For auto aligning, cropping, and scaling HR and LR images for training image based neural networks

Related tags

Deep LearningImgAlign
Overview

ImgAlign

For auto aligning, cropping, and scaling HR and LR images for training image based neural networks

Usage

Make sure OpenCV is installed, 'pip install opencv-python' (OpenCV not yet working on python 3.10).

For now, the options are: mode (0 or 1), HR file name, LR file name, and scale (integer) in that other: ImgAlign.py mode HR LR scale

Example:

ImgAlign.py 0 HR.png LR.png 2

This is still very much a work in progress. I have fairly limited coding knowledge, but am always trying to pick up new things.

I'd like to add batch functionality so that it will automatically process each picture with matching names in HR and LR directories. I also need to make the argument input nicer.

This cannot handle rotations at the moment, but I am going to try to add that feature soon.

ImgAlign can scale height and width independently, but being more similar tends to give better results. For instance, DVD images are stored at 720x480 resolution, but are almost always displayed at 720x540 or 640x480 (Also known as anamorphic, where SAR≠PAR). To match that with a 1920x1080 image (SAR=PAR), you'd get better results prescaling the the LR image (or HR image) to the intended 720x540 or 640x480 (1920x1280, 1620x1080, 1440x960, etc. for HR) than leaving it at 720x480, although either way works.

Mode 0 is true to the LR file, meaning it maintains the resolution, aspect ratio, and orientation of the LR image, cropping where needed. The HR image is cropped, scaled, and translated accordingly.

Mode 1 is true to the HR image, maintaining its resolution, orientaion, and aspect ratio. The LR image is cropped, scaled, translated to match. I have not added a boundary check for this mode yet, so the HR image should be fully contained within the LR image, or else black bars will likely be added. I also haven't yet added a check to make sure the HR resolution is evenly divisible by scale, so be sure it is before using This mode only outputs a new LR image because, as stated, the HR should be contained in the other image, so no cropping is needed.

Starting Point/Credit

I used lines of code from this site to get started with basic alignment: https://learnopencv.com/feature-based-image-alignment-using-opencv-c-python/

You might also like...
Script that receives an Image (original) and a set of images to be used as
Script that receives an Image (original) and a set of images to be used as "pixels" in reconstruction of the Original image using the set of images as "pixels"

picinpics Script that receives an Image (original) and a set of images to be used as "pixels" in reconstruction of the Original image using the set of

An integration of several popular automatic augmentation methods, including OHL (Online Hyper-Parameter Learning for Auto-Augmentation Strategy) and AWS (Improving Auto Augment via Augmentation Wise Weight Sharing) by Sensetime Research.

An integration of several popular automatic augmentation methods, including OHL (Online Hyper-Parameter Learning for Auto-Augmentation Strategy) and AWS (Improving Auto Augment via Augmentation Wise Weight Sharing) by Sensetime Research.

Official code for On Path Integration of Grid Cells: Group Representation and Isotropic Scaling (NeurIPS 2021)
Official code for On Path Integration of Grid Cells: Group Representation and Isotropic Scaling (NeurIPS 2021)

On Path Integration of Grid Cells: Group Representation and Isotropic Scaling This repo contains the official implementation for the paper On Path Int

Unofficial PyTorch reimplementation of the paper Swin Transformer V2: Scaling Up Capacity and Resolution

PyTorch reimplementation of the paper Swin Transformer V2: Scaling Up Capacity and Resolution [arXiv 2021].

Implementation of the 😇 Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones
Implementation of the 😇 Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones

HaloNet - Pytorch Implementation of the Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones. This re

Implementation of "Scaled-YOLOv4: Scaling Cross Stage Partial Network" using PyTorch framwork.

YOLOv4-large This is the implementation of "Scaled-YOLOv4: Scaling Cross Stage Partial Network" using PyTorch framwork. YOLOv4-CSP YOLOv4-tiny YOLOv4-

[SIGGRAPH'22] StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets
[SIGGRAPH'22] StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets

[Project] [PDF] This repository contains code for our SIGGRAPH'22 paper "StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets" by Axel Sauer, Katja

FuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space OptimizationFuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space Optimization
FuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space OptimizationFuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space Optimization

FuseDream This repo contains code for our paper (paper link): FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimizat

Complex-Valued Neural Networks (CVNN)Complex-Valued Neural Networks (CVNN)

Complex-Valued Neural Networks (CVNN) Done by @NEGU93 - J. Agustin Barrachina Using this library, the only difference with a Tensorflow code is that y

Releases(Official_Release)
  • Official_Release(Dec 25, 2021)

    Now supports full homography mapping (warping), use option -f or --full to enable. Better alignment algorithm implemented for more accurate matching. 4x scale now much more reliable. Batch processing now does not halt when a match isn't found. Generates a log file for failed matches.

    Source code(tar.gz)
    Source code(zip)
    ImgAlign.exe(52.11 MB)
StyleGAN - Official TensorFlow Implementation

StyleGAN — Official TensorFlow Implementation Picture: These people are not real – they were produced by our generator that allows control over differ

NVIDIA Research Projects 13.1k Jan 09, 2023
GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily

GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily Abstract Graph Neural Networks (GNNs) are widely used on a

10 Dec 20, 2022
DvD-TD3: Diversity via Determinants for TD3 version

DvD-TD3: Diversity via Determinants for TD3 version The implementation of paper Effective Diversity in Population Based Reinforcement Learning. Instal

3 Feb 11, 2022
Unpaired Caricature Generation with Multiple Exaggerations

CariMe-pytorch The official pytorch implementation of the paper "CariMe: Unpaired Caricature Generation with Multiple Exaggerations" CariMe: Unpaired

Gu Zheng 37 Dec 30, 2022
City-seeds - A random generator of cultural characteristics intended to spark ideas and help draw threads

City Seeds This is a random generator of cultural characteristics intended to sp

Aydin O'Leary 2 Mar 12, 2022
AquaTimer - Programmable Timer for Aquariums based on ATtiny414/814/1614

AquaTimer - Programmable Timer for Aquariums based on ATtiny414/814/1614 AquaTimer is a programmable timer for 12V devices such as lighting, solenoid

Stefan Wagner 4 Jun 13, 2022
PyTorch implementation of "Debiased Visual Question Answering from Feature and Sample Perspectives" (NeurIPS 2021)

D-VQA We provide the PyTorch implementation for Debiased Visual Question Answering from Feature and Sample Perspectives (NeurIPS 2021). Dependencies P

Zhiquan Wen 19 Dec 22, 2022
TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow

TensorFlow 101: Introduction to Deep Learning I have worked all my life in Machine Learning, and I've never seen one algorithm knock over its benchmar

Sefik Ilkin Serengil 896 Jan 04, 2023
Start-to-finish tutorial for interactive music co-creation in PyTorch and Tensorflow.js

Start-to-finish tutorial for interactive music co-creation in PyTorch and Tensorflow.js

Chris Donahue 98 Dec 14, 2022
The official code for paper "R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Modeling".

R2D2 This is the official code for paper titled "R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Mode

Alipay 49 Dec 17, 2022
PyTorch code for our paper "Image Super-Resolution with Non-Local Sparse Attention" (CVPR2021).

Image Super-Resolution with Non-Local Sparse Attention This repository is for NLSN introduced in the following paper "Image Super-Resolution with Non-

143 Dec 28, 2022
ICRA 2021 - Robust Place Recognition using an Imaging Lidar

Robust Place Recognition using an Imaging Lidar A place recognition package using high-resolution imaging lidar. For best performance, a lidar equippe

Tixiao Shan 293 Dec 27, 2022
Spectral Temporal Graph Neural Network (StemGNN in short) for Multivariate Time-series Forecasting

Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting This repository is the official implementation of Spectral Temporal Gr

Microsoft 306 Dec 29, 2022
Voila - Voilà turns Jupyter notebooks into standalone web applications

Rendering of live Jupyter notebooks with interactive widgets. Introduction Voilà turns Jupyter notebooks into standalone web applications. Unlike the

Voilà Dashboards 4.5k Jan 03, 2023
A Keras implementation of CapsNet in the paper: Sara Sabour, Nicholas Frosst, Geoffrey E Hinton. Dynamic Routing Between Capsules

NOTE This implementation is fork of https://github.com/XifengGuo/CapsNet-Keras , applied to IMDB texts reviews dataset. CapsNet-Keras A Keras implemen

Lauro Moraes 5 Oct 23, 2022
Optical Character Recognition + Instance Segmentation for russian and english languages

Распознавание рукописного текста в школьных тетрадях Соревнование, проводимое в рамках олимпиады НТО, разработанное Сбером. Платформа ODS. Результаты

Gerasimov Maxim 21 Dec 19, 2022
SPCL: A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive Learning

SPCL SPCL: A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive Learning Update on 2021/11/25: ArXiv Ver

Binhui Xie (谢斌辉) 11 Oct 29, 2022
Meaningful titles for tabs and PDF downloads! Also supports tab search.

arxiv-utils If you are a researcher that reads a lot on ArXiv, you'll benefit a lot from this web extension. Renames the title of PDF page to the pape

Johnson 174 Dec 20, 2022
rliable is an open-source Python library for reliable evaluation, even with a handful of runs, on reinforcement learning and machine learnings benchmarks.

Open-source library for reliable evaluation on reinforcement learning and machine learning benchmarks. See NeurIPS 2021 oral for details.

Google Research 529 Jan 01, 2023
[ICCV 2021] Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification

Counterfactual Attention Learning Created by Yongming Rao*, Guangyi Chen*, Jiwen Lu, Jie Zhou This repository contains PyTorch implementation for ICCV

Yongming Rao 90 Dec 31, 2022