Convert floor plan images to vector data and JSON metadata
Simulate wearing clothes on images
Apply ZCA Whitening to images
Decode images to teacher model outputs
Extract text from images using OCR
Complete depth for images using sparse depth maps
https://huggingface.co/spaces/VIDraft/mouse-webgen
https://huggingface.co/spaces/VIDraft/mouse-webgen
Convert images of screens to structured elements
Train LoRA with ease
Recognize text and formulas in images
Analyze fashion items in images with bounding boxes and masks
Segment human parts in images
Automated Floor Plan Digitalization is an AI-powered tool designed to convert floor plan images into precise vector data and JSON metadata. It streamlines the process of transforming physical or raster floor plans into digital formats, enabling easier editing, analysis, and integration into various applications. This tool is particularly useful for architects, real estate professionals, and facility managers looking to modernize their workflows and improve collaboration.
• Image to Vector Conversion: Accurately converts raster floor plans into editable vector formats like SVG or DWG.
• Metadata Extraction: Automatically extracts room labels, dimensions, and other relevant information into JSON format.
• Scalability: Processes multiple floor plans efficiently, making it ideal for large projects.
• Support for Multiple Formats: Works with various image formats, including PDF, PNG, and JPG.
• Customizable Output: Allows users to specify output formats and levels of detail.
What file formats are supported?
The tool supports common image formats such as PDF, PNG, JPG, and TIFF for input, and outputs vector data in formats like SVG, DWG, and JSON metadata.
How accurate is the conversion?
The accuracy depends on the quality of the input image. High-resolution images with clear markings will yield the best results, while blurry or distorted images may require manual adjustments.
Can I customize the output metadata?
Yes, users can specify metadata fields and formatting requirements during the configuration step to tailor the output to their needs.