Only Text Generativ Inneneinrichtungs-Designtool vum Zichun Shao

D'Wierk Only Text Generativ Inneneinrichtungs-Designtool vum Designer Zichun Shao ass en héich geschätzten Gewënner vum prestigiéisen 2023 A' Design Award an Eisen an der Wettbewerbskategorie Generativt, Algorithmesch, Parametrescht a KI-ënnerstëtzt Design.

EisenGenerativ· 2023

Only Text Generativ Inneneinrichtungs-Designtool

vum Zichun Shao

Client: Zichun Shao

A' Design Award an Eisen Gewënner an der Kategorie Generativ

44,535

Verifizéierte Präisgewënner

Präisstatus fir #150725 verifizéieren

Kuckt beim A' Design Award Pressemëtteelung Award Badge

Faarwen

Den Design

Iwwer Only Text Generativ Inneneinrichtungs-Designtool

Only Text ass en generativ Designtool, dat Interieur-Designbiller aus schrëftlechen Beschreiwungen erstellt. D'Tool baséiert op engem Diffusiounsmodell, dat fir professionell Inneneinrichtung trainéiert gouf. Méi wéi 20.000 Interieur-Renderings goufen vun Designer gesammelt an markéiert, fir den Trainingsdatesaz ze bilden. Only Text kann an e puer Sekonnen eng Interieuransicht generéieren, mat engem gewielte Dekorationsstil an Raumeegenschaften. Detailer ginn geännert andeems een den Text bearbecht an nei generéiert. D'Method eliminéiert manuellt Modelléieren an Rendering, sou datt vill Optiounen séier mat Clienten gedeelt kënne ginn.

D'Unerkennung

Iwwer den A' Design Award an Eisen

Only Text Generativ Inneneinrichtungs-Designtool ass e Gewënner vum A' Design Award an Eisen, enger prestigiéiser Unerkennung, déi un gutt Designe vergi gëtt, déi déi professionell an industriell Ufuerderunge erfëllen, déi vu gutt gestaltene Kreatioune erwaart ginn. Eisen-Gewënner weisen déi grouss Fäegkeet, déi héich Spezialiséierung, dat Expertewëssen an d'kreativ Kapazitéit vun hire Schëpfer. Et gëtt erwaart, datt Only Text Generativ Inneneinrichtungs-Designtool eng héich geschätzt, bewonnert a beléifte Kreatioun ass, déi praktesch an innovativ ass. Dëst mam Eisen ausgezeechent Design integréiert déi beschte Praktike vun der Industrie a huet kompetent technesch Eegeschaften, déi mat Know-how an Talent verbonne sinn. Only Text Generativ Inneneinrichtungs-Designtool gëtt fir seng Grëndlechkeet respektéiert a ass gestalt, d'Liewensqualitéit ze verbesseren an ze hëllefen, d'Welt zu enger besserer Plaz ze maachen.

Hannert dem Design

Press Kit

Credits, Teammemberen an technesch Detailer vum Designer zur Verfügung gestallt.

Eenzegaarteg Eegeschaften: 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.
Dimensiounen & Verpackung: 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
Produktiounstechnologie: 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 Erausfuerderung: 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.
Fuerschung: 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.
Inspiratioun: 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.
Projetdauer: The project is located in Guangzhou, Guangdong Province, China, and was designed in 2023.
Operatiounsablaf: 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.