Virtual landscape and garden design
TEXT_INPUT:Ask the user for their preferred landscape or garden theme;;CHATGPT:Prompt ChatGPT to generate design ideas based on the chosen theme;;TEXT_INPUT:Ask the user to input the size and shape of their outdoor space;;DALL_E:Generate an image of the proposed landscape or garden design;;DISPLAY_OUTPUT:Present the generated image and design ideas to the user
Generative AI models, including Language Models (LLMs) and image generators, can be used to transform virtual landscape and garden design. An LLM like ChatGPT can process user-defined briefs, like 'design a Japanese Zen garden' and generate detailed landscaping plans, suggesting plant varieties, placement, and maintenance instructions. It can also provide real-time advice, answer questions, and offer iterative refinements based on user feedback.
For image generation, AI models can visualize these verbal descriptions into stunning digital visuals. For instance, given the input 'a tranquil pond surrounded by cherry blossoms and bamboo screens', the AI can generate an accurate, photorealistic visual representation. They could also iterate designs based on new input - a shifted perspective, a change of plant species or a new design trend. Together, these capabilities could help both professionals and hobbyists explore countless landscape and garden design possibilities beyond their imagination.
How to build with Clevis
This is an example of an app built using Clevis: a Virtual Landscape and Garden Design App. You can build similar apps within the same area using Clevis, a robust tool for constructing AI applications. The process is described through a series of steps baked into the app's JSON Configuration.
Firstly, the app asks the user for their preferred landscape or garden theme via a text input function. This could be 'Tropical', 'Desert', 'English Garden', and so on.
Next, it prompts OpenAI's ChatGPT to generate design ideas based on the user's preferred theme. This AI model uses machine learning to comprehend the user's request and deliver creative suggestions.
Thirdly, the user is again asked to provide more specific input regarding the size and shape of their outdoor space. These specifications will guide the creation of a suitable design.
Now, DALL-E, another AI developed by OpenAI, is employed to generate an image of the proposed landscape or garden design. This module translates textual descriptions into vivid, virtual images.
Finally, the app presents the generated image and design ideas to the user using a 'Display Output' function. Here, the user can visualize their dream garden and landscape as conceptualized by powerful AI algorithms.