Open Source Python Multimedia Software - Page 10
Sort By:
Python Multimedia Software
View 5147 business solutionsBrowse free open source Python Multimedia Software and projects below. Use the toggles on the left to filter open source Python Multimedia Software by OS, license, language, programming language, and project status.
-
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
1
3DDFA
Fast, accurate and stable 3D dense face alignment
This work extends 3DDFA, named 3DDFA_V2, titled Towards Fast, Accurate and Stable 3D Dense Face Alignment, accepted by ECCV 2020. The supplementary material is here. The gif above shows a webcam demo of the tracking result, in the scenario of my lab. This repo is the official implementation of 3DDFA_V2. Compared to 3DDFA, 3DDFA_V2 achieves better performance and stability. Besides, 3DDFA_V2 incorporates the fast face detector FaceBoxes instead of Dlib. A simple 3D render written by c++ and cython is also included. This repo supports the onnxruntime, and the latency of regressing 3DMM parameters using the default backbone is about 1.35ms/image on CPU with a single image as input. See requirements.txt, tested on macOS and Linux platforms. The Windows users may refer to FQA for building issues. Note that this repo uses Python3. The major dependencies are PyTorch, numpy, opencv-python and onnxruntime, etc. -
2
AnimeGAN
A simple PyTorch Implementation of Generative Adversarial Networks
A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing. The images are generated from a DCGAN model trained on 143,000 anime character faces for 100 epochs. Manipulating latent codes enables the transition from images in the first row to the last row. The images are not clean, some outliers can be observed, which degrades the quality of the generated images. Anime-style images of 126 tags are collected from danbooru.donmai.us using the crawler tool gallery-dl. The images are then processed by an anime face detector python-anime face. The resulting dataset contains ~143,000 anime faces. Note that some of the tags may no longer be meaningful after cropping, i.e. the cropped face images under the 'uniform' tag may not contain visible parts of uniforms. -
3
Audiomentations
A Python library for audio data augmentation
A Python library for audio data augmentation. Inspired by albumentations. Useful for deep learning. Runs on CPU. Supports mono audio and multichannel audio. Can be integrated in training pipelines in e.g. Tensorflow/Keras or Pytorch. Has helped people get world-class results in Kaggle competitions. Is used by companies making next-generation audio products. Mix in another sound, e.g. a background noise. Useful if your original sound is clean and you want to simulate an environment where background noise is present. A folder of (background noise) sounds to be mixed in must be specified. These sounds should ideally be at least as long as the input sounds to be transformed. Otherwise, the background sound will be repeated, which may sound unnatural. Note that the gain of the added noise is relative to the amount of signal in the input. This implies that if the input is completely silent, no noise will be added. -
4
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. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
5
ChatterBot
Machine learning, conversational dialog engine for creating chat bots
ChatterBot is a Python library that makes it easy to generate automated responses to a user’s input. ChatterBot uses a selection of machine learning algorithms to produce different types of responses. This makes it easy for developers to create chat bots and automate conversations with users. For more details about the ideas and concepts behind ChatterBot see the process flow diagram. The language independent design of ChatterBot allows it to be trained to speak any language. Additionally, the machine-learning nature of ChatterBot allows an agent instance to improve it’s own knowledge of possible responses as it interacts with humans and other sources of informative data. An untrained instance of ChatterBot starts off with no knowledge of how to communicate. Each time a user enters a statement, the library saves the text that they entered and the text that the statement was in response to. As ChatterBot receives more input the number of responses that it can reply increase. -
6
Crunch
Insane(ly slow but wicked good) PNG image optimization
Crunch is an image compression tool for lossy PNG image file optimization. Using a combination of selective bit depth, color palette reduction and color type, as well as zopfli DEFLATE compression algorithm encoding that employs the pngquant and zopflipng PNG optimization tools, Crunch is effectively able to optimize and compress images with minimal decrease in image quality. While it may produce file size gains larger than those produced by lossless approaches, the impact on image quality is often imperceptible, and optimized file sizes are still significantly lower than the original. -
7
GIF for CLI
Takes in a GIF, short video, or a query to the Tenor GIF API
gif-for-cli is a small, playful utility that brings animated GIFs to the command line by rendering frames directly in a terminal. It takes an input GIF (or a URL) and converts each frame into a terminal-friendly representation, timing updates to approximate the original animation. Depending on terminal capabilities, it can use ANSI color blocks or image protocols to achieve surprisingly faithful playback. The tool includes conveniences such as looping control, scaling to fit your terminal, and caching to avoid repeated downloads. It’s useful for quick visual feedback, lightweight demos, or just adding some personality to scripts and readmes. Despite its whimsical nature, the project is a tight example of frame decoding, timing, and terminal rendering glued together in a single command. -
8
Image Super-Resolution (ISR)
Super-scale your images and run experiments with Residual Dense
The goal of this project is to upscale and improve the quality of low-resolution images. This project contains Keras implementations of different Residual Dense Networks for Single Image Super-Resolution (ISR) as well as scripts to train these networks using content and adversarial loss components. Docker scripts and Google Colab notebooks are available to carry training and prediction. Also, we provide scripts to facilitate training on the cloud with AWS and Nvidia-docker with only a few commands. When training your own model, start with only PSNR loss (50+ epochs, depending on the dataset) and only then introduce GANS and feature loss. This can be controlled by the loss weights argument. The weights used to produce these images are available directly when creating the model object. ISR is compatible with Python 3.6 and is distributed under the Apache 2.0 license. -
9
JamTools
JamTools is a cross-platform gadget set software
JamTools is a multifunctional desktop utility suite designed to provide a collection of tools for productivity, media processing, and system enhancements within a single application. It integrates various features such as file management, multimedia handling, and system utilities into a unified interface. The project emphasizes ease of use while offering advanced functionality for handling common tasks efficiently. It includes support for media-related operations, often leveraging FFmpeg for processing video and audio content. JamTools is structured to allow modular expansion, enabling new tools and features to be added over time. Its interface is designed to centralize multiple utilities, reducing the need for separate applications. Overall, it serves as an all-in-one toolkit for managing everyday tasks and media workflows. -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
-
10
JoyAI-Video-Edit
Real-Time Open-Ended Video Editing with Autoregressive Diffusion
JoyAI-Video-Edit is a real-time, instruction-guided system for editing open-ended video streams as frames arrive. It works with live camera feeds or uploaded videos without waiting for the entire sequence or knowing the final video length. Natural-language instructions can drive subject edits, local changes, background replacement, style transfer, motion changes, and reference-guided transformations. Its architecture combines a multimodal condition encoder, causal video VAE, and a 16B-parameter multimodal diffusion transformer. Autoregressive diffusion and bounded KV-state inference are used to keep computation stable across long streams. The released deployment reaches high-throughput 720p editing and also supports real-time operation on selected consumer GPUs. Updated checkpoints improve identity preservation, reference conditioning, and temporal consistency for reference-image-guided editing. -
11
Kornia
Open Source Differentiable Computer Vision Library
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within neural networks to train models to perform image transformations, epipolar geometry, depth estimation, and low-level image processing such as filtering and edge detection that operate directly on tensors. With Kornia we fill the gap between classical and deep computer vision that implements standard and advanced vision algorithms for AI. Our libraries and initiatives are always according to the community needs. -
12
MMDeploy
OpenMMLab Model Deployment Framework
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN frameworks. Please read getting_started for the basic usage of MMDeploy. -
13
MangaPark-DL
A Python script to download mangas from MangaPark
MangaPark-DL is a Python command-line script designed to download manga chapters from MangaPark and convert them into PDF files for convenient offline reading. The tool allows users to specify individual chapters or ranges, automating the retrieval of images and their conversion into a single document format. It is particularly useful for mobile users who prefer reading manga in PDF form rather than browsing online chapter pages. The script includes options for resizing images to reduce file size and avoid processing issues during PDF generation. It is lightweight and relies on standard Python dependencies, making it easy to run in most environments. The project emphasizes simplicity and efficiency, focusing on a single workflow that converts web-hosted manga into portable reading files. -
14
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. -
15
Pydub
Manipulate audio with a simple and easy high level interface
Manipulate audio with a simple and easy high level interface. You can pass an optional bitrate argument to export using any syntax ffmpeg supports. Any further arguments supported by ffmpeg can be passed as a list in a 'parameters' argument, with switch first, argument second. Note that no validation takes place on these parameters, and you may be limited by what your particular build of ffmpeg/avlib supports. You can open and save WAV files with pure python. For opening and saving non-wav files, like mp3, you'll need ffmpeg or libav. Any operations that combine multiple AudioSegment objects in any way will first ensure that they have the same number of channels, frame rate, sample rate, bit depth, etc. -
16
Spaceship Generator
A Blender script to procedurally generate 3D spaceships
A Blender script to procedurally generate 3D spaceships from a random seed. Install Blender 2.80 or greater. Download newest add_mesh_SpaceshipGenerator.zip from the Releases section. Under Edit, Preferences, Add-ons, Install, open the downloaded ZIP file. Under Edit, Preferences, Add-ons enable the "Add Mesh Spaceship Generator" script (search for "spaceship"). Add a spaceship in the 3D View under Add, Mesh, Spaceship. Expand the Spaceship tab that appears in the bottom left of the viewport to adjust procedural generation settings. Build the hull. Extrude the front/rear faces several times, adding random translation/scaling/rotation along the way. Add asymmetry to the hull: Pick random faces and extrude them out in a similar manner, reducing in scale each time. Categorize each face by its orientation and generate details on it such as engines, antenna, weapon turrets, lights etc. -
17
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. -
18
Super-résolution via CNN
Super resolution using a CNN, based on the work of the DGtal team
Super-resolution using a CNN, based on the work of the DGtal team. First of all, an Nvidia graphics card (neither AMD nor Intel integrated) is highly recommended to parallelize the CNN. You will then need to install CUDA. No CUDA = dozens of times slower. This program will generate "model_epoch_ .pth" files corresponding to the model at epoch n, in a folder saved_model_u t_bs bs_tbs tbs_lr lr, where corresponds to the scale factor, bsthe size of the training batch, tbsthe size of the test batch and lrto the learning rate. Low res images should be located in a "dataset/input" folder, and high res targets in a "dataset/target" folder, where each different quality image has the same name in both folders. -
19
Telegram WebRTC (VoIP)
Voice chats, private incoming and outgoing calls in Telegram
Telegram WebRTC (VoIP) is a Python and C++ library that enables real-time voice and video communication features for Telegram bots and clients. It provides an interface for joining, managing, and streaming audio or video in Telegram group calls and voice chats. The library is built on top of low-level communication protocols, ensuring efficient handling of real-time media streams. It supports integration with FFmpeg and other tools for processing audio and video before transmission. tgcalls allows developers to create bots that can play music, stream content, or interact with live voice channels programmatically. It also supports cross-platform usage and integration into larger automation systems. Overall, it serves as a powerful toolkit for building real-time communication features within Telegram ecosystems. -
20
Verticals v3
Automated YouTube Shorts pipeline
Verticals v3 is an automated content generation workflow designed to create and process YouTube Shorts videos programmatically. It combines multiple tools and scripts to handle tasks such as downloading source material, editing clips, adding subtitles, and formatting output for vertical video platforms. The pipeline emphasizes automation, allowing users to produce short-form content at scale with minimal manual intervention. It integrates FFmpeg and other media processing tools to handle video transformations, resizing, and encoding. The system also supports adding overlays, captions, and audio enhancements to improve engagement. Designed for creators and developers, it enables repeatable workflows for generating social media content efficiently. Its modular structure allows customization of each stage in the pipeline, making it adaptable to different content strategies. -
21
Videomass
Videomass is a free, open source and cross-platform GUI for FFmpeg
Videomass is a free, open-source graphical interface for FFmpeg designed to make advanced video and audio processing accessible to both beginners and experienced users. Built in Python using wxPython, it provides a cross-platform environment for managing encoding, conversion, and editing tasks through a visual interface. The software supports multitasking operations, allowing users to process multiple media files simultaneously. It offers extensive configuration options while also providing presets to simplify common workflows. Videomass integrates closely with FFmpeg, exposing powerful capabilities such as transcoding, filtering, and format conversion without requiring command-line interaction. It also supports scripting and customization for more advanced use cases. Overall, it combines usability and flexibility into a comprehensive multimedia processing tool. -
22
Web RPA
Web Robotics Process Automation Tool
Web RPA is a browser automation framework designed to perform robotic process automation tasks directly within web environments. It enables users to automate repetitive actions such as form filling, data extraction, and workflow execution through programmable scripts. The system focuses on simplicity and flexibility, allowing automation without requiring complex infrastructure. It supports interaction with web elements, navigation flows, and dynamic content handling, making it suitable for scraping and automation scenarios. WebRPA can be integrated into larger systems or used as a standalone tool for automating browser-based operations. Its lightweight design ensures efficient execution while maintaining adaptability for different use cases. Overall, it provides a practical solution for automating web workflows and repetitive tasks. -
23
You-Get
Dumb downloader that scrapes the web
You-Get is a small command-line utility for downloading media (video, audio and images) from the Web when there are no other means to do so. It can download video and audio files from such popular web sites as YouTube, Twitter, Niconico, Vimeo, Flickr, Instagram and a whole lot more. You-Get is a great option for when you want to enjoy your favorite videos, audio or images from the internet without having to open any web browsers or get interrupted by ads. It’s also a good choice for when you want to get rid of any closed-source technology or proprietary JavaScript code from running on your computer. -
24
auto-subtitle
Automatically generate and overlay subtitles for any video
auto-subtitle is a Python-based command-line tool that automatically generates and overlays subtitles on video files using AI-driven speech recognition. It combines FFmpeg with OpenAI’s Whisper model to transcribe spoken audio into text and synchronize it with video playback. The tool processes video input, extracts audio, and produces subtitle files that can be either exported separately or burned directly into the final video output. It supports multiple transcription models with varying accuracy and performance, allowing users to balance speed and quality depending on their needs. The system can also translate subtitles into English, enabling multilingual accessibility for video content. Once the required models are downloaded, it can operate offline, making it practical for local workflows. Designed for simplicity, it provides a streamlined way to automate subtitle creation without manual transcription effort. -
25
ffmpy
Pythonic interface for FFmpeg/FFprobe command line
ffmpy is a Python wrapper that provides a simple and Pythonic interface for constructing and executing FFmpeg and FFprobe command-line operations. It abstracts command generation into structured Python objects, making it easier to define inputs, outputs, and parameters programmatically. The library uses Python’s subprocess module to run compiled commands, ensuring compatibility with standard FFmpeg installations. It is designed for developers who want to automate media processing tasks without manually writing complex command strings. ffmpy supports flexible argument configuration, enabling a wide range of transcoding and analysis workflows. Its lightweight design makes it suitable for scripting, automation, and integration into larger Python applications.
