Apply a perspective transformation to a raster image inside Inkscape (no need to use an external software such as GIMP or Krita).

Related tags

Deep Learningsvginkscapeinkscape-extensionperspective-transformation
Overview

Raster Perspective

Apply a perspective transformation to bitmap image using the selected path as envelope, without the need to use an external software to transform the image.

Installation:

On Linux:

cd $HOME/.config/inkscape/extensions
git clone https://github.com/s1291/InkRasterPerspective.git
  • Open Inkscape (if it is already open, close then re-open it) and you should find the extension under: Extensions > Raster Perspective > Perspective

On Windows:

  • Download the most recent version (direct link: zip)
  • Extract it and copy the files imagePerspective.py and imagePerspective.inx to C:\Program Files\Inkscape\share\inkscape\extensions

How to use

(This extension was tested with both Inkscape 1.1.1 and 1.2-dev on GNU/Linux Ubuntu 20.04.3)

  1. Select the raster image and the quadrangle path (envelope) . Make sure the envelope nodes are ordered as follows:

order of enveloppe nodes

For more details on how to find the nodes order for a path, check out this post.

  1. Extensions > Raster Perspective > Perspective

See below:

How to use the extension

Author

Samir OUCHENE, 2021-2022

All code is licensed under the GNU General Public License version 3. See the license file for details.

You might also like...
Applicator Kit for Modo allow you to apply Apple ARKit Face Tracking data from your iPhone or iPad to your characters in Modo.

Applicator Kit for Modo Applicator Kit for Modo allow you to apply Apple ARKit Face Tracking data from your iPhone or iPad with a TrueDepth camera to

Andrew Buttigieg 3 Aug 24, 2021
Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Datset)

Graphlevel-SSL Overview Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Dataset). It is unified framework to co

JunSeok 8 Oct 15, 2021
Apply our monocular depth boosting to your own network!
Apply our monocular depth boosting to your own network!

MergeNet - Boost Your Own Depth Boost custom or edited monocular depth maps using MergeNet Input Original result After manual editing of base You can

Computational Photography Lab @ SFU 142 Dec 17, 2022
Apply AnimeGAN-v2 across frames of a video clip

title emoji colorFrom colorTo sdk app_file pinned AnimeGAN-v2 For Videos 🔥 blue red gradio app.py false AnimeGAN-v2 For Videos Apply AnimeGAN-v2 acro

Nathan Raw 36 Oct 18, 2022
IJON is an annotation mechanism that analysts can use to guide fuzzers such as AFL.
IJON is an annotation mechanism that analysts can use to guide fuzzers such as AFL.

IJON SPACE EXPLORER IJON is an annotation mechanism that analysts can use to guide fuzzers such as AFL. Using only a small (usually one line) annotati

Chair for Sys­tems Se­cu­ri­ty 146 Dec 16, 2022
External Attention Network

Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks paper : https://arxiv.org/abs/2105.02358 Jittor code will come soon

MenghaoGuo 357 Dec 11, 2022
External Attention Network

Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks paper : https://arxiv.org/abs/2105.02358 EAMLP will come soon Jitto

MenghaoGuo 357 Dec 11, 2022
VID-Fusion: Robust Visual-Inertial-Dynamics Odometry for Accurate External Force Estimation
VID-Fusion: Robust Visual-Inertial-Dynamics Odometry for Accurate External Force Estimation

VID-Fusion VID-Fusion: Robust Visual-Inertial-Dynamics Odometry for Accurate External Force Estimation Authors: Ziming Ding , Tiankai Yang, Kunyi Zhan

ZJU FAST Lab 86 Nov 18, 2022
[ACL-IJCNLP 2021] Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning

CLNER The code is for our ACL-IJCNLP 2021 paper: Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning CLNER is a

null 71 Dec 8, 2022
Comments
  • Inkscape 1.2.1: PIL.UnidentifiedImageError: cannot identify image file if image is linked instead of embedded.

    Inkscape 1.2.1: PIL.UnidentifiedImageError: cannot identify image file if image is linked instead of embedded.

    Since I used a quite old version in issue #3, I thought I'd better upgrade to the latest version of Inkscape. Now I get this error:

    Traceback (most recent call last): File "C:\Program Files\Inkscape\share\inkscape\extensions\imagePerspective.py", line 179, in imagePerspective.run() File "C:\Program Files\Inkscape\share\inkscape\extensions\inkex\base.py", line 231, in run self.save_raw(self.effect()) File "C:\Program Files\Inkscape\share\inkscape\extensions\imagePerspective.py", line 123, in effect orig_image = PIL_Image.open(io.BytesIO(img_data)) File "C:\Program Files\Inkscape\lib\python3.10\site-packages\PIL\Image.py", line 3147, in open raise UnidentifiedImageError( PIL.UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x000001ca3022c900>

    My image is a 1314x2592 pixel 24 bit PNG file with a size of 6.99 MB, if that matters. Same error for a 3072x2048 pixel 8 bit BMP file with a size of 6 MB.

    The problem disappears if the file is embedded instead of linked. image

    opened by WelliSolutions 10
  • Inkscape 1.0.2-2: Your selection must contain an image and a path with at least 4 points.

    Inkscape 1.0.2-2: Your selection must contain an image and a path with at least 4 points.

    I tried the extension with Inkscape 1.0.2-2 on Windows 10 and I got the error message:

    Your selection must contain an image and a path with at least 4 points.

    I'm 100% sure I do the steps correctly. Here's how my selection looks like when I invoke the command.

    image

    I don't know how to debug the extension in Inkscape, but I have debugging skills in general. Maybe I just need a pointer on how to enable extension debugging.

    opened by WelliSolutions 2
  • Image distorted when resized in a non-uniform way (aspect ratio changed)

    Image distorted when resized in a non-uniform way (aspect ratio changed)

    First of all thanks for this awesome extension. This is exactly what I need.

    The following does not happen for all images. I have not yet identified criteria when it happens or when it doesn't.

    Using commit https://github.com/s1291/InkRasterPerspective/commit/897d8eb4532eac2032d4dc17f8c30fe4c3b053fe which fixes #4 so I can use linked images.

    I start with a linked image like this 1280x960 pixel 24 bit 3.5 MB BMP file:

    image

    and I get this result

    image

    Note the lower right corner which doesn't match the path.

    opened by WelliSolutions 2
  • Not working on windows - issues with deconstructing self.svg.selection and uuto unit

    Not working on windows - issues with deconstructing self.svg.selection and uuto unit

    Using this package on windows had to fix this error.

    issue:

    will not deconstruct the_image_node, envelope_node = self.svg.selection error of missing expected atribute units when calling unit_to_vp

    Created fix and will submit.

    Thanks for the excellent package.

    needs info 
    opened by cia05rf 5
Releases(v1.0.1)
Owner
s.ouchene
s.ouchene
GitHub Repository
Efficient training of deep recommenders on cloud.

HybridBackend Introduction HybridBackend is a training framework for deep recommenders which bridges the gap between evolving cloud infrastructure and

Alibaba 111 Dec 23, 2022
Detectron2-FC a fast construction platform of neural network algorithm based on detectron2

What is Detectron2-FC Detectron2-FC a fast construction platform of neural network algorithm based on detectron2. We have been working hard in two dir

董晋宗 9 Jun 06, 2022
Minimal implementation of Denoised Smoothing: A Provable Defense for Pretrained Classifiers in TensorFlow.

Denoised-Smoothing-TF Minimal implementation of Denoised Smoothing: A Provable Defense for Pretrained Classifiers in TensorFlow. Denoised Smoothing is

Sayak Paul 19 Dec 11, 2022
A collection of IPython notebooks covering various topics.

ipython-notebooks This repo contains various IPython notebooks I've created to experiment with libraries and work through exercises, and explore subje

John Wittenauer 2.6k Jan 01, 2023
Official code for paper "Demystifying Local Vision Transformer: Sparse Connectivity, Weight Sharing, and Dynamic Weight"

Demysitifing Local Vision Transformer, arxiv This is the official PyTorch implementation of our paper. We simply replace local self attention by (dyna

138 Dec 28, 2022
Fast and accurate optimisation for registration with little learningconvexadam

convexAdam Learn2Reg 2021 Submission Fast and accurate optimisation for registration with little learning Excellent results on Learn2Reg 2021 challeng

17 Dec 06, 2022
这是一个yolox-pytorch的源码，可以用于训练自己的模型。

YOLOX：You Only Look Once目标检测模型在Pytorch当中的实现 目录 性能情况 Performance 实现的内容 Achievement 所需环境 Environment 小技巧的设置 TricksSet 文件下载 Download 训练步骤 How2train 预测步骤

Bubbliiiing 613 Jan 05, 2023
Code for Understanding Pooling in Graph Neural Networks

Select, Reduce, Connect This repository contains the code used for the experiments of: "Understanding Pooling in Graph Neural Networks" Setup Install

Daniele Grattarola 37 Dec 13, 2022
Morphable Detector for Object Detection on Demand

Morphable Detector for Object Detection on Demand (ICCV 2021) PyTorch implementation of the paper Morphable Detector for Object Detection on Demand. I

9 Feb 23, 2022
AugLiChem - The augmentation library for chemical systems.

AugLiChem Welcome to AugLiChem! The augmentation library for chemical systems. This package supports augmentation for both crystaline and molecular sy

BaratiLab 17 Jan 08, 2023
Code for Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data? (SDM 2022)

Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data? (SDM 2022) We consider how a user of a web servi

joisino 20 Aug 21, 2022
Multi-View Radar Semantic Segmentation

Multi-View Radar Semantic Segmentation Paper Multi-View Radar Semantic Segmentation, ICCV 2021. Arthur Ouaknine, Alasdair Newson, Patrick Pérez, Flore

valeo.ai 37 Oct 25, 2022
Official Pytorch implementation for AAAI2021 paper (RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning)

RSPNet Official Pytorch implementation for AAAI2021 paper "RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning" [Suppleme

35 Jun 24, 2022
DCA - Official Python implementation of Delaunay Component Analysis algorithm

Delaunay Component Analysis (DCA) Official Python implementation of the Delaunay

Petra Poklukar 9 Sep 06, 2022
MVS2D: Efficient Multi-view Stereo via Attention-Driven 2D Convolutions

MVS2D: Efficient Multi-view Stereo via Attention-Driven 2D Convolutions Project Page | Paper If you find our work useful for your research, please con

96 Jan 04, 2023
Dataset Condensation with Contrastive Signals

Dataset Condensation with Contrastive Signals This repository is the official implementation of Dataset Condensation with Contrastive Signals (DCC). T

3 May 19, 2022
SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks (Scientific Reports)

SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks Molecular interaction networks are powerful resources for the discovery. While dee

Kexin Huang 49 Oct 15, 2022
SciPy fixes and extensions

scipyx SciPy is large library used everywhere in scientific computing. That's why breaking backwards-compatibility comes as a significant cost and is

Nico Schlömer 16 Jul 17, 2022
Official implementation of NeurIPS 2021 paper "Contextual Similarity Aggregation with Self-attention for Visual Re-ranking"

CSA: Contextual Similarity Aggregation with Self-attention for Visual Re-ranking PyTorch training code for CSA (Contextual Similarity Aggregation). We

Hui Wu 19 Oct 21, 2022
An essential implementation of BYOL in PyTorch + PyTorch Lightning

Essential BYOL A simple and complete implementation of Bootstrap your own latent: A new approach to self-supervised Learning in PyTorch + PyTorch Ligh

Enrico Fini 48 Sep 27, 2022