Automated Image Metadata Tagging

Target Audience

• Photographers: Those looking to automatically tag and organize their images for better searchability.
• Content Creators: Individuals who frequently use images in their work and need a streamlined process for metadata management.
• Digital Asset Managers: Professionals managing large collections of images who require efficient tagging and metadata integration.
• Developers: Those interested in integrating AI-based image analysis into their applications or workflows.
• Businesses: Organizations that rely on visual content for marketing and need to enhance their image libraries with relevant metadata.

Problem Solved

This workflow addresses the challenge of manually tagging images with relevant metadata. It automates the process by:

• Extracting image content from Google Drive.
• Analyzing the image using AI to generate descriptive tags.
• Writing these tags back into the image metadata, ensuring images are easily searchable and organized. This significantly reduces the time and effort required for metadata management, allowing users to focus on their core tasks.

Workflow Steps

1. Trigger: The workflow begins when a new file is added to a specific Google Drive folder.
2. Download Image File: The newly added image is downloaded for processing.
3. Analyze Image Content: The downloaded image is analyzed using AI, generating a comma-separated list of keywords that describe the image's content.
4. Extract Metadata: The workflow extracts existing metadata from the image file.
5. Merge Metadata and Base64 Code: The generated keywords are combined with the extracted metadata.
6. Write Metadata to Base64 Code: A code node processes the merged data, incorporating the keywords into the image metadata.
7. Convert to File: The modified image data is converted back into a file format.
8. Update Image File: The original image file in Google Drive is updated with the new metadata, ensuring the changes are saved and accessible.