Image to license plate number

Image to license plate number automates the extraction of license plate numbers from uploaded images, providing quick and accurate results. Users can easily analyze images by uploading them through a simple form, streamlining the process of obtaining essential vehicle information.

7/8/2025
5 nodes
Simple
manualsimplelangchainformformtrigger
Categories:
Manual TriggeredSimple Workflow
Integrations:
LangChainFormFormTrigger

Target Audience

This workflow is ideal for:
- Developers looking to integrate image processing with license plate recognition in their applications.
- Businesses in the automotive or security sectors needing to automate the extraction of license plate numbers from images.
- Researchers interested in studying image recognition technologies and their applications.
- Hobbyists working on DIY projects related to automated vehicle identification or surveillance systems.

Problem Solved

This workflow addresses the challenge of manually extracting license plate numbers from images. By automating this process, it:
- Saves time by eliminating the need for manual data entry.
- Increases accuracy in recognizing and extracting license plate information.
- Improves efficiency for industries that require quick access to vehicle identification data.

Workflow Steps

  • Manual Trigger: The workflow begins when a user uploads an image of a vehicle containing a license plate.
    2. Settings Node: Predefined settings are established, including the language model to be used (openai/gpt-4o) and a prompt that instructs the model to extract the license plate number.
    3. Basic LLM Chain: The uploaded image is processed through a language model that utilizes the specified prompt to analyze the image and extract the license plate number.
    4. OpenRouter LLM: This node further processes the output from the previous step, utilizing the OpenRouter API to enhance the extraction accuracy.
    5. Form Result Page: Finally, the extracted license plate number is displayed to the user in a completion message, providing a clear result of the workflow.

    • Customization Guide

    Users can customize this workflow by:
    - Changing the Language Model: Modify the model parameter in the Settings node to use a different AI model that suits their needs.
    - Adjusting the Prompt: Edit the prompt value in the Settings node to refine the extraction instructions or to adjust for different types of images.
    - Modifying Form Fields: Users can add or change form fields in the FromTrigger node to collect additional data or to change the file types accepted for upload.
    - Enhancing Output: Customize the FormResultPage node to change the format or style of the output message displayed to users.