Instagram Reel Text Extractor

The Instagram Reel Text Extractor is an Apify Actor that reads public Instagram Reels and returns every piece of visible on-screen text as structured data. Businesses overlay text, captions, stickers, hashtags, and watermarks directly onto their videos — this Actor unlocks that content for search, analysis, and database ingestion without manual review.

Each reel is processed by AI vision and the results are returned as a flat, structured dataset of text segments — each with its timestamp, type, screen position, language, and confidence rating.

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Key Features

• Full on-screen text extraction: Captures animated overlays, editor captions, Instagram stickers, watermarks, hashtags, and @mentions.
• Timestamp-aware: Records the MM:SS timestamp when each text element first appears.
• Type classification: Distinguishes overlay, caption, sticker, watermark, hashtag, mention, and other text types.
• Multilingual: Detects the ISO 639-1 language code for each segment from the text itself.
• Position detection: Classifies text placement as top, center, or bottom of screen.
• Confidence rating: High/medium/low rating based on text clarity in the video frame.
• No login required: Works with any public Instagram Reel.

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Why Extract Text from Reels?

Instagram Reels have become a primary publishing surface for businesses, creators, and brands. Menu specials, product drops, event announcements, hiring notices, and pricing updates are routinely shared only as Reel overlays — never structured or indexed. This Actor makes that content machine-readable for:

• Content intelligence and brand monitoring tracking what competitors publish in Reels.
• Food and hospitality capturing daily specials and seasonal menus announced via video.
• Event aggregators extracting event names, dates, and lineup text from promotional Reels.
• Retail and e-commerce indexing product drops, discount codes, and launch dates.
• Market research tracking pricing, offers, and messaging trends across accounts.
• Accessibility tools converting visual Reel text to readable formats.

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Who Is It For?

• Marketing and analytics teams monitoring brand or competitor Reel content at scale.
• Product and data teams building structured datasets from Instagram video content.
• Developers integrating Reel text extraction into discovery or monitoring pipelines.
• Researchers studying visual communication trends in short-form video.

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Input Schema

{
  "reelUrls": [
    "https://www.instagram.com/reel/DY8NM9WJfM8/"
  ],
  "maxItems": 10
}

reelUrls is required. All other fields are optional.

Field	Type	Default	Description
reelUrls	Array of strings	—	Public Instagram Reel URLs (/reel/... or /p/...)
maxItems	Integer	10	Maximum number of reels to process in a single run

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Output Schema

Each dataset item represents one reel and all the on-screen text found in it:

{
  "reelUrl": "https://www.instagram.com/reel/DY8NM9WJfM8/",
  "shortcode": "DY8NM9WJfM8",
  "textSegments": [
    {
      "text": "POV: Getting robbed at gunpoint but you're fat",
      "timestamp": "00:00",
      "type": "overlay",
      "position": "top",
      "language": "en",
      "confidence": "high"
    }
  ],
  "scrapedAt": "2026-06-01T08:15:42.000Z"
}

Field	Description
reelUrl	Normalized canonical URL of the reel
shortcode	Instagram shortcode (e.g. ABC123)
textSegments	Array of all on-screen text elements found
textSegments[].text	The visible text content as it appears on screen
textSegments[].timestamp	MM:SS when the text first appears — null if indeterminate
textSegments[].type	overlay | caption | sticker | watermark | hashtag | mention | other
textSegments[].position	top | center | bottom — vertical screen position, null if it moves
textSegments[].language	ISO 639-1 language code detected from the text, e.g. "en", "es" — null if indeterminate
textSegments[].confidence	high | medium | low — extraction confidence based on text clarity
scrapedAt	ISO timestamp of when this reel was processed

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How It Works

1. Validate inputs — each URL is checked against accepted Instagram Reel URL patterns and normalized to a canonical form.
2. Fetch video — the Reel is retrieved without requiring a browser or login session.
3. AI text extraction — the video is analyzed by AI vision to extract all visible on-screen text in a single pass.
4. Structured output — each text segment is classified by type, position, language, and confidence.
5. Push to dataset — one dataset row is pushed per reel containing all its text segments.

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Notes and Limitations

• Public reels only: Private accounts and reels that require login to view are not supported.
• Video availability: Deleted or expired reels will fail to download and are skipped with a warning.
• OCR accuracy: Fast-moving, small-font, or low-contrast text may yield lower confidence extractions.
• Rate limiting: Instagram may rate-limit requests at high volume. Reduce concurrency or add delays between runs if you encounter failures.
• Video size: Very large Reels are skipped automatically.
• Audio not included: Spoken content is intentionally excluded — only text visually rendered on screen is extracted.