Search Results for "ai models"
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Showing 23 open source projects for "ai models"
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HyperFrames
Write HTML. Render video. Built for agents
...It supports integration with AI models to generate or modify content within these frames, allowing real-time adaptation. The framework emphasizes composability, enabling developers to build complex experiences by combining smaller units. It is also designed to be extensible, allowing integration with different platforms and tools. Overall, Hyperframes provides a flexible infrastructure for building dynamic, AI-driven content systems that go beyond static outputs. -
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OpenShorts
Free & open source AI video platform
...It also supports generating marketing videos using AI actors, voiceovers, and scripted narratives without requiring cameras or production resources. The platform integrates publishing capabilities, allowing users to distribute content directly to TikTok, Instagram, and YouTube. Its architecture uses modern technologies such as FastAPI, FFmpeg, and AI models for transcription, analysis, and rendering. -
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Palmier Pro
macOS video editor built for AI
Palmier Pro is an open-source video editor for Mac built around AI-assisted video creation. It lets users and coding agents work together directly inside a timeline, blending traditional editing with generative workflows. The app is written from scratch in Swift and takes inspiration from professional editors like Premiere Pro while rethinking the workflow around AI. Users can generate videos and images inside the editor with models such as Seedance, Kling, and Nano Banana Pro. ... -
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nunif
Misc; latest version of waifu2x; 2D video to stereo 3D video
nunif is a deep learning–based image processing framework focused on image upscaling, restoration, denoising, and enhancement tasks using neural network models. The project provides a collection of AI-powered utilities designed primarily for anime-style artwork, illustrations, and high-quality image restoration workflows. It includes command-line tools and graphical interfaces for applying trained neural models to improve image resolution and visual clarity while minimizing artifacts. nunif supports GPU acceleration and batch processing, making it suitable for creators, archivists, and enthusiasts handling large image collections. ... -
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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... -
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Bloom
An open source, agentic Loom alternative
...Bloom supports the concept of “agentic video,” where recordings are not just passive media files but interactive assets that can be searched, summarized, and transformed into workflows or insights. This makes it particularly useful for use cases such as debugging AI agents, documenting processes, training models, or creating automated video-based reports. -
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Transcoder
Hardware-accelerated video transcoding using Android MediaCodec APIs
Transcoder by DeepMedia is an AI-powered video-to-video speech translation engine that enables fully automated multilingual dubbing. Unlike traditional speech translation systems that rely on multi-stage pipelines, Transcoder directly translates one speaker’s video into another language while preserving facial expressions, lip-sync, and vocal identity. Designed for real-time use and production-grade pipelines, Transcoder combines advanced deep learning models with GPU acceleration to deliver high-quality translations across languages. ... -
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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. -
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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 switch to alternative layouts such as letterboxing to maintain context. ... -
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.
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Warlock-Studio
AI Suite for upscaling, interpolating & restoring images/videos
v6.0. Warlock-Studio is a Windows application that uses Real-ESRGAN, BSRGAN, IRCNN, GFPGAN, RealESRNet, RealESRAnime and RIFE Artificial Intelligence models to upscale, restore faces, interpolate frames and reduce noise in images and videos. the application supports GPU acceleration (including multi-GPU setups) and offers batch processing for large workloads. It includes drag-and-drop handling for single or multiple files, optional pre-resize functions, and an automatic tiling system... -
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Smooth My Video
Offline AI frame interpolation, upscaling and HDR for NVIDIA GPUs
Turn any video into a buttery-smooth high-frame-rate copy, entirely offline on your NVIDIA GPU. Pick a file, choose a target frame rate (2x, 4x, 8x and up, or match your monitor) and click Smooth It! Five interpolation models: GMFSS (best for anime), RIFE (best for live action) with a DRBA option that preserves anime pacing, NVIDIA DLSS 4.5 Frame Generation, Nvidia Smooth Motion, and SVP's svpflow engine. The same render can AI-upscale to 16K (RTX Video Super Resolution + Real-ESRGAN restore), sharpen, and convert SDR to real HDR10 with proper mastering metadata, plus optional Dolby Vision 8.1 and HDR10+ export. ... -
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blackvideo-mini-player
A standalone lightweight auxiliary CLI video player for BlackVideo.
Lightweight cross-platform video player (Ada + SDL2 + FFmpeg). Support player for the BlackVideo. Works standalone via CLI or right-click on any video file. Usage Method 1 — Command Line Step 1. Unzip blackvideo-mini-player-v2.3.0.win.zip Step 2. Open the build\ folder, then type cmd directly in the address bar and press Enter — this opens a terminal already in that folder. Alternatively: open Command Prompt anywhere and use cd with the copied path: cd... -
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AI-Shorts-Creator
Python-based tool that leverages the power of GPT-4
AI-Shorts-Creator is a Python-based tool that automates the creation of short-form videos by analyzing long-form content and extracting the most engaging segments. It uses AI models to evaluate transcripts and identify highlight moments, then processes video clips accordingly. The system integrates FFmpeg and OpenCV to crop videos dynamically, often using face detection to keep subjects centered. -
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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. ... -
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AI Models
A repository of trained models
All models (at least currently) are supported by chaiNNer, an upscaling GUI that allows for both very simple and very complex tasks to be completed in a nice manner where you "chain" nodes together. Highly recommended for images. If you're looking to upscale videos using the models then use enhancr simply due to the fact that it supports TensorRT, which will allow you to upscale videos at incredible speeds! The GUI is one of the best looking applications out there and is personally my go to... -
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enhancr
Video Frame Interpolation & Super Resolution using NVIDIA's TensorRT
enhancr is an elegant and easy to use GUI for Video Frame Interpolation and Video Upscaling which takes advantage of artificial intelligence - built using node.js and Electron. It was created to enhance the user experience for anyone interested in enhancing video footage using artificial intelligence. The GUI was designed to provide a stunning experience powered by state-of-the-art technologies without feeling clunky and outdated like other alternatives. It features blazing-fast TensorRT... -
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Automatic YouTube subtitle generation
Using OpenAI's Whisper to automatically generate YouTube subtitles
Automatic YouTube subtitle generation is a command-line tool that combines YouTube downloading capabilities with AI-powered transcription using Whisper models. It allows users to download videos or audio from YouTube and automatically generate subtitles or transcripts. The tool processes media locally, extracting audio and applying speech recognition to produce accurate text outputs. It supports multiple languages and can handle different Whisper model sizes, balancing performance and accuracy. yt-whisperc is designed for automation, enabling batch processing of multiple videos for transcription workflows. ... -
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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... -
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G2SConverter
Convert models from GoldSource engine to Source engine with AI
Convert models from GoldSource engine to the Source engine with AI. This utility converts GoldSource engine models to Source engine models. A feature of this utility is the ability to improve the quality of textures of models using Upscaling, deblurring, and normal map generating. All operations to improve the quality of textures are performed by neural networks. -
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avio
Python version of ffplay with built-in AI
See the Files tab above for installation instructions -
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TimeSformer
The official pytorch implementation of our paper
TimeSformer is a vision transformer architecture for video that extends the standard attention mechanism into spatiotemporal attention. The model alternates attention along spatial and temporal dimensions (or designs variants like divided attention) so that it can capture both appearance and motion cues in video. Because the attention is global across frames, TimeSformer can reason about dependencies across long time spans, not just local neighborhoods. The official implementation in PyTorch... -
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DeepFaceLab
The leading software for creating deepfakes
DeepFaceLab is currently the world's leading software for creating deepfakes, with over 95% of deepfake videos created with DeepFaceLab. DeepFaceLab is an open-source deepfake system that enables users to swap the faces on images and on video. It offers an imperative and easy-to-use pipeline that even those without a comprehensive understanding of the deep learning framework or model implementation can use; and yet also provides a flexible and loose coupling structure for those who want to... -
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YouTube-8M
Starter code for working with the YouTube-8M dataset
youtube-8m is Google’s open source starter code and reference implementation for training and evaluating machine learning models on the YouTube-8M dataset, one of the largest video understanding datasets publicly released. The repository provides a complete pipeline for video-level and frame-level modeling using TensorFlow, including data reading, model training, evaluation, and inference. It was developed to support the YouTube-8M Video Understanding Challenge (hosted on Kaggle and featured...
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