Only Text Generative Interior Design Tool by Zichun Shao

Only Text Generative Interior Design Tool by Zichun Shao is a highly esteemed winner of the very prestigious 2023 A' Design Award nga Puthaw in Heneratibo, Algoritmiko, Parametriko ug Disenyo nga Tinabangan sa AI Competition Category.

PuthawHeneratibo· 2023

Only Text Generative Interior Design Tool

by Zichun Shao

Client: Zichun Shao

A' Design Award nga Puthaw Winner in Heneratibo Category

43,980

Verified Award Winner

Verify Award Status for #150725

View at A' Design Award Press Release Award Badge

Colors

The Design

About Only Text Generative Interior Design Tool

Ang Only Text usa ka generative design tool nga naghimo og interior design nga mga imahe gikan sa sinulat nga mga deskripsyon. Ang tool naka-base sa usa ka diffusion model nga gi-train alang sa propesyonal nga interior design. Kapin sa 20,000 ka interior renderings ang gikolekta ug gi-label sa mga designer aron makahimo sa training data set. Ang Only Text makahimo og interior view sulod sa pipila ka segundo, uban sa gipili nga estilo sa dekorasyon ug mga kinaiya sa espasyo. Ang mga detalye mausab pinaagi sa pag-edit sa teksto ug pag-generate pag-usab. Ang metodo nagtangtang sa manual nga modeling ug rendering, mao nga daghang mga opsyon ang mahimong ipakita dayon sa mga kliyente.

The Recognition

About the A' Design Award nga Puthaw

Only Text Generative Interior Design Tool usa ka mananaog sa A' Design Award nga Puthaw, usa ka dungganon nga pag-ila nga gihatag sa maayong mga disenyo nga nakatagbo sa propesyonal ug industriyal nga mga gikinahanglan nga gipaabot gikan sa maayo ang pagkadisenyo nga mga paglalang. Ang mga mananaog sa Puthaw nagpakita og dakong kahanas, taas nga espesyalisasyon, eksperto nga pagsabot, ug mamugnaon nga abilidad sa ilang mga tiglalang. Gilauman nga ang Only Text Generative Interior Design Tool mahimong gipabilhan, gihangaan, ug gihigugma nga paglalang nga praktikal ug bag-o. Kini nga disenyo nga nakadaog og A' Design Award nga Puthaw naghiusa sa labing maayong mga praktis sa industriya ug adunay hanas nga teknikal nga mga kinaiya nga nalambigit sa kahibalo ug talento. Only Text Generative Interior Design Tool gitahod tungod sa pagkamaabtik niini ug gidisenyo aron maghatag og mga pagpaayo sa kalidad sa kinabuhi nga makatabang sa paghimo sa kalibutan nga mas maayong dapit.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: The design was done by artificial intelligence (AI) in collaboration with designers. This project has trained an AI for professional interior design generation, which can generate interior designs with different decoration styles according to the input text. It only takes a few seconds for AI to generate a new interior design, and it can quickly generate a large number of designs for communication with users, thereby improving design efficiency.
Dimensions & Packaging: The project uses diffusion model technology, using artificial intelligence to cooperate with designers to generate designs of different decorative styles. We retrained a professional interior design AI to quickly create designs with varying decoration styles.
Tags: Artificial intelligence, Human-computer collaboration, Interior design, Generative design, Text generative design, Efficient design, Rapid modification, Controllable design, Decoration style control
Production Technology: Ordinary AI cannot generate interior design according to specific "decoration style" and "space attributes," which is a fatal flaw for interior design. To this end, this project collected more than 20,000 interior design renderings, labeled them to make a data set and gave the data set to AI for learning, thus creating an AI suitable for interior design. The AI can generate interior renderings specifying "decorative style" and "space attributes" by inputting text.
Design Challenge: The challenge of this design is to build a professional interior design AI that generates designs of high quality and correct decor. To this end, this project asked professional designers to collect and label tens of thousands of interior design images and then handed over the filtered data to AI for training. Make AI understand what is "decorative style," "spatial attributes," and "aesthetic attributes" and generate an interior design with a specified decorative style.
Research: Research Background: Interior design communication is complex, and obtaining designs and communicating with customers quickly is necessary.
Methods: This project trained an AI to generate interior designs professionally and used the AI to collaborate with humans to create interior designs in various decorative styles from the text.
Results: Using the AI trained in this project, designers can generate an interior design rendering in just a few seconds.
Insights: This project approach rapidly generates large batches of interior designs for specified decor styles and spatial properties and allows new designs to be generated by modifying text. This method eliminates the need for manual modeling and rendering, which improves design efficiency.
Inspiration: It is difficult for users to imagine the scheme described by the designer in words. Designers need to turn thinking into design quickly. With the development of artificial intelligence (AI), designers can generate designs directly from text. Specifically, this project trained an AI to create interior design, which can generate interior design only by inputting text, improving communication efficiency between designers and users.
Project Duration: The project is located in Guangzhou, Guangdong Province, China, and was designed in 2023.
Operation Flow: 1. Professional designers collect interior design images and mark and screen them.
2. Use the filtered data to train a professional interior design AI.
3. Designers use AI to design.
4. The designer inputs the design text description into the AI to specify the decoration style.
5. AI generates the interior design of the specified decoration style.
6. Modify the unsatisfactory details in the design through text description, and regenerate the design.
7. After adjusting the text description and generating it multiple times, a good design is obtained.