Open Source Python Multimedia Software - Page 64
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Python Multimedia Software
View 5155 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.
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VGGSfM
VGGSfM: Visual Geometry Grounded Deep Structure From Motion
VGGSfM is an advanced structure-from-motion (SfM) framework jointly developed by Meta AI Research (GenAI) and the University of Oxford’s Visual Geometry Group (VGG). It reconstructs 3D geometry, dense depth, and camera poses directly from unordered or sequential images and videos. The system combines learned feature matching and geometric optimization to generate high-quality camera calibrations, sparse/dense point clouds, and depth maps in standard COLMAP format. Version 2.0 adds support for dynamic scene handling, dense point cloud export, video-based reconstruction (1000+ frames), and integration with Gaussian Splatting pipelines. It leverages tools like PyCOLMAP, poselib, LightGlue, and PyTorch3D for feature matching, pose estimation, and visualization. With minimal configuration, users can process single scenes or full video sequences, apply motion masks to exclude moving objects, and train neural radiance or splatting models directly from reconstructed outputs. -
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VIPS is an image processing suite designed for extremely large images and colorimetry. It consists of a powerful re-usable library and a graphical user interface. http://www.vips.ecs.soton.ac.uk
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This project is an initial reference implementation of the VSI-E protocol. The implementation has been done using the C/C++ language and is in the form of a re-useable library developed on the Linux platform.
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VMZ (Video Model Zoo)
VMZ: Model Zoo for Video Modeling
The codebase was designed to help researchers and practitioners quickly reproduce FAIR’s results and leverage robust pre-trained backbones for downstream tasks. It also integrates Gradient Blending, an audio-visual modeling method that fuses modalities effectively (available in the Caffe2 implementation). Although VMZ is now archived and no longer actively maintained, it remains a valuable reference for understanding early large-scale video model training, transfer learning, and multimodal integration strategies that influenced modern architectures like SlowFast and X3D. -
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VSGAN
VapourSynth Single Image Super-Resolution Generative Adversarial
Single Image Super-Resolution Generative Adversarial Network (GAN) which uses the VapourSynth processing framework to handle input and output image data. Transform, Filter, or Enhance your input video, or the VSGAN result with VapourSynth, a Script-based NLE. You can chain models or re-run the model twice-over (or more). Have low VRAM? Don’t worry! The Network will be applied in quadrants of the image to reduce up-front VRAM usage. You can use any RGB video input, including float32 (e.g., RGBS) inputs. Using VapourSynth you can pass a Video directly to VSGAN, without any frame extraction needed. Any edit you make in the VapourSynth script with or without VSGAN can be re-used for any other video. VSGAN is released under the MIT License, ensuring it will stay free, with the ability to be used commercially. -
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A Python library to create sophisticated multilingual IVR applications. NOTICE. The repository is frozen, please find the latest version of the software at https://github.com/sippy/vapp
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An image-masking application which revolves around the new user-friendly and interactive use of the standard 'magic wand' tool. Features an extensive preview system, interactive parameter adjustment and a node-based structure.
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ViAmI-Server
Pattern recognition for ADL events
This software uses computer vision algorithms for mining sequence data from telemonitoring data with CBRs. We propose an approach which treats the detection of changes in behavior detected with a sensor/video fusion, which occur at radically different time-scales, through a CBR in two levels: low and high level. The system is always updating the database with the daily data. -
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Video 2 Audio The Converter [I.S.A]
Video 2 Audio The Converter [Improved.Simplified.Alternative]
'Vido 2 Audio : The converter' is an desktop application developed using python 3.6.8 and other add-on libaries. Converts video file into audio file. Vido 2 Audio : The converter has two modes: 1) Single file - Convert one video file into audio file. 2) Multiple files - Convert more than one video files into audio files from a folder\directory. Compatible only for windows OS. -
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Video Clips Merger 2-6B8 (P.F+ Rev2B)
Video Clips Merger 2-6B8 (Perfected.Further+ Revised 2B)
'Video Clips Merger' is an desktop application developed using python 3.6.8 and other add-on libaries. Can combine extracted clips into one video file. Compatible only for windows OS. -
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Video Clips Rotator [I.S.A]
Video Clips Rotator [Improved.Simplified.Alternative]
'Video Clips: Rotator' is an desktop application developed using python 3.6.8 and other add-on libaries. Rotates video files to requested angle (eg:360°). Compatible only for windows OS. -
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Video Cropper 1-6B2-2 (P.F+ Rev2B)
Video Cropper 1-6B2-2 (Perfected.Further+ Revised-2B)
'Video Cropper' an desktop application developed using python 3.6.8 and other add-on libaries. Crops video file into external video file. Compatible only for windows OS. -
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Video DeDup
Find duplicate videos by content
VIDEO DeDup Find duplicate videos by content. Parse a video directory to create one image every n seconds, then identify duplicate images and show possible video duplicates for manual analysis. . 1f_parse scan video source folder, replicate with ffmpeg an image folder, then for each image create a fingerprint. . CompareV2 perform the fingerprints comparison and works in memory with constant memory usage. It is folder agnostic and parse fingerprints ordered by source file name. Since 201906 in free Pascal for x3 speed and less memory usage in multi-threading. . 3h_analyse is folder agnostic by first loading in memory current source and image folder. Then a lot of options and cache mechanism enable to get correct performance. At the end all duplicates are copied in an analysed folder. . To finalise you'll have to look at analysed folder to make your decisions : remove duplicate, flag some images as irrelevent or flag pair of videos as NOT dupes. -
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Video Nonlocal Net
Non-local Neural Networks for Video Classification
video-nonlocal-net implements Non-local Neural Networks for video understanding, adding long-range dependency modeling to 2D/3D ConvNet backbones. Non-local blocks compute attention-like responses across all positions in space-time, allowing a feature at one frame and location to aggregate information from distant frames and regions. This formulation improves action recognition and spatiotemporal reasoning, especially for classes requiring context beyond short temporal windows. The repo provides training recipes and models for standard datasets, as well as ablations that show how many non-local blocks to insert and at which stages. Efficient implementations keep memory and compute manageable so the blocks can be added without rewriting the entire backbone. The result is a practical, drop-in mechanism for upgrading purely local video models into context-aware networks with strong benchmark performance. -
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Video Pre-Training
Learning to Act by Watching Unlabeled Online Videos
The Video PreTraining (VPT) repository provides code and model artifacts for a project where agents learn to act by watching human gameplay videos—specifically, gameplay of Minecraft—using behavioral cloning. The idea is to learn general priors of control from large-scale, unlabeled video data, and then optionally fine-tune those priors for more goal-directed behavior via environment interaction. The repository contains demonstration models of different widths, fine-tuned variants (e.g. for building houses or early-game tasks), and inference scripts that instantiate agents from pretrained weights. Key modules include the behavioral cloning logic, the agent wrapper, and data loading pipelines (with an accessible skeleton for loading Minecraft demonstration data). The repo also includes a run_agent.py script for testing an agent interactively, and an agent.py module encapsulating the control logic. -
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Video2GIF Extractor 2.6B8-105(PF+ Rev2B)
Video-2-GIF Extractor 2.6 B8-105 (Perfected.Further+ Revised 2B)
'Video-2-GIF Extractor' is an desktop application using python 3.6.8 and other add-on libaries. Can extract clips from videos and convert those extracted clips into gif file Compatible only for windows OS. -
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VideoTk
Sencillo administrador de base de datos de películas
VideoTk está apuntado a simplificar el mantenimiento de una videoteca en la vida real (formada por cualesquiera medios de almacenamiento, por ejemplo discos DVD). Es un programa muy ligero, de poco tamaño en Mb (menos de 9Mb para el archivo comprimido que contiene dos versiones), lo que permite que se ejecute rápidamente incluso en computadoras viejas o de poca potencia. Las tareas básicas que permite realizar son: Buscar película en función de su título, genero, año, actor/es, calificación, entre otros; Ver detalles completos de cada película, por ejemplo descripción(sinopsis), idiomas de audio, idiomas de subtitulo, entre otros; Añadir, editar y borrar películas junto con sus correspondientes datos. -
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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. -
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Viral-Clips-Crew
Your CrewAI Powered Video Editing Assistant
Viral-Clips-Crew is an AI-driven video processing pipeline designed to generate short-form, engaging clips from long-form video content automatically. It analyzes transcripts and video data to identify the most engaging or “viral” moments, reducing the need for manual editing. The system integrates tools like FFmpeg and AI models to handle segmentation, cropping, and formatting for vertical video platforms. It supports automation workflows that allow creators to produce multiple clips efficiently at scale. The project focuses on content repurposing, helping users adapt long videos into formats suitable for platforms like TikTok and YouTube Shorts. Its modular design allows customization of each processing stage, including selection logic and visual formatting. Overall, it serves as a tool for automating short-form content creation. -
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VRT is a Virtual Reality Toolkit. It is planned to be OS-independent, easy-to-use, full-feature VR platform. It integrates 3D engine, physical engine and AI engine.
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Visor3DTV
Stereo Photo viewer for Passive 3DTV
Visor3DTV is a stereo photo viewer that understand SBS JPG and MPO, and shows them in the interlaced screen of a 3DTV. It has a thumbnail browsing window and a presentation window. It features Pan and Zoom of the images. -
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Vivid3DIDE
Vivid3D is a C++ IDE/3D engine, with python scripting.
Vivid3D is a C++ IDE/3D engine, with python scripting. - It uses DX12 or Vulkan, and will support RTX features. It features gameplay facilitated by Python.
