web-form-ui-field-detection
| Property | Value |
|---|---|
| Architecture | YOLOv8 |
| Task | Object Detection |
| Performance | mAP@0.95: 0.52196 |
| Training Data | 600 images |
What is web-form-ui-field-detection?
This is a specialized object detection model built on YOLOv8 architecture, designed to detect and locate UI form fields in web images. The model can identify various form elements including input fields, buttons, radio buttons, and other UI components, making it valuable for automated form analysis and processing.
Implementation Details
The model is implemented using the ultralytics framework and requires minimal setup. It uses YOLOv8s as the base architecture and was trained for 1 hour on an NVIDIA GeForce RTX 3090 GPU. The model achieves a precision of 0.80, recall of 0.70, and an F1 score of 0.71.
- Confidence threshold: 0.25
- IoU threshold: 0.45
- Maximum detections per image: 1000
- Training optimizer: Adam with 1e-4 learning rate
Core Capabilities
- Detection of form input fields (name, email, password)
- Button and radio button identification
- Form structure analysis and layout detection
- Automated form field extraction
- UI component recognition
Frequently Asked Questions
Q: What makes this model unique?
The model specializes in web form UI detection, offering high precision in identifying various form elements. Its integration with the ultralytics library makes it easily deployable for practical applications.
Q: What are the recommended use cases?
The model is ideal for automated form processing systems, UI testing tools, web scraping applications, and form accessibility analysis. It's particularly useful for projects requiring automated detection and extraction of form fields from web interfaces.
