Best AI tools for< Video Engineer >

Daily is a platform offering real-time voice, video, and AI solutions for developers. It provides ultra-low latency, open-source SDKs, and enterprise reliability since 2016. Daily collaborates with NVIDIA on Voice Agent Blueprint, offers Pipecat - a vendor-neutral open-source orchestration framework, Daily Bots for Pipecat Cloud deployment, and Daily Infrastructure for running real-time calls on WebRTC global infrastructure. The platform ensures the best video quality on every network, with a global mesh network, low latency, and enterprise-grade security features.

Template Prompts is a personal AI prompts generator that allows users to write complex AI prompts, use variables to turn them into templates, and store and organize prompts in a private library. Users can easily change the values of variables to use the same prompt with different data. The tool enables fast copy-paste of customized prompts into AI tools, organizes prompts by tools and tags, and provides a demonstration video for prompt engineering. Users can improve their prompting with fast templating and easy copy-paste.

Mind-Video is an AI tool that focuses on high-quality video reconstruction from brain activity data. It bridges the gap between image and video brain decoding by utilizing masked brain modeling, multimodal contrastive learning, spatiotemporal attention, and co-training with an augmented Stable Diffusion model. The tool aims to recover accurate semantic information from fMRI signals, enabling the generation of realistic videos based on brain activities.

SoraHub is a platform that showcases videos and prompts generated by OpenAI's Sora model. Users can explore the latest Sora-generated content, subscribe to a newsletter for updates, and submit their own prompts for the model to generate. The platform also provides a list of frequently asked questions and answers about the application.

Frigate is an open source NVR application that focuses on locally processed AI object detection for security camera monitoring. It allows users to run advanced analysis on their camera feeds without sending data to the cloud, reducing false positives and providing precise notifications. Frigate offers custom models with Frigate+ and integrates with popular home automation platforms for enhanced functionality.

TubeSum is a Chrome Extension that allows users to summarize YouTube videos efficiently. It provides concise summaries of lengthy content, helping professionals and learners save time and gain insights effortlessly. With TubeSum, users can quickly grasp key points from various types of videos, such as medical lectures, tech tutorials, educational content, podcasts, and daily news broadcasts. The tool aims to streamline the learning process and keep users informed without the need to invest hours in watching full-length videos.

Sighthound is an AI-powered video solutions provider that specializes in solving complex video AI problems at scale. Their products, such as Sighthound ALPR+ for Automatic License Plate Recognition and Sighthound Redactor for Video Redaction, leverage deep learning technology to unlock valuable user insights, reduce operational costs, and increase revenue in the privacy and vehicle recognition space. With a focus on simplicity and customer support, Sighthound offers easy integration of their AI products through simple-to-use APIs.

Tavus is an AI tool that offers digital twin APIs for video generation and conversational video interfaces. It provides developers with cutting-edge AI technology to create immersive video experiences using AI-generated digital twins. Tavus' Phoenix model enables the generation of realistic digital replicas with natural face movements and expressions. The platform also supports rapid training, instant inference, and multi-language capabilities. With a developer-first approach, Tavus focuses on security, trust, and user experience, offering features like dubbing APIs and automated content moderation. The tool is praised for its speed of development cycles, high-quality AI video, and exceptional customer service.

Loom is a free screen recorder for Mac and PC that allows users to easily record and share AI-powered video messages with their teammates and customers. With Loom, users can quickly record their screen and camera, and then share their videos anywhere they work, including Google Workspace, Slack, and more. Loom also offers a variety of features to help users edit and personalize their videos, including the ability to trim and stitch video clips, add custom logos and thumbnails, and add tasks, CTAs, comments, and emojis. Loom is used by over 25 million people across 400,000 companies, and is a valuable tool for sales, engineering, customer support, design, and more.

Videograph is an AI-powered video streaming platform that offers a comprehensive suite of tools for video encoding, live streaming, monetization, analytics, and content distribution. It provides advanced features such as AI cropping for portrait videos, digital asset management, live streaming with low latency, content distribution analytics, and dynamic ad insertion. With seamless organization and precision analytics, Videograph aims to revolutionize video streaming experiences for users. The platform also offers plug-and-play APIs for easy integration and provides robust infrastructure for fast encoding and worldwide delivery.

Valossa is an AI video analysis tool that transcribes videos to text metadata, captions, and clips. It offers a range of AI-powered features such as automating captions, content logging, brand-safe contextual advertising, clip promo videos, identify sensitive content, and analyze video moods and sentiment. Valossa's AI capabilities include speech-to-text, computer vision, emotion analysis, and metadata generation, enabling users to accelerate video productivity with cognitive automation.

Hypergro is an AI-powered platform that specializes in UGC video ads for smart customer acquisition. Leveraging the 4th Generation of AI-powered growth marketing on Meta and Youtube, Hypergro helps businesses discover their audience, drive sales, and increase revenue through real-time AI insights. The platform offers end-to-end solutions for creating impactful short video ads that combine creator authenticity with AI-driven research for compelling storytelling. With a focus on precision targeting, competitor analysis, and in-depth research, Hypergro ensures maximum ROI for brands looking to elevate their growth strategies.

viAct.ai is an AI-powered construction management software and app that utilizes computer vision and video analytics for workplace safety. The platform offers scenario-based AI vision technology to simplify monitoring processes in industries such as construction, oil & gas, mining, manufacturing, and more. viAct.ai helps in automating monitoring tasks, empowering jobsites with automated construction management software powered by AI video analytics.

MMAudio is an AI-powered platform that specializes in transforming silent videos into immersive experiences with intelligent audio synthesis. The advanced AI technology analyzes video content to generate perfectly matched audio, creating professional soundtracks in minutes. MMAudio offers cutting-edge features for video audio generation, catering to various industries such as education, film production, game development, historical film enhancement, social media content, and storytelling. The platform provides seamless AI-powered video to audio transformation in three simple steps: uploading the video, advanced AI analysis, and intelligent audio generation. MMAudio stands out through its high-quality output, real-time processing capabilities, and extensive customization options.

SignalWire is a cloud communications platform that provides a suite of APIs and tools for building voice, messaging, and video applications. With SignalWire, developers can quickly and easily create AI-powered applications without extensive coding. SignalWire's platform is designed to be scalable, reliable, and easy to use, making it a great choice for businesses of all sizes.

Moonvalley is a research company focused on developing generative media using deep learning technology. The team consists of experienced researchers, engineers, and artists from renowned companies such as Deepmind, IBM, and Microsoft. Moonvalley aims to revolutionize the field of generative video production through cutting-edge AI techniques.

The website displays a '404: NOT_FOUND' error message indicating that the deployment cannot be found. It provides a code 'DEPLOYMENT_NOT_FOUND' and an ID 'sin1::t6mdp-1736442717535-3a5d4eeaf597'. Users are directed to refer to the documentation for further information and troubleshooting.

Pixel Dojo is an AI-powered platform that offers a wide range of tools for creators to generate AI art, videos, and character designs. With features like image enhancement, animation, inpainting, and more, Pixel Dojo aims to simplify and elevate the creative process for both beginners and advanced users. The platform integrates multiple professional-grade AI models to provide a seamless and intuitive experience.

The AI Insights website provides quick insights and summaries from leading AI videos on YouTube. It covers a wide range of topics related to artificial intelligence, including key learnings, advancements, and future trends in the AI landscape. Users can stay updated on the latest developments in AI through video summaries and podcasts, gaining valuable knowledge and understanding of complex AI concepts.

OpenGPT is a community for Open AI enthusiasts. It provides access to various AI tools such as GPT Store, OpenGPTs, Open Chat, Open Draw, and Open Video. Users can submit their GPTs and earn credits for free access to advanced AI models like Google Gemini Pro, ChatGPT4, DALL.E.3, and Imagen2.

Intel® Library for Video Super Resolution (Intel® Library for VSR) is a project that offers a variety of algorithms, including machine learning and deep learning implementations, to convert low-resolution videos to high resolution. It enhances the RAISR algorithm to provide better visual quality and real-time performance for upscaling on Intel® Xeon® platforms and Intel® GPUs. The project is developed in C++ and utilizes Intel® AVX-512 on Intel® Xeon® Scalable Processor family and OpenCL support on Intel® GPUs. It includes an FFmpeg plugin inside a Docker container for ease of testing and deployment.

This repository contains course materials for T81 559: Applications of Generative Artificial Intelligence at Washington University in St. Louis. The course covers practical applications of Large Language Models (LLMs) and text-to-image networks using Python. Students learn about generative AI principles, LangChain, Retrieval-Augmented Generation (RAG) model, image generation techniques, fine-tuning neural networks, and prompt engineering. Ideal for students, researchers, and professionals in computer science, the course offers a transformative learning experience in the realm of Generative AI.

BMF (Babit Multimedia Framework) is a cross-platform, multi-language, customizable multimedia processing framework developed by ByteDance. It offers native compatibility with Linux, Windows, and macOS, Python, Go, and C++ APIs, and high performance with strong GPU acceleration. BMF allows developers to enhance its features independently and provides efficient data conversion across popular frameworks and hardware devices. BMFLite is a client-side lightweight framework used in apps like Douyin/Xigua, serving over one billion users daily. BMF is widely used in video streaming, live transcoding, cloud editing, and mobile pre/post processing scenarios.

aiortc is a Python library for Web Real-Time Communication (WebRTC) and Object Real-Time Communication (ORTC). It provides a simple and readable implementation for programmers to understand and tinker with WebRTC internals. The library allows for exchanging audio, video, and data channels, supports SDP generation/parsing, ICE, DTLS, SRTP, SCTP, and various audio/video codecs. It also enables creating innovative products by leveraging Python ecosystem modules, such as computer vision algorithms with OpenCV. Extensive testing ensures high code quality.

Python SDK for LiveKit enables developers to easily integrate real-time video, audio, and data features into their Python applications. By connecting to a LiveKit server, users can quickly build interactive live streaming or video call applications with minimal code. The SDK includes packages for real-time participant connection and access token generation, making it simple to create rooms and manage participants. With asyncio and aiohttp support, developers can seamlessly interact with the LiveKit server API and handle real-time communication tasks effortlessly.

mediasoup-client-aiortc is a handler for the aiortc Python library, allowing Node.js applications to connect to a mediasoup server using WebRTC for real-time audio, video, and DataChannel communication. It facilitates the creation of Worker instances to manage Python subprocesses, obtain audio/video tracks, and create mediasoup-client handlers. The tool supports features like getUserMedia, handlerFactory creation, and event handling for subprocess closure and unexpected termination. It provides custom classes for media stream and track constraints, enabling diverse audio/video sources like devices, files, or URLs. The tool enhances WebRTC capabilities in Node.js applications through seamless Python subprocess communication.

The Prompt Engineering Holy Grail repository is a curated resource for prompt engineering enthusiasts, providing essential resources, tools, templates, and best practices to support learning and working in prompt engineering. It covers a wide range of topics related to prompt engineering, from beginner fundamentals to advanced techniques, and includes sections on learning resources, online courses, books, prompt generation tools, prompt management platforms, prompt testing and experimentation, prompt crafting libraries, prompt libraries and datasets, prompt engineering communities, freelance and job opportunities, contributing guidelines, code of conduct, support for the project, and contact information.

Tools4AI is a Java-based Agentic Framework for building AI agents to integrate with enterprise Java applications. It enables the conversion of natural language prompts into actionable behaviors, streamlining user interactions with complex systems. By leveraging AI capabilities, it enhances productivity and innovation across diverse applications. The framework allows for seamless integration of AI with various systems, such as customer service applications, to interpret user requests, trigger actions, and streamline workflows. Prompt prediction anticipates user actions based on input prompts, enhancing user experience by proactively suggesting relevant actions or services based on context.

LLM Steer is a Python module designed to steer Large Language Models (LLMs) towards specific topics or subjects by adding steer vectors to different layers of the model. It enhances the model's capabilities, such as providing correct responses to logical puzzles. The tool should be used in conjunction with the transformers library. Users can add steering vectors to specific layers of the model with coefficients and text, retrieve applied steering vectors, and reset all steering vectors to the initial model. Advanced usage involves changing default parameters, but it may lead to the model outputting gibberish in most cases. The tool is meant for experimentation and can be used to enhance role-play characteristics in LLMs.

RD-Agent is a tool designed to automate critical aspects of industrial R&D processes, focusing on data-driven scenarios to streamline model and data development. It aims to propose new ideas ('R') and implement them ('D') automatically, leading to solutions of significant industrial value. The tool supports scenarios like Automated Quantitative Trading, Data Mining Agent, Research Copilot, and more, with a framework to push the boundaries of research in data science. Users can create a Conda environment, install the RDAgent package from PyPI, configure GPT model, and run various applications for tasks like quantitative trading, model evolution, medical prediction, and more. The tool is intended to enhance R&D processes and boost productivity in industrial settings.

Learn Agentic AI is a repository that is part of the Panaversity Certified Agentic and Robotic AI Engineer program. It covers AI-201 and AI-202 courses, providing fundamentals and advanced knowledge in Agentic AI. The repository includes video playlists, projects, and project submission guidelines for students to enhance their understanding and skills in the field of AI engineering.

This course has 18 lessons. Each lesson covers its own topic so start wherever you like! Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both **Python** and **TypeScript** when possible. Each lesson also includes a "Keep Learning" section with additional learning tools. **What You Need** * Access to the Azure OpenAI Service **OR** OpenAI API - _Only required to complete coding lessons_ * Basic knowledge of Python or Typescript is helpful - *For absolute beginners check out these Python and TypeScript courses. * A Github account to fork this entire repo to your own GitHub account We have created a **Course Setup** lesson to help you with setting up your development environment. Don't forget to star (🌟) this repo to find it easier later. ## 🧠 Ready to Deploy? If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both **Python** and **TypeScript**. ## 🗣️ Meet Other Learners, Get Support Join our official AI Discord server to meet and network with other learners taking this course and get support. ## 🚀 Building a Startup? Sign up for Microsoft for Startups Founders Hub to receive **free OpenAI credits** and up to **$150k towards Azure credits to access OpenAI models through Azure OpenAI Services**. ## 🙏 Want to help? Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request ## 📂 Each lesson includes: * A short video introduction to the topic * A written lesson located in the README * Python and TypeScript code samples supporting Azure OpenAI and OpenAI API * Links to extra resources to continue your learning ## 🗃️ Lessons | | Lesson Link | Description | Additional Learning | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 00 | Course Setup | **Learn:** How to Setup Your Development Environment | Learn More | | 01 | Introduction to Generative AI and LLMs | **Learn:** Understanding what Generative AI is and how Large Language Models (LLMs) work. | Learn More | | 02 | Exploring and comparing different LLMs | **Learn:** How to select the right model for your use case | Learn More | | 03 | Using Generative AI Responsibly | **Learn:** How to build Generative AI Applications responsibly | Learn More | | 04 | Understanding Prompt Engineering Fundamentals | **Learn:** Hands-on Prompt Engineering Best Practices | Learn More | | 05 | Creating Advanced Prompts | **Learn:** How to apply prompt engineering techniques that improve the outcome of your prompts. | Learn More | | 06 | Building Text Generation Applications | **Build:** A text generation app using Azure OpenAI | Learn More | | 07 | Building Chat Applications | **Build:** Techniques for efficiently building and integrating chat applications. | Learn More | | 08 | Building Search Apps Vector Databases | **Build:** A search application that uses Embeddings to search for data. | Learn More | | 09 | Building Image Generation Applications | **Build:** A image generation application | Learn More | | 10 | Building Low Code AI Applications | **Build:** A Generative AI application using Low Code tools | Learn More | | 11 | Integrating External Applications with Function Calling | **Build:** What is function calling and its use cases for applications | Learn More | | 12 | Designing UX for AI Applications | **Learn:** How to apply UX design principles when developing Generative AI Applications | Learn More | | 13 | Securing Your Generative AI Applications | **Learn:** The threats and risks to AI systems and methods to secure these systems. | Learn More | | 14 | The Generative AI Application Lifecycle | **Learn:** The tools and metrics to manage the LLM Lifecycle and LLMOps | Learn More | | 15 | Retrieval Augmented Generation (RAG) and Vector Databases | **Build:** An application using a RAG Framework to retrieve embeddings from a Vector Databases | Learn More | | 16 | Open Source Models and Hugging Face | **Build:** An application using open source models available on Hugging Face | Learn More | | 17 | AI Agents | **Build:** An application using an AI Agent Framework | Learn More | | 18 | Fine-Tuning LLMs | **Learn:** The what, why and how of fine-tuning LLMs | Learn More |

MaixPy is a Python SDK that enables users to easily create AI vision projects on edge devices. It provides a user-friendly API for accessing NPU, making it suitable for AI Algorithm Engineers, STEM teachers, Makers, Engineers, Students, Enterprises, and Contestants. The tool supports Python programming, MaixVision Workstation, AI vision, video streaming, voice recognition, and peripheral usage. It also offers an online AI training platform called MaixHub. MaixPy is designed for new hardware platforms like MaixCAM, offering improved performance and features compared to older versions. The ecosystem includes hardware, software, tools, documentation, and a cloud platform.

Pixeltable is a Python library designed for ML Engineers and Data Scientists to focus on exploration, modeling, and app development without the need to handle data plumbing. It provides a declarative interface for working with text, images, embeddings, and video, enabling users to store, transform, index, and iterate on data within a single table interface. Pixeltable is persistent, acting as a database unlike in-memory Python libraries such as Pandas. It offers features like data storage and versioning, combined data and model lineage, indexing, orchestration of multimodal workloads, incremental updates, and automatic production-ready code generation. The tool emphasizes transparency, reproducibility, cost-saving through incremental data changes, and seamless integration with existing Python code and libraries.

LLM_Notebooks is a repository supporting The Machine Learning Engineer YouTube channel. It contains materials related to various topics such as Generative AI, MLOps, ML projects, Azure Projects, Google VertexAi, ML Tricks, and more. The repository includes notebooks and code in Python and C#, with a focus on Python. The videos on the channel cover a wide range of topics in English and Spanish, organized into playlists based on general themes. The repository links are provided in the video descriptions for easy access. The creator uploads videos regularly and encourages viewers to subscribe, like, and leave constructive comments. The repository serves as a valuable resource for learning and exploring machine learning concepts and tools.

AI-in-a-Box is a curated collection of solution accelerators that can help engineers establish their AI/ML environments and solutions rapidly and with minimal friction, while maintaining the highest standards of quality and efficiency. It provides essential guidance on the responsible use of AI and LLM technologies, specific security guidance for Generative AI (GenAI) applications, and best practices for scaling OpenAI applications within Azure. The available accelerators include: Azure ML Operationalization in-a-box, Edge AI in-a-box, Doc Intelligence in-a-box, Image and Video Analysis in-a-box, Cognitive Services Landing Zone in-a-box, Semantic Kernel Bot in-a-box, NLP to SQL in-a-box, Assistants API in-a-box, and Assistants API Bot in-a-box.

Awesome-LLMs-for-Video-Understanding is a repository dedicated to exploring Video Understanding with Large Language Models. It provides a comprehensive survey of the field, covering models, pretraining, instruction tuning, and hybrid methods. The repository also includes information on tasks, datasets, and benchmarks related to video understanding. Contributors are encouraged to add new papers, projects, and materials to enhance the repository.

Video-MME is the first-ever comprehensive evaluation benchmark of Multi-modal Large Language Models (MLLMs) in Video Analysis. It assesses the capabilities of MLLMs in processing video data, covering a wide range of visual domains, temporal durations, and data modalities. The dataset comprises 900 videos with 256 hours and 2,700 human-annotated question-answer pairs. It distinguishes itself through features like duration variety, diversity in video types, breadth in data modalities, and quality in annotations.

AI Video Search Engine (AVSE) is a video search engine powered by the latest tools in AI. It allows users to search for specific answers within millions of videos by indexing video content. The tool extracts video transcription, elements like thumbnail and description, and generates vector embeddings using AI models. Users can search for relevant results based on questions, view timestamped transcripts, and get video summaries. AVSE requires a paid Supabase & Fly.io account for hosting and can handle millions of videos with the current setup.

A powerful starting kit for building AI-powered video applications. This toolkit simplifies the complexities of working with AI video models in the browser. It offers browser-native video processing, AI model integration, advanced media capabilities, and developer utilities. The tech stack includes fal.ai for AI model infrastructure, Next.js for React framework, Remotion for video processing, IndexedDB for browser-based storage, Vercel for deployment platform, and UploadThing for file upload. The kit provides features like seamless video handling, multi-clip composition, audio track integration, voiceover support, metadata encoding, and ready-to-use UI components.

An expert in video from classic to future neural network compression

Coconut API Guide

Write a video script of between 750 and 800 words for motion graphics on topics of sustainability in engineering.

Artistic and informative advice on audio/video recording and music production.

Your ultimate guide for navigating AI tools in fields like video, audio, writing, from beginner to expert.

A data assistant for devs, now with real video and image links.

Your ffmpeg command assistant.

Your expert in FFMPEG.

In-depth FFmpeg expert with web browsing and DALL-E capabilities.

Expert in audio format conversion, guiding through simple steps.

A flight simulator, offering immersive flying scenarios and guidance.

Professional guide in computer vision, offering clear, insightful advice.

一个帮助用户写Prompt的专业助手，支持各种模型的文本生视频 Sora｜Pika｜Gen-2 By 内啡肽

I find videos on how items are made from your photos and describe the process.

Create consistency across your AI Film, automatically format Midjourney prompts, and more!

A helpful guide for file size reduction, offering tailored advice on various file types.

Creates AI Prompts for Anime Style AI Images

測試用：引用 OMP YouTube vidoe 回答 Zapier 問題

Expert in video production and editing techniques

Transform your brand! Provide brand and product info, and we'll craft a unique, visually stunning 30-45 second video brief. Simple, effective, impactful.