Automatic Floor Plan Analysis
Develop an algorithm to analyze uploaded images of floor plans automatically. This feature would identify and extract key elements such as walls, furniture, doors, and other relevant components.
Object Detection and Recognition
Implement an object detection and recognition system to accurately identify different elements within the floor plans. This could involve using machine learning techniques such as convolutional neural networks (CNNs) to classify and locate objects.
Canvas Rendering
Create a rendering engine to display the analyzed floor plan elements onto a canvas or graphical interface. Users should be able to visualize the layout with accurately positioned walls, furniture, and doors.
Export and Sharing Options
Enable users to export the finalized floor plans in various formats such as images or PDFs. Additionally, provide sharing options to allow users to easily share their designs with others via email, social media, or collaborative platforms.
Room Functionality Analysis
Implement a feature to analyze the functionality of each room within the floor plan. This could include identifying the primary purpose of the room (e.g., bedroom, kitchen, living room) and suggesting layout optimizations based on typical usage patterns and ergonomic principles.
Semantic Understanding of Floor Plans
Develop an AI model capable of understanding the semantic meaning of elements within floor plans. This could involve training a deep learning model to recognize spatial relationships between objects, such as identifying which furniture items belong to specific rooms or areas.
