Open Source Python Animation Software for Linux
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Python Animation Software for Linux
View 13 business solutionsBrowse free open source Python Animation Software for Linux and projects below. Use the toggles on the left to filter open source Python Animation Software for Linux by OS, license, language, programming language, and project status.
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Manim
A community-maintained Python framework for creating animations
A community-maintained Python library for creating mathematical animations. Manim is a free and open-source project originally written by Grant Sanderson. It is now maintained by the Manim Community and permissively released under the MIT license. Manim was originally created by Grant Sanderson as a personal project and for use in his YouTube channel, 3Blue1Brown. As his channel gained popularity, many grew to like the style of his animations and wanted to use manim for their own projects. However, as manim was only intended for personal use, it was very difficult for other users to install and use it. Manim, or ManimCE refers to the community-maintained version of the library. This is the version documented on this website; the package name on PyPI is manim. ManimGL is the latest released version of the library developed by Grant “3b1b” Sanderson. It has more experimental features and breaking changes between versions are not documented. -
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srt-whiteboard-animation
Make SRT into a streaming handwriting whiteboard hand-drawn animation
srt-whiteboard-animation is an AI skill for turning SRT subtitle files into hand-drawn whiteboard videos that follow the narrative order of the captions. It parses subtitles and recommends scene divisions, typically targeting segments of about 25 to 35 seconds. Each scene is planned around one core idea before artwork and annotations are prepared. Semantic drawing order connects visual elements to specific subtitle events rather than relying only on coordinates. A streaming renderer first reveals ink strokes and then progressively adds color. Users can adjust regions, timing, sequence, and subtitle associations in a browser preview before rendering scenes and merging them into a final MP4. -
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PersonaLive
Expressive Portrait Image Animation for Live Streaming
PersonaLive is an open-source diffusion-based portrait animation framework focused on generating expressive, long-duration animated sequences in real time, primarily for live streaming or interactive applications. It leverages deep generative models that condition on a static reference image and a driving input (such as motion or expression cues) to produce a seamless animated portrait sequence that can run indefinitely without segmentation artifacts. The framework prioritizes low-latency and streamable output, making it suitable for real-time creative workflows, broadcast overlays, or interactive avatars on consumer-grade GPUs. PersonaLive’s architecture balances visual quality and efficiency by combining motion encoding, temporal modules, and hybrid implicit control signals to preserve identity and stable expression through long sequences. -
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UniMate
UniMate: One Unified Model to Animate Diverse Skeletons
UniMate is a generative motion model that animates rigged 3D assets with different skeletal structures from natural-language prompts. It is designed to handle bipeds, quadrupeds, birds, marine creatures, insects, serpentine rigs, and articulated rigid objects with one unified model. Its topology-aware diffusion transformer conditions generation on skeleton structure rather than requiring a fixed character template. The accompanying UniML3D dataset contains 13,006 text-paired motion sequences with unified skeletal canonicalization. Inference can generate motion for unseen skeleton topologies without per-skeleton retraining or test-time optimization. The same model supports text-guided motion editing, in-betweening, and longer motion expansion. Training, inference, data processing, and preview checkpoints are provided for research use. -
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Animated Drawings
Code to accompany "A Method for Animating Children's Drawings"
AnimatedDrawings is a framework that converts user sketches or line drawings into fully animated 2D motion sequences using learned motion priors. The idea is that you draw a simple static figure (stick figure, silhouette, or contour lines), and the system produces plausible skeletal motion (walking, jumping, dancing) that adheres to the drawn shape constraints. The architecture separates shape embedding (to understand user-drawn geometry) from motion embedding / generation (to produce temporally coherent movement). Users can provide rough keyframes or control constraints (pose anchors), and the system fills intermediate frames with fluid animation. The repository includes demonstration apps and notebooks where you can upload or draw shapes and watch animations play. Because the approach is data-driven, it generalizes to new drawings even with varying proportions or stylizations. -
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Blend_My_NFTs
Easily generate thousands of 3D models, images, and animation NFTs
Blend_My_NFTs is an open-source, free-to-use Blender add-on that enables you to easily generate thousands of 3D Models, Animations, and Images. This add-on's primary purpose is to aid in the creation of large generative 3D NFT collections. It is the first and easiest 3D NFT generator. Blend_My_NFTs was initially developed to create Cozy Place, an NFT collection by This Cozy Studio Inc. Blend_My_NFTs works with Blender 3.2.2 on Windows 10 or macOS Big Sur 11.6. Linux is supported, however we haven't had the chance to test and guarantee this functionality. Windows 11 has not been tested as of yet. Any rendering engine works; Cycles, Eevee, and Octane have all been used by the community. This add-on only works in Blender, a Cinima 4D port is being investigated. Every object, model, texture, camera, light etc. must be in the same .blend file! If you have mulitiple .blend files, Blend_My_NFTs is unable to open and process them. It's recommended to keep your file's total size 5gb. -
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Oil Motion
Create smooth, responsive interactive web animations
Oil Motion is an agent-agnostic skill for creating smooth interactive animations for websites and digital interfaces. Users describe the desired movement, available assets, and the interaction that should control it while the agent manages the production workflow. The system defines key states, generates continuous motion between them, reviews frames, removes artifacts, and prepares optimized assets. Animation progress can then be mapped to scrolling, mouse movement, dragging, touch input, device orientation, clicks, or component states. Reverse movement naturally follows the same frame sequence when the user reverses an interaction. The workflow also considers motion continuity, visual clarity, loading size, and mobile performance. It is suitable for product reveals, character interactions, demonstrations, data transitions, and narrative page sequences. -
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SCAIL
Towards Studio-Grade Character Animation via In-Context Learning of 3D
SCAIL is a project developed by the ZAI Organization, focusing on AI-driven research initiatives. While specific documentation about SCAIL’s exact goals and implementation is limited from the repository context alone, the project appears to be part of a collection of machine learning and AI research tools that facilitate scalable model development, evaluation, or application workflows. Given its listing alongside other ZAI projects like speech recognition and text-to-speech systems, SCAIL likely emphasizes scalable, composable AI learning frameworks that support researchers and practitioners in experimenting with learning algorithms, datasets, and model components. The repository structure suggests a focus on flexibility and extensibility, with potential integration into other ZAI tooling for training or analysis. -
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ipyvizzu
Build animated charts in Jupyter Notebook and similar environments
ipyvizzu - Build animated charts in Jupyter Notebook and similar environments with a simple Python syntax ipyvizzu is an animated charting tool for Jupyter, Google Colab, Databricks, Kaggle and Deepnote notebooks among other platforms. ipyvizzu enables data scientists and analysts to utilize animation for storytelling with data using Python. It's built on the open-source JavaScript/C++ charting library Vizzu. There is a new extension of ipyvizzu, ipyvizzu-story with which the animated charts can be presented right from the notebooks. Since ipyvizzu-story's syntax is a bit different to ipyvizzu's, we suggest you to start from the ipyvizzu-story repo if you're interested in using animated charts to present your findings live or to share your presentation as an HTML file. -
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AnimateDiff
Plug-n-play module turning text-to-image models into animation
AnimateDiff is an open-source project designed to enhance text-to-image diffusion models by adding animation capabilities. It allows users to turn static images generated by popular text-to-image models into animated sequences without requiring additional model training. This plug-and-play tool is compatible with a wide range of community models and facilitates the generation of animation directly from pre-existing text-to-image models. It supports various configurations to create animations with different visual styles, providing flexibility and ease of use for developers and artists interested in exploring dynamic, AI-generated animations. -
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SmartBody
Character animation system for games and simulations.
SmartBody is available for download for Windows, Linux and OSX users. SmartBody can also be used on Android and iOS platforms. SmartBody is a character animation platform that provides the following capabilities in real time: * Locomotion (walk, jog, run, turn, strafe, jump, etc.) * Steering - avoiding obstacles and moving objects * Object manipulation - reach, grasp, touch , pick up objects * Lip Syncing - characters can speak with simultaneous lip-sync using text-to-speech or prerecorded audio * Gazing - robust gazing behavior that incorporates various parts of the body * Nonverbal behavior - gesturing, head nodding and shaking, eye saccades - Online and offline retargeting of motion - Automatic skinning and rigging SmartBody is written in C++ and can be incorporated into most game engines. SmartBody is developed at the USC Institute for Creative Technologies from the Character Animation and Simulation group: http://cas.ict.usc.edu -
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A Stick figure animation program written with Python(www.python.org) and PyGame(www.pygame.org). It is similar to Pivot, except with a much wider variety of animation features, such as keyframes.
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Python Script to process a wave file and transform to movement (key frames) on Blender 2.5. Input: sound file (.wav) Output: Key frames direct into the selected object Work to meshes and bones (location, scale or rotation in any axis)
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Gato (Graph Animation Toolbox): Animate graph algorithms for example for computing shortest paths, minimal spanning trees, maximum flows or maximal cardinality or weight matchings. Create your own animations using the Animated Data Structures (ADS).
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The Houdini Character Development Kit is a set of tools (scripts / HDA's) that help and make easier the task of rigging characters.
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Pivot: Revolution is a remake of the highly popular Pivot Stickfigure Animator, which was designed to allow easy animation using stick figures. Pivot: Revolution, however, will add many features on top of it, allowing for further ease of use.
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PythonStarSplitter
A Python Script I made to split a starfield image into several layers.
A Python Script I made to split a starfield image into several layers. To be able to use the script, PixInsight with an installed Gaia data catalogue is required, as it needs the exported astrometry data text file. -
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SteadyDancer
Harmonized and Coherent Human Image Animation
SteadyDancer is a research-oriented motion stabilization and dancer tracking system designed to analyze and correct motion in videos, making captured performances appear smoother and more stable while preserving expressiveness. It employs computer vision and motion modeling to estimate and reduce unwanted jitters, shakes, or camera wobbles — particularly in dance or movement sequences where traditional smoothing would distort intentional motion. By differentiating between intentional rhythmic motion and unintentional instability, SteadyDancer applies adaptive filtering that enhances video quality without flattening the core movement dynamics. The system can be used both in preprocessing pipelines for content creators and in live feedback loops for performers, giving dancers and videographers a tool to refine their visual outputs. It supports integration with standard video formats and includes customizable parameters so users can tune stabilization aggressiveness. -
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Web browser plug-in for hosting real 3D on the websites.
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A Maya plugin-in which allows you to bake particle instances into geometry, animation, and blendshapes that can be modified and updated without messing around with dynamics and expressions.
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convertToMP4
Easily convert to MP4 with H264 and without all the codec hassle
Convert existing media data (movies or images) to an mp4 movie, with the high performane h264 codec. Usually it takes quite a lot to get the video running as you wish. As convertion engine, Mencoder will be used. This script is intended to ease the creation of videos. It is suitable for the beginner or the lazy advanced people. It will not suite the professional wanting to have full control over all codec parameters. Consider donating to this project: https://sourceforge.net/projects/converttomp4/files/ -
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iamar browser is a GPU web browser that displays 3d specific contents. Instead of html, it run on a scripting language called semblis. Together with mesh made from blender, it makes 3d game production extremely easy.
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Motion Graphs in Blender
A Blender 2.6+ addon that aims to implement Motion Graphs
This add-on demonstrates how motion graphs can be created in Blender in order to create a variety of arbitrary length character animations from a small set of character motions. This add-on implements motion graphs as described in Motion Graphs paper by Kovar, Gleicher, and Pighin from SIGGRAPH 2002. The add-on can import set of motion captured BVH files and construct a motion graph based on some given parameters. This motion graph can be stored in memory and used until Blender is running, or can be baked to a file in a compact format so that it can be retrieved later without the need of re-computation. This motion graph can be used to generate arbitrary length motions that is composed of frames from the original motions and some generated transition frames between them. The add-on is currently being extended for path synthesis where the the animation required to make the character traverse an arbitrary path will be generated from the motion graph.
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