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layeredimage

Use this module to read, and write to a number of layered image formats

    2024.2

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LayeredImage

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Use this module to read, and write to a number of layered image formats

Compatibility

Bear in mind that the tables below may not be completely accurate. If that is the case, please open an issue and I will fix the tables.

Overview

Key
  • ✔ - Supported
  • ⚠ - Things will look the same, but data is lost
  • ❌ - This is not supported and will cause loss of data
  • N/A - The source format does not support this so treat this as a ✔
Format.ora.pdn.xcf.psd.tiff/ .tif.webp.gif.lsr
Read
Layers
GroupsN/AN/AN/AN/A
Write
Reading - Group
Format.ora.pdn.xcf.psd.tiff/ .tif.webp.gif.lsr
NameN/AN/AN/AN/A
DimensionsN/AN/AN/AN/A
OffsetsN/AN/AN/AN/A
OpacityN/AN/AN/AN/AN/A
VisibilityN/AN/AN/AN/AN/A
Blend ModeN/AN/AN/AN/AN/A
Reading - Layer
Format.ora.pdn.xcf.psd.tiff/ .tif.webp.gif.lsr
Name
Dimensions
OffsetsN/AN/AN/AN/A
OpacityN/AN/AN/AN/A
VisibilityN/AN/AN/AN/A
Blend ModeN/AN/AN/AN/A
Writing - Group
Format.ora.pdn.xcf.psd.tiff/ .tif.webp.gif.lsr
Name
Dimensions
Offsets
Opacity
Visibility
Blend Mode
Layers are extracted from groups and saved to TIFF/ GIF or WEBP
Writing - Layer
Format.ora.pdn.xcf.psd.tiff/ .tif.webp.gif.lsr
Name
Dimensions
Offsets
Opacity
Visibility
Blend Mode
Layers are rendered with offsets before being written to TIFF/ GIF or WEBP
First child layers are placed in a group when written to LSR

.layered

.layered is highly inspired by the open raster format and aims to provide an exchange format in the cases when saving in ora would cause unacceptable data loss. .layered has been designed so that if the format became deprecated and no readers existed for it tomorrow, the data would be easily salvageable.

See the LAYERED_SPEC for more information.

Example Usage

Here's some basic example usage below.

"""Example module """
from pathlib import Path
THISDIR = str(Path(__file__).resolve().parent)
import layeredimage.io

# Do stuff
ora = layeredimage.io.openLayerImage(f"{THISDIR}/image.ora")

imageDimensions = ora.dimensions
# There are a load of handy functions for getting layers, and adding new
# layers, but here we will act directly on the object
layer = ora.layersAndGroups[0] # For the sake of the e.g. this is a layer

# Lets overwrite the layer with a transparent image (bit boring I know...)
layer.image = Image.new("RGBA", imageDimensions)
ora.layersAndGroups[0] = layer

# And let's save
layeredimage.io.saveLayerImage(f"{THISDIR}/image(modified).ora", ora)

# Let's save a flattened version too
ora.getFlattenLayers().save(f"{THISDIR}/image(modified).png")

# Doing stuff with a group
group = ora.getLayerOrGroup(1) # For the sake of the e.g. this is a group
group.layers[0].image.show() # Open the image of the first layer of the group

# Deleting a layer/ group
ora.removeLayerOrGroup(2)

Images are PIL.Image (s) and so you can use the power of Pillow to apply filters, and other modifications to the images.

See below for an old version of the tests. These provide a few examples of file conversions. Not going to get 100% coverage anytime soon but hopefully this will help a little.

"""Test module """

import sys
import os
from pathlib import Path
THISDIR = str(Path(__file__).resolve().parent)
sys.path.insert(0, os.path.dirname(THISDIR))
import layeredimage.io

# ORA
ora = layeredimage.io.openLayerImage(f"{THISDIR}/base24.ora")
layeredimage.io.saveLayerImage(f"{THISDIR}/base24(ora).ora", ora)
layeredimage.io.saveLayerImage(f"{THISDIR}/base24(ora).tiff", ora)
ora.getFlattenLayers().save(f"{THISDIR}/base24(ora).png")

# PSD
psd = layeredimage.io.openLayerImage(f"{THISDIR}/base24.psd")
layeredimage.io.saveLayerImage(f"{THISDIR}/base24(psd).ora", psd)
layeredimage.io.saveLayerImage(f"{THISDIR}/base24(psd).tiff", psd)
psd.getFlattenLayers().save(f"{THISDIR}/base24(psd).png")

# PDN
pdn = layeredimage.io.openLayerImage(f"{THISDIR}/base24.pdn")
layeredimage.io.saveLayerImage(f"{THISDIR}/base24(pdn).ora", pdn)
layeredimage.io.saveLayerImage(f"{THISDIR}/base24(pdn).tiff", pdn)
pdn.getFlattenLayers().save(f"{THISDIR}/base24(pdn).png")

# XCF
xcf = layeredimage.io.openLayerImage(f"{THISDIR}/base24.xcf")
layeredimage.io.saveLayerImage(f"{THISDIR}/base24(xcf).ora", xcf)
layeredimage.io.saveLayerImage(f"{THISDIR}/base24(xcf).tiff", xcf)
xcf.getFlattenLayers().save(f"{THISDIR}/base24(xcf).png")

# TIFF
tiff = layeredimage.io.openLayerImage(f"{THISDIR}/base24.tiff")
layeredimage.io.saveLayerImage(f"{THISDIR}/base24(tiff).ora", tiff)
layeredimage.io.saveLayerImage(f"{THISDIR}/base24(tiff).tiff", tiff)
tiff.getFlattenLayers().save(f"{THISDIR}/base24(tiff).png")

Documentation

A high-level overview of how the documentation is organized organized will help you know where to look for certain things:

  • The Technical Reference documents APIs and other aspects of the machinery. This documentation describes how to use the classes and functions at a lower level and assume that you have a good high-level understanding of the software.

Install With PIP

pip install layeredimage

Head to https://pypi.org/project/layeredimage/ for more info

Language information

Built for

This program has been written for Python versions 3.8 - 3.11 and has been tested with both 3.8 and 3.11

Install Python on Windows

Chocolatey

choco install python

Windows - Python.org

To install Python, go to https://www.python.org/downloads/windows/ and download the latest version.

Install Python on Linux

Apt

sudo apt install python3.x

Dnf

sudo dnf install python3.x

Install Python on MacOS

Homebrew

brew install python@3.x

MacOS - Python.org

To install Python, go to https://www.python.org/downloads/macos/ and download the latest version.

How to run

Windows

  • Module py -3.x -m [module] or [module] (if module installs a script)

  • File py -3.x [file] or ./[file]

Linux/ MacOS

  • Module python3.x -m [module] or [module] (if module installs a script)

  • File python3.x [file] or ./[file]

Building

This project uses https://github.com/FHPythonUtils/FHMake to automate most of the building. This command generates the documentation, updates the requirements.txt and builds the library artefacts

Note the functionality provided by fhmake can be approximated by the following

handsdown  --cleanup -o documentation/reference
poetry export -f requirements.txt --output requirements.txt
poetry export -f requirements.txt --with dev --output requirements_optional.txt
poetry build

fhmake audit can be run to perform additional checks

Testing

For testing with the version of python used by poetry use

poetry run pytest

Alternatively use tox to run tests over python 3.8 - 3.11

tox

Download Project

Clone

Using The Command Line
  1. Press the Clone or download button in the top right

  2. Copy the URL (link)

  3. Open the command line and change directory to where you wish to clone to

  4. Type 'git clone' followed by URL in step 2

    git clone https://github.com/FHPythonUtils/LayeredImage
    

More information can be found at https://help.github.com/en/articles/cloning-a-repository

Using GitHub Desktop
  1. Press the Clone or download button in the top right
  2. Click open in desktop
  3. Choose the path for where you want and click Clone

More information can be found at https://help.github.com/en/desktop/contributing-to-projects/cloning-a-repository-from-github-to-github-desktop

Download Zip File

  1. Download this GitHub repository
  2. Extract the zip archive
  3. Copy/ move to the desired location

Community Files

Licence

MIT License Copyright (c) FredHappyface (See the LICENSE for more information.)

Changelog

See the Changelog for more information.

Code of Conduct

Online communities include people from many backgrounds. The Project contributors are committed to providing a friendly, safe and welcoming environment for all. Please see the Code of Conduct for more information.

Contributing

Contributions are welcome, please see the Contributing Guidelines for more information.

Security

Thank you for improving the security of the project, please see the Security Policy for more information.

Support

Thank you for using this project, I hope it is of use to you. Please be aware that those involved with the project often do so for fun along with other commitments (such as work, family, etc). Please see the Support Policy for more information.

Rationale

The rationale acts as a guide to various processes regarding projects such as the versioning scheme and the programming styles used. Please see the Rationale for more information.

FAQs


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Socket installs a GitHub app to automatically flag issues on every pull request and report the health of your dependencies. Find out what is inside your node modules and prevent malicious activity before you update the dependencies.

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