Many of us think that interior designing is just placing few artifacts here and there, changing the paint, and using color-coordinated upholstery. But, the reality is exactly reverse from this. It involves taking multiple experts’ advice, aligning them with the clients’ needs, and coming up with a viable design.
As each individual has a different thought process and advice is also subjective, it’s hard to strike a balance in all these aspects. Here is good news; technology has broken into the world and has allowed professionals, related to the interior designing industry, to have data-driven recommendations. How it happens and how one can make the most of this technology is what we’re going to explain next in the post.
Business Solution: Smart Product Recommendation System
Interior Designing and its Challenges
Interior designing is one field that involves a lot of guesswork to bring the client’s imagination into reality. Clients only say that they need a modern or rustic set-up with extraordinary elements. The onus of giving birth to this imagination falls on the shoulders of the interior designer.
The expert professional can define and categorize the room style, using the technology. But, it’s hard to explain the design in words. To make things worse, an anticipated room style can have a blend of many styles. The trends in the interior designing industry change so fast that it’s hard to design timeless designs.
Whenever a client is hiring an interior designer for a project, the expectation is having something out of the box. They just have a vague idea of the style in their mind and an interior designer needs to grasp that idea and deliver a solution accordingly.
With so many ambiguities, it’s hard to do an accurate representation of room style. So, does it mean that interior designers should keep on struggling that hard?
Of course not!
There is always a way out. Scroll down to know more about it.
As mentioned above, interior designer applications have shown up for the rescue of interior designers. They feature AI-driven and deep learning-based style aware product recommenders. These style recommenders can capture the data from the style image offered by the client and find a similar design. It happens because of their in-built data labeling approach so that subjectivity is well handled.
Also, they include a deep-learning-based classification that focuses on the high volume classes and samples so that the real-time depiction of the visual features reflecting styles is possible. It’s a strategic approach delivered via blending AI and DIP or Digital Image Processing wherein data captured from an image is processed to deliver desired results.
While you’re thinking of bringing these two technologies to your service, don’t forget to hire an application development company or IT service provider that has mastered the art of these two technologies. Stridely is a trusted name to be taken at this front.
This service provider is has explored AI and DIP to a larger extent and has already delivered multiple solutions, based on these two technologies.
Here are some of the key rewards that any end-user of Style Aware Product Recommender, powered by DIP technology, can relish.
Now that it’s clear that Style Aware Product Recommender is a game-changer for an interior designing domain, it’s time to understand how it works. Basically, its modus operandi is based on two things: data collection/labeling and Training Room Style Estimator (RoSE).
To begin with, an extensive data set of room styles and décor are collected. Mostly, house websites and designers of in-house designers are used to build this database.
As subjectivity is of a higher sort here, each image is tagged by a minimum of 10 experts with specific terms. These specific terms are commonly loosely defined style terms of trending names of the interior industry. The gathered images are then categorized into styles.
At large, the most widely used home décor styles are coastal, rustic, modern, traditional, cottage, industrial, and eclectic.
While this style segregation is done, details about fabric, material, flooring, color scheme, and furniture style are explained.
Once the desired style images are collected, the next step is to build a training room style estimator that can classify the entire room style. It’s done with the help of deep neural networks. By using the customer inputs and gathered data, the style estimator designs the whole room style in no time.
There is no second opinion that DIP and AI-driven style aware recommender is going to make interior designing a lot more simplified and easy. But, it’s not always a cakewalk. If attention is not paid to certain aspects, your entire effort will go in vain. Here is what should be kept in mind while using AI and DIP for style aware recommenders.
The image-based recommendation or digital image processing system of Stridely Solutions is based on Deep Learning and Natural Language Processing. These two are the cutting-edge technologies to use when image-based recommendation system needs to build.
There is one more extraordinary feature about the digital image processing of Stridely Solution and it’s the formation of a Deep Neural Network. As mentioned above, style-aware product recommender needs to create room style estimator with the help of deep neural networks.
Stridely Solutions brings modern deep neural networks to your service for this job, using which one can easily predict the next actions, after a certain action. We can also introduce cross-category personalization in the style aware product recommender. Because of this feature, interior designers can give more personal touch to the designs and make them more accurate.
By integrating the facility of reporting and analytics in the tool, such a solution can prevent you from struggling hard to figure out which style or décor is winning customers’ hearts.
As Stridely Solutions offers constant technical support, AI adoption is risk-free and quick. We have a team of expert AI and digital image processing professionals to handle your needs. Let our expertise help you out in creating an image-based style recommender for your interior firm and enjoy better ROI, higher revenue, and simplified revenue.
Interior designing may seem a piece of cake but it’s a very tedious and brainstorming field wherein it takes a lot to understand what a customer is trying to convey. Designers need to put extra effort to turn the clients’ imagination into reality.
The introduction of an interior designing application, supported by style aware product recommender, has made the job a little more simple and easy to accomplish. Style aware product recommender is a technology, shaped using the AI and digital image processing, that allows interior designers to make accurate and realistic recommendations.
Give it a try and witness the magic by yourself. But, one has to be very diligent as digital image processing, when not done right, can mess –up the whole thing. We would suggest you place your bet on an experienced digital image processing service provider, like Stridely Solutions.
The nitty-gritty of image-based product recommendation solutions at Stridely is powered by AI, deep learning, and natural language processing. They will help you create a high-end image-based product/style recommender and make the job of interior designing effortless than ever. So, don’t tangle in vague and inadequate descriptions that hinder your process. Deliver the best-of-breed home designing solutions.