README.md

metadata

title: Template Final Assignment
emoji: 🕵🏻‍♂️
colorFrom: indigo
colorTo: indigo
sdk: gradio
sdk_version: 5.25.2
app_file: app.py
pinned: false
hf_oauth: true
hf_oauth_expiration_minutes: 480

Agent with YouTube Video Analysis

This agent includes advanced YouTube video analysis capabilities using yt-dlp and OpenCV for frame extraction and analysis.

Features

YouTube Video Analysis Tools

The agent is equipped with two powerful YouTube video analysis tools:

1. analyze_youtube_video(video_url, max_frames=6, interval_seconds=45.0)

• Purpose: Downloads a YouTube video and extracts frames at regular intervals for detailed analysis
• Parameters:
  • video_url: YouTube video URL (e.g., https://www.youtube.com/watch?v=VIDEO_ID)
  • max_frames: Maximum number of frames to extract (1-10, default: 6)
  • interval_seconds: Time interval between extractions (minimum: 10s, default: 45s)
• Returns: JSON with video metadata, frame timestamps, and detailed descriptions of each frame
• Use cases: Content analysis, scene detection, video summarization, accessibility descriptions

2. get_youtube_video_info(video_url)

• Purpose: Quickly retrieves video metadata without downloading
• Parameters:
  • video_url: YouTube video URL
• Returns: JSON with title, duration, uploader, view count, description, and resolution
• Use cases: Video verification, content filtering, metadata collection

Technical Implementation

• Video Processing: Uses yt-dlp for robust YouTube video downloading
• Frame Extraction: OpenCV for efficient frame extraction and processing
• Image Processing: PIL and numpy for frame manipulation and encoding
• Analysis Ready: Frames are prepared for image analysis (base64 encoded, resized)
• Error Handling: Comprehensive error handling for network issues, invalid URLs, and processing failures

Example Usage

The agent can answer questions like:

• "Analyze this YouTube video and tell me what happens: [URL]"
• "Extract 5 frames from this video every 60 seconds: [URL]"
• "What is the title and duration of this video: [URL]"
• "Describe the visual content of this tutorial video: [URL]"

Dependencies

• yt-dlp: YouTube video downloading
• opencv-python: Computer vision and frame extraction
• PIL (Pillow): Image processing
• numpy: Numerical operations

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference