Crawl4AI

Episode 8: Media Handling: Images, Videos, and Audio

Quick Intro

Showcase Crawl4AI’s media extraction capabilities, including lazy-loaded media and metadata. Demo: Crawl a multimedia page, extract images, and show metadata (alt text, context, relevance score).

Here’s a clear and focused outline for the Media Handling: Images, Videos, and Audio video:

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Media Handling: Images, Videos, and Audio

1) Overview of Media Extraction in Crawl4AI:

• Crawl4AI can detect and extract different types of media (images, videos, and audio) along with useful metadata.
• This functionality is essential for gathering visual content from multimedia-heavy pages like e-commerce sites, news articles, and social media feeds.

2) Image Extraction and Metadata:

• Crawl4AI captures images with detailed metadata, including:
  • Source URL: The direct URL to the image.
  • Alt Text: Image description if available.
  • Relevance Score: A score (0–10) indicating how relevant the image is to the main content.
  • Context: Text surrounding the image on the page.
• Example:

  result = await crawler.arun(url="https://example.com")
  
  for image in result.media["images"]:
      print(f"Source: {image['src']}")
      print(f"Alt Text: {image['alt']}")
      print(f"Relevance Score: {image['score']}")
      print(f"Context: {image['context']}")
  

• This example shows how to access each image’s metadata, making it easy to filter for the most relevant visuals.

3) Handling Lazy-Loaded Images:

• Crawl4AI automatically supports lazy-loaded images, which are commonly used to optimize webpage loading.
• Example with Wait for Lazy-Loaded Content:

  result = await crawler.arun(
      url="https://example.com",
      wait_for="css:img[data-src]",  # Wait for lazy-loaded images
      delay_before_return_html=2.0   # Allow extra time for images to load
  )
  

• This setup waits for lazy-loaded images to appear, ensuring they are fully captured.

4) Video Extraction and Metadata:

• Crawl4AI captures video elements, including:
  • Source URL: The video’s direct URL.
  • Type: Format of the video (e.g., MP4).
  • Thumbnail: A poster or thumbnail image if available.
  • Duration: Video length, if metadata is provided.
• Example:

  for video in result.media["videos"]:
      print(f"Video Source: {video['src']}")
      print(f"Type: {video['type']}")
      print(f"Thumbnail: {video.get('poster')}")
      print(f"Duration: {video.get('duration')}")
  

• This allows users to gather video content and relevant details for further processing or analysis.

5) Audio Extraction and Metadata:

• Audio elements can also be extracted, with metadata like:
  • Source URL: The audio file’s direct URL.
  • Type: Format of the audio file (e.g., MP3).
  • Duration: Length of the audio, if available.
• Example:

  for audio in result.media["audios"]:
      print(f"Audio Source: {audio['src']}")
      print(f"Type: {audio['type']}")
      print(f"Duration: {audio.get('duration')}")
  

• Useful for sites with podcasts, sound bites, or other audio content.

6) Filtering Media by Relevance:

• Use metadata like relevance score to filter only the most useful media content:

  relevant_images = [img for img in result.media["images"] if img['score'] > 5]
  

• This is especially helpful for content-heavy pages where you only want media directly related to the main content.

7) Example: Full Media Extraction with Content Filtering:

• Full example extracting images, videos, and audio along with filtering by relevance:

  async with AsyncWebCrawler() as crawler:
      result = await crawler.arun(
          url="https://example.com",
          word_count_threshold=10,  # Filter content blocks for relevance
          exclude_external_images=True  # Only keep internal images
      )
  
      # Display media summaries
      print(f"Relevant Images: {len(relevant_images)}")
      print(f"Videos: {len(result.media['videos'])}")
      print(f"Audio Clips: {len(result.media['audios'])}")
  

• This example shows how to capture and filter various media types, focusing on what’s most relevant.

8) Wrap Up & Next Steps:

• Recap the comprehensive media extraction capabilities, emphasizing how metadata helps users focus on relevant content.
• Tease the next video: Link Analysis and Smart Filtering to explore how Crawl4AI handles internal, external, and social media links for more focused data gathering.

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This outline provides users with a complete guide to handling images, videos, and audio in Crawl4AI, using metadata to enhance relevance and precision in multimedia extraction.