Technology Inheritance Għodda għall-Ġenerazzjoni ta' Disinn Arkitettoniku minn Junming Chen

Id-disinn Technology Inheritance Għodda għall-Ġenerazzjoni ta' Disinn Arkitettoniku minn Junming Chen 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

Technology Inheritance Għodda għall-Ġenerazzjoni ta' Disinn Arkitettoniku

minn Junming Chen

Klijent: Chen junming

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

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Rebbieħ ta' Premju Ivverifikat

Ivverifika l-Istatus tal-Premju għal #150834

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

Kuluri

Id-Disinn

Dwar Technology Inheritance Għodda għall-Ġenerazzjoni ta' Disinn Arkitettoniku

L-Wirt tat-Teknoloġija hija għodda ta' intelliġenza artifiċjali li tiġġenera disinji tal-esterjur tal-bini. L-għodda toħloq dehriet tal-bini f'diversi stili arkitettoniċi minn test imdaħħal mill-utent. Kull immaġni tiġi prodotta fi ftit sekondi, u d-disinn jista' jinbidel billi tiġi editjata d-deskrizzjoni tat-test. Is-sistema nbniet billi nġabru u ġew ittikkettati eluf ta' rendering arkitettoniċi, u mbagħad ġie rfinat mudell eżistenti ta' ġenerazzjoni ta' immaġini bis-sett ta' dejta l-ġdid. L-għan huwa li jgħin lill-bidejja jilħqu livell professjonali ta' kwalità.

Ir-Rikonoxximent

Dwar il-Premju A' Design Award tal-Ħadid

Technology Inheritance Għodda għall-Ġenerazzjoni ta' Disinn Arkitettoniku 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 Technology Inheritance Għodda għall-Ġenerazzjoni ta' Disinn Arkitettoniku 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. Technology Inheritance Għodda għall-Ġenerazzjoni ta' Disinn Arkitettoniku 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: This project trains an AI that professionally generates the appearance of buildings. The AI can generate buildings of different architectural styles according to the text entered by the user. The AI only takes a few seconds to generate the building's appearance, and users can recreate the design by changing the text description. That is, designers can obtain design concept proposals through AI cooperation and continuously optimize the design.
Dimensjonijiet u Ippakkjar: Generating building exteriors using a fine-tuned stable diffusion technique.
Tikketti: Artificial intelligence, Human-computer cooperation, Architectural appearance generation, Text generation design, Quick modification, Architectural style control
Teknoloġija tal-Produzzjoni: The effect of using stable diffusion to produce architectural appearance could be better. The reason is that this mode needs to sufficiently understand the design skills of different designers, resulting in a messy appearance design and low quality. For this, fine-tuning the existing AI is essential. So this project reworked the data set, fine-tuned the critical stable diffusion, and made an AI to generate the specified architectural style to assist the junior designer in the design.
Sfida tad-Disinn: The challenge of this design is to build a professional architectural design AI for generating high-quality and stylized designs. This project collected and marked thousands of architectural appearance renderings of dozens of well-known architects, created a data set of architectural appearance, and then handed the data set to AI for fine-tuning learning. This project builds an AI to generate a given building's exterior style.
Riċerka: Research Background: It is difficult for beginners to design high-quality architectural appearances.
Methods: This project trained an AI to professionally generate building exteriors, which can contract with designers to complete architectural exterior designs.
Results: Using the AI trained in this project, the designer can generate an architectural appearance rendering in just a few seconds.
Insights: Using this method, the architectural appearance of a specified style can be generated and modified through text description, and the quality of the generated design is close to that of a professional designer. This method does not require manual modeling and rendering, which improves design efficiency and quality.
Ispirazzjoni: Most people measure the quality of a building by evaluating how it looks. Good architectural exterior design can bring attention and economic benefits. However, the exterior architectural design is complex, and the quality of architectural exteriors designed by excellent designers and beginners varies greatly. This design makes an artificial intelligence (AI) that can expertly generate building exteriors to help beginners achieve designs that approach the quality of master builders.
Tul tal-Proġett: The project has already been completed in 2023.
Fluss tal-Operazzjoni: 1. Professional designers collect and mark, and screen images of outstanding designer building exteriors.
2. Use the filtered data to train an AI that specializes in generating the exterior of a given architectural style.
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.