Open Source Python Graphic Design Software
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Python Graphic Design Software
View 159 business solutionsBrowse free open source Python Graphic Design Software and projects below. Use the toggles on the left to filter open source Python Graphic Design Software by OS, license, language, programming language, and project status.
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Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
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Dia Diagram Editor
Free drawing software for Windows, Mac OS X, and Linux
Dia Diagram Editor is free Open Source drawing software for Windows, Mac OS X and Linux. Dia supports more than 30 different diagram types like flowcharts, network diagrams, database models. More than a thousand readymade objects help to draw professional diagrams. Dia can read and write a number of different raster and vector image formats. Software developers and database specialists can use Dia as a CASE tool to generate code skeletons from their drawings. Dia can be scripted and extended using Python. -
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FreeImage is a library project for developers who would like to support popular graphics image formats (PNG, JPEG, TIFF, BMP and others). Some highlights are: extremely simple in use, not limited to the local PC (unique FreeImageIO) and Plugin driven!
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Developer's Image Library
A full featured cross-platform image library
Developer's Image Library (DevIL) is a cross-platform image library utilizing a simple syntax to load, save, convert, manipulate, filter and display a variety of images with ease. -
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MoviePy
Video editing with Python
MoviePy is a Python module for video editing, which can be used for basic operations (like cuts, concatenations, title insertions), video compositing (a.k.a. non-linear editing), video processing, or to create advanced effects. It can read and write the most common video formats, including GIF. MoviePy is an open source software originally written by Zulko and released under the MIT licence. It works on Windows, Mac, and Linux, with Python 2 or Python 3. The code is hosted on Github, where you can push improvements, report bugs and ask for help. There is also a MoviePy forum on Reddit and a mailing list on librelist. MoviePy depends on the Python modules NumPy, Imageio, Decorator, and Proglog, which will be automatically installed during MoviePy's installation. The software FFMPEG should be automatically downloaded/installed (by imageio) during your first use of MoviePy (installation will take a few seconds). -
Secure remote access solution to your private network, in the cloud or on-prem.OpenVPN is here to bring simple, flexible, and cost-effective secure remote access to companies of all sizes, regardless of where their resources are located.
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Asymptote
2D & 3D TeX-Aware Vector Graphics Language
Asymptote is a powerful descriptive vector graphics language for technical drawing, inspired by MetaPost but with an improved C++-like syntax. Asymptote provides for figures the same high-quality typesetting that LaTeX does for scientific text. -
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Lama Cleaner
Image inpainting tool powered by SOTA AI Model
Image inpainting tool powered by SOTA AI Model. Remove any unwanted object, defect, or people from your pictures or erase and replace(powered by stable diffusion) anything on your pictures. Lama Cleaner is a free, open-source and fully self-hostable inpainting tool powered by state-of-the-art AI models. You can use it to remove any unwanted object, defect, or people from your pictures or erase and replace anything on your pictures. Many AICG creators are using Lama Cleaner to clean-up their work. Completely free and open-source, fully self-hosted, supports CPU & GPU. Windows 1-Click Installer, classical image inpainting algorithm powered by cv2. Multiple SOTA AI models, and various inpainting strategies. Run as a desktop application. Interactive Segmentation on any object. -
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A powerful editor for video games based on or similar to id Software's series of Quake games. Currently QuArK supports 41 distinct games, 5 generic game engines, and a countless number of expansions packs, addons, and mods. It integrates a map editor, model editor, archive editors, texture management, and much more.
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GIMP ML
AI for GNU Image Manipulation Program
This repository introduces GIMP3-ML, a set of Python plugins for the widely popular GNU Image Manipulation Program (GIMP). It enables the use of recent advances in computer vision to the conventional image editing pipeline. Applications from deep learning such as monocular depth estimation, semantic segmentation, mask generative adversarial networks, image super-resolution, de-noising and coloring have been incorporated with GIMP through Python-based plugins. Additionally, operations on images such as edge detection and color clustering have also been added. GIMP-ML relies on standard Python packages such as numpy, scikit-image, pillow, pytorch, open-cv, scipy. In addition, GIMP-ML also aims to bring the benefits of using deep learning networks used for computer vision tasks to routine image processing workflows. -
Sales CRM and Pipeline Management Software | PipedrivePipedrive’s simple interface empowers salespeople to streamline workflows and unite sales tasks in one workspace. Unlock instant sales insights with Pipedrive’s visual sales pipeline and fine-tune your strategy with robust reporting features and a personalized AI Sales Assistant.
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Dream Textures
Stable Diffusion built-in to Blender
Create textures, concept art, background assets, and more with a simple text prompt. Use the 'Seamless' option to create textures that tile perfectly with no visible seam. Texture entire scenes with 'Project Dream Texture' and depth to image. Re-style animations with the Cycles render pass. Run the models on your machine to iterate without slowdowns from a service. Create textures, concept art, and more with text prompts. Learn how to use the various configuration options to get exactly what you're looking for. Texture entire models and scenes with depth to image. Inpaint to fix up images and convert existing textures into seamless ones automatically. Outpaint to increase the size of an image by extending it in any direction. Perform style transfer and create novel animations with Stable Diffusion as a post processing step. Dream Textures has been tested with CUDA and Apple Silicon GPUs. Over 4GB of VRAM is recommended. -
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FontForge Windows builds
Unofficial Windows builds of FontForge
The aim of this project is to compile up-to-date Windows builds of FontForge. For 'stable' builds, see https://github.com/fontforge/fontforge/releases The build system used was based off that offered by Matthew Petroff (http://www.mpetroff.net/software/fontforge-windows/), but has since been practically rewritten. New in 11/07/2020: * Synced with the 20201107 release. New in 06/04/2020: * Updated to latest master, picks up a clipboard copying fix New in 14/03/2020: * Synced with the 20200314 release. New in 01/03/2020: * Updated to latest master, now built with CMake. (prerelease) New in 02/06/2019: * The 32-bit build now uses Python 3 (3.7) instead of Python 2. No further Python 2 builds will be provided. * The GDK3 backend is now used. VcXsrv is no longer bundled. New in 31/07/2017: KNOWN ISSUES: * CTRL-C from console no longer interrupts/stops FontForge -
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BG Remover - offline
AI powered Offline Background Remover.
Our Offline AI-powered Background Remover Desktop App effortlessly removes backgrounds from any image or photo. It utilizes the latest machine learning algorithms to provide accurate results within seconds. Download now and experience the ease and efficiency of our AI-powered solution. -
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JAX
Composable transformations of Python+NumPy programs
With its updated version of Autograd, JAX can automatically differentiate native Python and NumPy functions. It can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation) via grad as well as forward-mode differentiation, and the two can be composed arbitrarily to any order. What’s new is that JAX uses XLA to compile and run your NumPy programs on GPUs and TPUs. Compilation happens under the hood by default, with library calls getting just-in-time compiled and executed. But JAX also lets you just-in-time compile your own Python functions into XLA-optimized kernels using a one-function API, jit. Compilation and automatic differentiation can be composed arbitrarily, so you can express sophisticated algorithms and get maximal performance without leaving Python. -
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This Inkscape extension provides table support for Inkscape. This is one of the features that are present in Corel Draw but are not present in Inkscape. So, just install this extension and you will have table support in Inkscape
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BackgroundRemover
Background Remover lets you Remove Background from images and video
BackgroundRemover is a command line tool to remove background from image and video, made by nadermx to power BackgroundRemoverAI. If you wonder why it was made read this short blog post. -
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Image-Editor
AI based photo editing website for changing image background
Welcome to Image-Editor, the AI-based photo editing website that lets you change backgrounds, colors, crop, sharpen images, and much more with just a single click. With exceptional image quality and fast processing times, Image-Editor is the ultimate tool for all your photo editing needs. To get started, simply run pip install -r requirements.txt to download all the necessary libraries. Then to, create a new Django project using django-admin startproject Website1, replacing 'Website1' with the name of your choice. Image-Editor uses Python's cv2 library, which provides an easy and efficient way to work with images and videos, including a wide range of image processing and computer vision algorithms. With cv2, you can easily read, write, filter, and display images, and much more. Image-Editor uses Mediapipe's selfie_segmentation model for background removal in real-time video streams. This advanced model uses deep neural networks to detect and remove the background. -
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Stable Diffusion in Docker
Run the Stable Diffusion releases in a Docker container
Run the Stable Diffusion releases in a Docker container with txt2img, img2img, depth2img, pix2pix, upscale4x, and inpaint. Run the Stable Diffusion releases on Huggingface in a GPU-accelerated Docker container. By default, the pipeline uses the full model and weights which requires a CUDA capable GPU with 8GB+ of VRAM. It should take a few seconds to create one image. On less powerful GPUs you may need to modify some of the options; see the Examples section for more details. If you lack a suitable GPU you can set the options --device cpu and --onnx instead. Since it uses the model, you will need to create a user access token in your Huggingface account. Save the user access token in a file called token.txt and make sure it is available when building the container. Create an image from an existing image and a text prompt. Modify an existing image with its depth map and a text prompt. -
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Video Object Remover – Frame-Accurate
🎥 A free & open-source Python tool to remove unwanted objects from videos frame-by-frame using brush masking and AI inpainting (OpenCV + FFmpeg). EXE included.
Video Object Remover – Frame Accurate Edition is a free and open-source desktop application that helps you remove unwanted objects, logos, or watermarks from videos using brush-based masking and AI inpainting. The tool extracts video frames using FFmpeg, lets you mask objects frame-by-frame, and removes them using OpenCV. Built with Python and Tkinter, it features a modern dark-themed GUI, adjustable brush tool, zoom control, and real-time logging. The cleaned video is rebuilt and exported with original quality. Includes a precompiled Windows EXE for normal users (no Python required) and full source code for developers or students. Perfect for YouTubers, video editors, educators, and open-source enthusiasts. 🖥️ Website: https://projectworlds.in 📺 YouTube: https://youtube.com/@projectworlds 📬 Support: https://projectworlds.in/contact-us -
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DreamStudio by Volocian Studios
Free yourself
Volocian believes first and foremost that financial status shouldn’t be a barrier to entry in multimedia content creation. Whether you want to design a product or website, record a band, remix a song, or produce a feature length movie with professional post production graphics and effects, Volocian™ wants to help, even if you’re using borrowed hardware with no previous experience. We provide affordable products and services for any budget, including cost-free solutions for education and demo purposes, while everything we do is designed with ease of use and flexibility in mind, to suit everyone from novice hobbyists to expert professionals. Wherever possible, Volocian™ relies on free, open source, and cross-platform software to prevent vendor lock-in, planned obsolescence, and software as a service licensing. While we remain pragmatic about the use of proprietary software, as we’re aware of the feature limitations of some open source solutions, free solutions are preferred. -
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DALL-E 2 - Pytorch
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch. The main novelty seems to be an extra layer of indirection with the prior network (whether it is an autoregressive transformer or a diffusion network), which predicts an image embedding based on the text embedding from CLIP. Specifically, this repository will only build out the diffusion prior network, as it is the best performing variant (but which incidentally involves a causal transformer as the denoising network) To train DALLE-2 is a 3 step process, with the training of CLIP being the most important. To train CLIP, you can either use x-clip package, or join the LAION discord, where a lot of replication efforts are already underway. Then, you will need to train the decoder, which learns to generate images based on the image embedding coming from the trained CLIP. -
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MMEditing
MMEditing is a low-level vision toolbox based on PyTorch
MMEditing is an open-source toolbox for low-level vision. It supports various tasks. MMEditing is a low-level vision toolbox based on PyTorch, supporting super-resolution, inpainting, matting, video interpolation, etc. We decompose the editing framework into different components and one can easily construct a customized editor framework by combining different modules. The toolbox directly supports popular and contemporary inpainting, matting, super-resolution and generation tasks. The toolbox provides state-of-the-art methods in inpainting/matting/super-resolution/generation. Note that MMSR has been merged into this repo, as a part of MMEditing. With elaborate designs of the new framework and careful implementations, hope MMEditing could provide a better experience. When installing PyTorch in Step 2, you need to specify the version of CUDA. If you are not clear on which to choose, follow our recommendations. -
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Transparent Background
This is a background removing tool powered by InSPyReNet
This is a background-removing tool powered by InSPyReNet (ACCV 2022). You can easily remove the background from the image or video or bunch of other stuffs when you can make the background transparent! We basically follow the virtual camera settings from pyvirtualcam. If you do not choose to install virtual camera, it will visualize real-time output with cv2.imshow. Use another checkpoint file. Default is trained with composite dataset and will be automatically downloaded if not available. -
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audio-diffusion-pytorch
Audio generation using diffusion models, in PyTorch
A fully featured audio diffusion library, for PyTorch. Includes models for unconditional audio generation, text-conditional audio generation, diffusion autoencoding, upsampling, and vocoding. The provided models are waveform-based, however, the U-Net (built using a-unet), DiffusionModel, diffusion method, and diffusion samplers are both generic to any dimension and highly customizable to work on other formats. Note: no pre-trained models are provided here, this library is meant for research purposes. -
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pybaselines
Library of algorithms for baseline correction of experimental data
pybaselines is a Python library that provides many different algorithms for performing baseline correction on data from experimental techniques such as Raman, FTIR, NMR, XRD, XRF, PIXE, etc. The aim of the project is to provide a semi-unified API to allow quick testing and comparing multiple baseline correction algorithms to find the best one for a set of data. pybaselines has 50+ baseline correction algorithms. These include popular algorithms, such as AsLS, airPLS, ModPoly, and SNIP, as well as many lesser-known algorithms. Most algorithms are adapted directly from literature, although there are a few that are unique to pybaselines, such as penalized spline versions of Whittaker-smoothing-based algorithms. The full list of implemented algorithms can be found in the documentation.
