Only Text Generativni alat za dizajn enterijera od Zichun Shao

Dizajn Only Text Generativni alat za dizajn enterijera od dizajnera Zichun Shao je visoko cijenjeni dobitnik prestižne nagrade 2023 Željezna nagrada A' Design Award u kategoriji Generativni, Algoritmički, Parametarski i AI-Potpomognuti Dizajn.

ŽeljezoGenerativni· 2023

Only Text Generativni alat za dizajn enterijera

autor Zichun Shao

Klijent: Zichun Shao

Dobitnik nagrade Željezna nagrada A' Design Award u kategoriji Generativni

44,535

Verificirani dobitnik nagrade

Verificirajte status nagrade za #150725

Pogledajte na A' Design Award Saopštenje za medije Značka nagrade

Boje

Dizajn

O dizajnu Only Text Generativni alat za dizajn enterijera

Only Text je generativni alat za dizajn koji kreira slike enterijera na osnovu pisanih opisa. Alat se zasniva na difuzijskom modelu treniranom za profesionalni dizajn enterijera. Prikupljeno je i označeno više od 20.000 renderiranih prikaza enterijera od strane dizajnera kako bi se formirao skup podataka za treniranje. Only Text može proizvesti prikaz enterijera u nekoliko sekundi, sa odabranim stilom dekoracije i prostornim karakteristikama. Detalji se mijenjaju uređivanjem teksta i ponovnim generisanjem. Ova metoda eliminiše ručno modeliranje i renderiranje, omogućavajući da se mnoge opcije brzo podijele s klijentima.

Priznanje

O nagradi Željezna nagrada A' Design Award

Only Text Generativni alat za dizajn enterijera je pobjednik Željezne nagrade A' Design Award, prestižnog priznanja koje se dodjeljuje dobrim dizajnima što ispunjavaju profesionalne i industrijske zahtjeve očekivane od dobro dizajniranih kreacija. Željezni pobjednici pokazuju veliku vještinu, visoku specijalizaciju, stručno razumijevanje i kreativne kapacitete svojih stvaralaca. Očekuje se da Only Text Generativni alat za dizajn enterijera bude visoko cijenjena, voljena i njegovana kreacija koja je praktična i inovativna. Ovaj dizajn koji je osvojio Željeznu nagradu A' Design Award integrira najbolje industrijske prakse i ima kompetentne tehničke karakteristike povezane sa znanjem i talentom. Only Text Generativni alat za dizajn enterijera se poštuje zbog svoje temeljitosti i dizajniran je da pruži poboljšanja kvaliteta života koja pomažu da svijet postane bolje mjesto.

Iza dizajna

Press komplet

Zasluge, članovi tima i tehnički detalji koje je dostavio dizajner.

Jedinstvena svojstva: 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.
Dimenzije i pakovanje: 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.
Oznake: Artificial intelligence, Human-computer collaboration, Interior design, Generative design, Text generative design, Efficient design, Rapid modification, Controllable design, Decoration style control
Tehnologija proizvodnje: 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.
Dizajnerski izazov: 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.
Istraživanje: 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.
Inspiracija: 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.
Trajanje projekta: The project is located in Guangzhou, Guangdong Province, China, and was designed in 2023.
Tok rada: 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.