorch implementation of Progressive Growing of GANs for Improved Quality, Stability, and Variation. Warning: the master branch might collapse. To ob

559 Dec 14, 2022
The ARCA23K baseline system

ARCA23K Baseline System This is the source code for the baseline system associated with the ARCA23K dataset. Details about ARCA23K and the baseline sy

4 Jul 02, 2022
Hierarchical Aggregation for 3D Instance Segmentation (ICCV 2021)

HAIS Hierarchical Aggregation for 3D Instance Segmentation (ICCV 2021) by Shaoyu Chen, Jiemin Fang, Qian Zhang, Wenyu Liu, Xinggang Wang*. (*) Corresp

Hust Visual Learning Team 145 Jan 05, 2023
【Arxiv】Exploring Separable Attention for Multi-Contrast MR Image Super-Resolution

SANet Exploring Separable Attention for Multi-Contrast MR Image Super-Resolution Dependencies numpy==1.18.5 scikit_image==0.16.2 torchvision==0.8.1 to

36 Jan 05, 2023
Unoffical reMarkable AddOn for Firefox.

reMarkable for Firefox (Download) This repo converts the offical reMarkable Chrome Extension into a Firefox AddOn published here under the name "Unoff

Jelle Schutter 45 Nov 28, 2022
Safe Bayesian Optimization

SafeOpt - Safe Bayesian Optimization This code implements an adapted version of the safe, Bayesian optimization algorithm, SafeOpt [1], [2]. It also p

Felix Berkenkamp 111 Dec 11, 2022
EncT5: Fine-tuning T5 Encoder for Non-autoregressive Tasks

EncT5 (Unofficial) Pytorch Implementation of EncT5: Fine-tuning T5 Encoder for Non-autoregressive Tasks About Finetune T5 model for classification & r

Jangwon Park 34 Jan 01, 2023
buildseg is a building extraction plugin of QGIS based on PaddlePaddle.

buildseg buildseg is a building extraction plugin of QGIS based on PaddlePaddle. TODO Extract building on 512x512 remote sensing images. Extract build

Yizhou Chen 11 Sep 26, 2022
"Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback"

This is code repo for our EMNLP 2017 paper "Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback", which implements the A2C algorithm on top of a neural encoder-

Khanh Nguyen 131 Oct 21, 2022