Search Results for "void linux based"
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Showing 11 open source projects for "void linux based"
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1
OpenShot Video Editor
Award-Winning Open Source Video Editing Software
OpenShot Video Editor is a powerful yet very simple and easy-to-use video editor that delivers high quality video editing and animation solutions. OpenShot offers a myriad of features and capabilities, including powerful curve-based Key frame animations, 3D animated titles and effects, slow motion and time effects, audio mixing and editing, and so much more. It’s available for Linux, Mac and Windows, with a very simple and friendly interface. Start creating stunning videos quickly and easily with OpenShot! -
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Video2X
A lossless video/GIF/image upscaler achieved with waifu2x, Anime4K
A lossless video/GIF/image upscale achieved with waifu2x, Anime4K, SRMD and RealSR. Started in Hack the Valley 2, 2018. The latest Windows update is built based on version 4.8.1. GUI is not available for 5.0.0 yet, but is already under development. Go to the GUI page to see the basic usage of the GUI. Try the mirror if you can't download releases directly from GitHub. You can use Video2X on Google Colab for free if you don't have a powerful GPU of your own. You can borrow a powerful GPU... -
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SeedVR2 Upscaler ComfyUI
Official SeedVR2 Video Upscaler for ComfyUI
ComfyUI-SeedVR2 Video Upscaler is an open-source integration node for the ComfyUI workflow environment that brings the advanced SeedVR2 video upscaling and restoration model directly into visual AI pipelines. This project packages the SeedVR2 architecture as a custom node for ComfyUI, letting users upscale low-resolution video or imagery inside a node-based interface without needing to write code manually. The underlying SeedVR2 model is known for delivering high-quality video enhancement... -
4
video-use
Edit videos with Claude Code
Video Use is an open-source AI-powered video editing tool that allows users to transform raw footage into polished videos using natural language commands. Designed to work with Claude Code, it automates the entire editing process—from cutting clips to rendering the final output—without requiring manual timelines or complex software interfaces. The system intelligently analyzes audio transcripts and visual cues to make precise, context-aware editing decisions. It supports a wide range of... -
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5
AutoCrop-Vertical
Smart video converter using YOLOv8 and FFmpeg
AutoCrop-Vertical is a Python-based video processing tool that automatically converts horizontal videos into vertical formats optimized for social media platforms. It uses computer vision techniques and AI models such as YOLOv8 to analyze each frame, detect subjects, and dynamically adjust cropping decisions. Instead of applying a static center crop, the system intelligently tracks people or key objects to preserve visual focus and composition. When cropping would degrade the scene, it can... -
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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... -
7
Clipstitch
Uility to make home movies from your digital camera files
Full documentation: Download clipstitchX.Y.html To make movies from your camera (or phone) video files. FFmpeg is a professional-quality, free, open-source program for video editing, with the ability to implement a huge number of operations and handle every data format! This kind of ability comes at a cost: its commands are quite complex-looking and difficult to use and remember. Clipstitch runs as a front-end to ffmpeg so that you use only the sub-set of ffmpeg commands necessary... -
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ProPainter
Improving Propagation and Transformer for Video Inpainting
ProPainter is a video inpainting project based on the ICCV 2023 paper “Improving Propagation and Transformer for Video Inpainting.” It is designed to remove objects, complete missing regions, and fill masked areas in videos while preserving temporal consistency. The project accepts video input or split frames along with frame-wise masks that define the areas to reconstruct. It provides pretrained models, example inputs, inference scripts, and an interactive demo workflow for object removal.... -
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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.,... -
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10
VidCutter
A modern yet simple multi-platform video cutter and joiner
A modern, simple to use, constantly evolving and hella fast MEDIA CUTTER + JOINER w/ frame-accurate SmartCut technology, chapter support, media stream selection for audio + subtitle channels and blackdetect video filter support to automatically detect scene changes or skip commercials in digital TV recordings. Chapter support allows scene chapter names to be included in final media metadata. NOTE: results will only work in media players that support chapters. Flatpak release includes the... -
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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...
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