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Hey everyone, I'm Kedar, and I’m excited to introduce you to VideoAI, a tool that lets you query video content just like a database using natural language! No more wasting time manually seeking through video footage to find key moments—VideoAI makes searching and retrieving information from videos seamless. 🤌
In this blog, I’ll walk you through how VideoAI works, from its processing flow to how it handles user queries. I’ll also highlight the exciting use cases that demonstrate the potential of this tool. Let’s dive in!
TL:DR
What is VideoAI?
VideoAI allows you to search video content as easily as you would query a database. It processes videos in the background, extracting and storing essential metadata so you can simply enter a query like “show me the crocodile” in a animal video and instantly find the corresponding moments in the video.
No more manual scrubbing through hours of footage—just ask, and VideoAI will deliver!
How VideoAI Works
This is the overall working of the app. It has 2 flows, viz., video processing flow and video querying flow.
Part 1: Uploading and Processing Your Video
The first step is uploading your video to VideoAI. Once uploaded, the platform begins to process it in the background. Here’s a step-by-step breakdown of how the magic happens:
Frame Extraction: VideoAI extracts frames from the video at regular intervals (e.g., every 1 second).
Captioning Each Frame: Using an image captioning model, VideoAI generates descriptive captions for each extracted frame. For example, if a frame contains a crocodile swimming in a lake, the model outputs something like, "a crocodile is swimming in the lake in the jungle."
Storing Captions in a Vector Database: These captions, along with their respective timestamps, are then stored in a vector database, making the video content searchable by time and description.
Step 2: Querying the Video
Once your video is processed, querying is as simple as typing or saying what you’re looking for. VideoAI takes your query—like "show me the monkey"—and performs the following:
Vectorizing Your Query: VideoAI converts your natural language query into a vector using the same embedding model that processed the video captions.
Searching the Vector Database: The system compares your query’s vector with the stored caption vectors in the database.
Returning the Relevant Timestamps: It then returns the exact timestamps of the frames that match your query, allowing you to jump straight to the moments you care about.
For instance, in a jungle-themed video containing animals like lions, monkeys, and crocodiles, you can search for "show me the crocodile," and VideoAI will return the precise timestamp where the crocodile appears.
Real-World Applications of VideoAI
VideoAI’s potential spans several industries and use cases. Here are a few exciting possibilities:
1. Surveillance Footage Analysis
Security operators can type in a natural language query like "person entering the building" or "car speeding" and VideoAI will return the exact moments in the surveillance footage where those events occurred. This feature could revolutionize how we handle and analyze security footage.
2. Rapid Media Curation for Broadcasters
Imagine a sports channel needing to curate the "best goals" or "top tackles" from a game. With VideoAI, they can pull these moments by simply querying those terms, saving countless hours of manual editing and review.
3. Video-Driven Search Engines
Picture a future where video search engines don’t rely solely on video titles, but on the actual content inside the videos. Imagine searching on YouTube not by title, but by asking for the specific scene or content you’re looking for!
Built as an MVP: Everything Runs Locally
VideoAI is currently an MVP. Everything is running locally on my machine—from the AI models that generate captions and embeddings, to the storage of video data in the vector database.
Final Thoughts
I’ve had an absolute blast building VideoAI, and I’m incredibly excited about its potential to transform how we interact with videos.
I hope you’re as excited about VideoAI as I am. I’d love to hear your thoughts, feedback, and ideas. Thank you for taking the time to explore this with me!