Only Text Għodda Ġenerattiva għad-Disinn tal-Interjuri minn Zichun Shao

Id-disinn Only Text Għodda Ġenerattiva għad-Disinn tal-Interjuri minn Zichun Shao huwa rebbieħ stmat ħafna tal-prestiġjuż 2023 Premju A' Design Award tal-Ħadid fil-Kategorija tal-Kompetizzjoni ta' Disinn Ġenerattiv, Algoritmiku, Parametriku u Assistit mill-AI.

ĦadidĠenerattiv· 2023

Only Text Għodda Ġenerattiva għad-Disinn tal-Interjuri

minn Zichun Shao

Klijent: Zichun Shao

Rebbieħ tal-Premju A' Design Award tal-Ħadid fil-Kategorija ta' Ġenerattiv

44,535

Rebbieħ ta' Premju Ivverifikat

Ivverifika l-Istatus tal-Premju għal #150725

Ara fuq A' Design Award Stqarrija għall-Istampa Badge tal-Premju

Kuluri

Id-Disinn

Dwar Only Text Għodda Ġenerattiva għad-Disinn tal-Interjuri

Only Text hija għodda ta' disinn ġenerattiv li toħloq immaġini ta' disinn tal-interjuri minn deskrizzjonijiet miktuba. L-għodda hija bbażata fuq mudell ta' diffużjoni mħarreġ għad-disinn professjonali tal-interjuri. Iktar minn 20,000 rendering tal-interjuri ġew miġbura u ttikkettati minn diżajners biex jiffurmaw is-sett ta' data tat-taħriġ. Only Text tista' tipproduċi veduta tal-interjur f'ftit sekondi, b'stil ta' dekorazzjoni magħżul u attributi tal-spazju. Id-dettalji jinbidlu billi jiġi editjat it-test u jerġa' jiġi ġenerat. Il-metodu jneħħi l-immudellar u r-rendering manwali, sabiex ħafna għażliet jistgħu jinqasmu mal-klijenti malajr.

Ir-Rikonoxximent

Dwar il-Premju A' Design Award tal-Ħadid

Only Text Għodda Ġenerattiva għad-Disinn tal-Interjuri huwa rebbieħ tal-Premju A' Design Award tal-Ħadid, rikonoxximent prestiġjuż mogħti lil disinji tajbin li jissodisfaw ir-rekwiżiti professjonali u industrijali mistennija minn ħolqien imfassal tajjeb. Ir-rebbieħa tal-Ħadid juru l-ħila kbira, l-ispeċjalizzazzjoni għolja, il-fehim espert u l-kapaċità kreattiva tal-ħallieqa tagħhom. Huwa mistenni li Only Text Għodda Ġenerattiva għad-Disinn tal-Interjuri ikun ħolqien imqabbar ħafna, mammirat u maħbub li huwa prattiku u innovattiv. Dan id-disinn rebbieħ tal-Ħadid jintegra l-aħjar prattiki tal-industrija u għandu karatteristiċi tekniċi kompetenti marbuta mal-għarfien u t-talent. Only Text Għodda Ġenerattiva għad-Disinn tal-Interjuri huwa rispettat għall-eżattezza tiegħu u mfassal biex itejjeb il-kwalità tal-ħajja u jgħin jagħmel id-dinja post aħjar.

Wara d-Disinn

Kit għall-Istampa

Krediti, membri tat-tim u dettalji tekniċi pprovduti mid-disinjatur.

Proprjetajiet Uniċi: 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.
Dimensjonijiet u Ippakkjar: 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.
Tikketti: Artificial intelligence, Human-computer collaboration, Interior design, Generative design, Text generative design, Efficient design, Rapid modification, Controllable design, Decoration style control
Teknoloġija tal-Produzzjoni: 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.
Sfida tad-Disinn: 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.
Riċerka: 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.
Ispirazzjoni: 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.
Tul tal-Proġett: The project is located in Guangzhou, Guangdong Province, China, and was designed in 2023.
Fluss tal-Operazzjoni: 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.