AI-Based Automatic Image Title and Watermark Generation

Workflow Name

AI-Based Automatic Image Title and Watermark Generation

Key Features and Highlights

This workflow leverages Google Gemini’s multimodal vision-language model to automatically generate semantically rich and structured titles and descriptive texts from input images. The generated text is intelligently overlaid at the bottom of the image, producing a final output with an explanatory watermark. The process integrates multiple steps—including image downloading, resizing, AI text generation, text formatting and parsing, position calculation, and image editing—all fully automated within the n8n platform without manual intervention.

Core Problems Addressed

Traditional image title generation often relies on single-text input, making it difficult to combine visual content understanding with semantic description. Additionally, manually adding captions or watermarks after title generation is cumbersome. This workflow closes the loop between visual AI models and image editing, enabling intelligent content understanding and automated annotation overlay, significantly improving content production efficiency and visual asset protection.

Application Scenarios

• Media Publishing: Automatically generate descriptive titles and annotations for images, accelerating content layout and proofreading workflows
• Social Media Management: Quickly produce images with creative captions, enhancing publishing efficiency and user engagement
• Copyright Protection: Automatically add copyright notices or watermarks on images to prevent unauthorized use
• Visual Data Management: Automatically generate structured annotations for large image collections, facilitating retrieval and classification

Main Workflow Steps

1. Image Import: Fetch images from the web via HTTP request node, with flexibility to replace this trigger to import any image source
2. Image Preprocessing: Resize images to 512×512 pixels to meet AI model input requirements
3. AI Title and Description Generation: Invoke Google Gemini multimodal chat model to generate structured titles and descriptions based on the image content, following a template covering “who, when, where, context, and supplementary information”
4. Output Parsing: Parse the structured text output for downstream processing
5. Text Overlay Position Calculation: Use a code node to dynamically calculate the text display area and font size according to image dimensions and text length
6. Text Overlay: Employ the image editing node to overlay a black semi-transparent background box and white text at the bottom of the image, ensuring clear and readable titles and descriptions
7. Final Image Output: Produce annotated images with AI-generated titles, ready for publishing or archiving

Involved Systems and Services

• Google Gemini (PaLM) Multimodal AI Model: Enables visual content understanding and text generation
• n8n Built-in Nodes: HTTP Request (image import), Code Node (dynamic calculations), Image Editing Node (resizing and text overlay)
• LangChain Integration: Chains language models and parsers to achieve structured text output

Target Users and Value Proposition

• Content creators, media editors, and digital marketers seeking rapid generation of image captions and descriptions
• Designers and brand protection teams needing automated copyright watermarking and annotation
• Developers and automation enthusiasts aiming to build intelligent image processing workflows based on visual AI
• Enterprises and organizations looking to enhance image content management and publishing efficiency while minimizing manual operations

This workflow demonstrates how to combine advanced multimodal AI models with automated image processing technologies to create an intelligent, convenient, and efficient solution for visual content generation and editing.