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Style Copy with Imagen 3.0 (Style Transfer Image Generation Workflow)

This workflow automates the processing of user-uploaded reference images and target descriptions by combining multimodal AI technology to generate new images with a similar visual style. Users can submit images and text prompts, and the system will generate up to four stylistically consistent images, organizing them into a webpage for sharing or sending to an email. This simplifies the design process, lowers the technical barrier, and is suitable for brand designers, marketing teams, and art creators, enhancing the production efficiency of creative content.

Workflow Diagram
Style Copy with Imagen 3.0 (Style Transfer Image Generation Workflow) Workflow diagram

Workflow Name

Style Copy with Imagen 3.0 (Style Transfer Image Generation Workflow)

Key Features and Highlights

This workflow leverages Google’s multimodal large language model Gemini 2.0 to analyze and describe the visual style of user-uploaded reference images. It then combines this style description with user-provided textual prompts for target images to generate new images with similar visual styles using the Google Imagen 3.0 model. The workflow supports generating up to 4 images per request. The generated results are automatically compiled into a web page, which can be sent to the user’s email or downloaded directly, significantly enhancing the efficiency of style transfer-based image generation.

Core Problems Addressed

Traditional style transfer or design variant generation processes are time-consuming and require high technical expertise. This workflow automates the integration of multimodal AI models, enabling users to quickly generate high-quality, style-consistent images without professional design skills, effectively saving time and labor costs.

Application Scenarios

  • Brand designers rapidly generating multiple logos or visual assets with consistent styles
  • Marketing teams quickly iterating and testing creative visual content
  • Artists exploring image variants in different artistic styles
  • Content creators producing personalized visual materials to enhance content appeal

Main Process Steps

  1. Users submit a form with: reference image URL, target image description, desired number of generated images, and optionally an email address.
  2. Validate the submitted reference image URL; if invalid, prompt the user to resubmit.
  3. Download the reference image and convert it to Base64 format; pass it to Gemini 2.0 for visual style analysis to generate a detailed style description.
  4. Combine the style description with the user’s target prompt and invoke Imagen 3.0 to generate new images with similar styles.
  5. Split the generated images, upload them to Cloudinary cloud storage, and obtain stable access URLs.
  6. Generate a display web page presenting all generated images in a gallery format, embedding the style description.
  7. If an email address is provided, automatically send an email containing the generated results web page.
  8. Provide an HTML file download option for offline viewing of the complete generation results.

Involved Systems and Services

  • Google Gemini 2.0 (Multimodal large language model for image style description)
  • Google Imagen 3.0 (Image generation model)
  • Cloudinary (Cloud image storage and CDN)
  • Gmail (Email sending service)
  • n8n built-in nodes (form triggers, HTTP requests, file conversion, conditional logic, HTML generation, etc.)

Target Users and Value Proposition

  • Designers and visual content creators: Quickly produce multiple style-consistent image variants without complex operations.
  • Marketing and branding teams: Obtain diverse visual assets in a short time to support creative marketing campaigns.
  • AI enthusiasts and automation developers: Explore applications of multimodal AI in visual content creation.
  • Enterprises and organizations: Reduce design costs and improve efficiency in producing brand visual assets.

This workflow offers users a streamlined and efficient AI-powered solution for image style transfer, perfectly combining advanced language understanding and image generation technologies to facilitate effortless creative design automation across various user groups.