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January 22, 2024
2min

VisionForge-A effective and efficient solution in the Real Estate and Design Sector

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Prospective home buyers have many factors to consider when looking for their dream home; the neighborhood, noise, environment, and most important of all, the interior of the home itself. Creating an appealing image of one’s home has boomed India’s Interior Design market to $31.5 Billion in 2023 [1]. This includes furniture, modeling, and most important of all when it comes time to sell the house: shooting. An interior photoshoot service of a house, the optimal way to attract buyers to view and tour your house, can be expensive and intrusive, requiring hours if not days of on site photography, editing, and further development. Homesellers often have no other avenue to showcase their homes on websites other than availing these services. This is the problem that VisionForge from Ankercloud is aiming to tackle.

VisionForge is a solution that allows homebuyers to develop high quality, photo realistic, and sharp images of their home, given only a small set of reference images, and reference prompts to encourage adherence and consistency.  Prospective homebuyers can virtually walk through spaces, exploring every nook and cranny with unparalleled detail. From furniture placement to color schemes, potential buyers can tailor the visuals to align with their unique taste and lifestyle. This level of personalization elevates the home-buying experience. Extending their inquisitive designs to realistic visualizations with the high customization capabilities of VisionForge. This immersive experience transcends conventional property viewing, fostering a deeper connection between potential buyers and their envisioned living spaces.

VisionForge works by taking in a set of reference images from the user first. These can include wide shots covering a large area of rooms, or profile shots, focused on a set of objects closely. The room for experimentation and creativity is given to the user. Then, the user can customize their picture based on different color schemes, furniture layouts, lighting, and more. The solution will use templates of prompts combined with a set of parameters unique to each use case and inference to generate high quality images of customized rooms that fit their vision. This allows the user to paint with broad strokes on their home without ever stepping out of it. 

The model works in a two step process, first utilizing a custom trained text to image model that takes in the user’s prompts and settings to generate sets of photorealistic and sharp images that include key features of the rooms/sets in question. Then, the user will be able to edit various aspects of the images, such as colors of certain objects, position, or even the type or style of the objects themselves using an image to image model using inpainting and the Bedrock API from AWS.

Put together, VisionForge is an elegant solution to a prevalent problem, accessible through a single Sagemaker endpoint, robust and flexible enough to handle complex requests and comprehensive product modifications, delivering a stable and highly available product streamlined through the API gateway and Lambda functions. With AWS Bedrock providing a robust foundation, the entire process becomes scalable, reliable, and tailored to the unique demands of various clients and businesses.

VisionForge’s advanced capabilities in image generation bring a new dimension to real estate marketing, offering a personalized and immersive experience for prospective buyers. The tool goes beyond static representations, creating hyper-realistic depictions of interiors that transcend traditional limitations. The ability to visualize spaces in such detail minimizes uncertainties, allowing individuals to make informed decisions confidently. This level of personalization in hand elevates the home-buying experience, making it more engaging and emotionally resonant.

References:

https://www.imarcgroup.com/india-interior-design market#:~:text=The%20India%20interior%20design%20market,8.81%25%20during%202024%2D2032.  

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