Creation of a website with an AI block

Good day! Very interesting AI project.
1. Are there already examples of the desired result or references?
2. Is a web version needed for the site or is a separate application also planned in the future?
3. What is the estimated budget or MVP stage planned initially?

Show original

Translate

Hello, Olena! Interesting project — there is experience with computer vision and image generation.

For your task, the optimal approach is: SAM (Segment Anything) for facade extraction + Stable Diffusion inpainting via Replicate API for generating material variations. This provides a quality result without a dedicated GPU server.

Question: is there already a catalog of facade materials (textures, colors) that need to be applied? This depends on the approach to generation.

Show original

Translate

I will develop an intelligent facade visualization module for your website, which will allow users to instantly "try on" materials on their own homes. With extensive experience in developing complex systems (Magento 2) and integrating AI solutions (Kaggle, Gradio), I will implement a pipeline based on Stable Diffusion and ControlNet for accurate preservation of the architecture of the object. My approach includes automatic segmentation of walls and roofs, ensuring realistic texture overlay without distorting the geometry of windows or doors. I will design a scalable architecture on serverless solutions, allowing the system to handle high loads with minimal initial costs. The estimated development time for the MVP with basic materials is 14–20 days. Please let me know if you already have ready-made texture libraries (high-res photos of materials) that need to be taught to the system to recognize? Let's discuss the technical details and integration with your CMS in private messages.

Show original

Translate

Hello! I reviewed the request — the idea is clear and realistic: photo of the house → AI applies material → 2–3 options → lead for calculation. This is not just "make it beautiful," it is a conversion tool that turns a website visitor into a potential client. My name is Andriy, I am a web designer and Webflow developer with a technical understanding of AI integrations for product solutions. I see that you need not just a developer, but a person who understands the entire chain: technical approach → UX flow → how it sits on the site and leads to the application. Here is my vision for the stack: From a technical approach, it looks optimal like this: facade segmentation through SAM from Meta, texture overlay through Stable Diffusion with ControlNet, orchestration through Replicate or a custom endpoint. This provides a balance between the quality of the result and the speed of generation. A critical point that most overlook — UX between uploading the photo and the result. If the user waits more than 15–20 seconds without feedback, they leave. A proper loading state and the right moment to show the application form are needed. Regarding scaling to a full-fledged application with material calculations — the architecture should be laid out right away, even if the first stage is minimal. Please clarify two points: what platform is the site currently on and is there already an understanding of the budget for the first stage?

Show original

Translate

Hello!

I can implement the MVP version of the AI block:

— User uploads a photo of the house
— Generation of 2–3 options via DALL-E or Stable Diffusion API
— Form for submitting a request for a quote
— Backend on Supabase

… Stack: GPT-4o Vision + DALL-E + Supabase + n8n

I am ready to discuss the technical approach in more detail.

Nazarii

Show original

Translate

Hello. To replace the facades in the photos, it is optimal to use a combination in Python: object segmentation through SAM (Segment Anything Model) and texture generation using Stable Diffusion (ControlNet Inpainting). I will implement the backend on FastAPI with Celery and Redis queues for stable image processing, and we will connect AI models via API or dedicated GPU servers. I will design the architecture immediately for future scaling (databases for the material calculator, React frontend for UI). What is the source of the input photos and the expected peak online for calculating server load?

Show original

Translate

Hello! I have reviewed the task, I have experience with AI integrations and web services. For such a solution, it is optimal to build the flow through segmentation + image generation pipeline — the user uploads a photo, the system identifies facade zones, applies materials, and generates several options through AI models. For implementation, Stable Diffusion/Flux + ControlNet or similar tools can be used for more precise work with facades. It is better to build the architecture scalable from the start, so that in the future, material calculations, estimates, and an ordering system can be added. I am ready to discuss the technical approach and propose an MVP within your budget.

Show original

Translate

Good day!

I have experience at the intersection of AI integrations, web development, automation, and product architecture, so such an AI block for the website is close to me from both a technical and product perspective. I have worked with SaaS products, web interfaces, AI tools, infrastructure, and building solutions that grow from MVP to a full-fledged product.

What I can offer
Based on your idea, I see not just "image generation," but a complete user flow: the user uploads a photo of a house, the system identifies facade zones, applies materials or styles, generates 2-3 controlled options, and then directs the user to a request for a quote.

Such an approach is better built as a modular system, where uploading and preprocessing photos, segmentation of facade zones, generation/redesign, business logic of the request, and user interaction analytics live separately.

… Technical approach
It is optimal to start with an MVP, where AI does not "invent a house from scratch," but works on top of a real photo through segmentation + controlled generation/inpainting, as this provides a more predictable and commercially viable result.

For such a scenario, I would lay out a pipeline with several stages: checking photo quality, highlighting the facade/windows/roof/material zones, applying style or material through controlled generation, and then saving options in CRM/admin along with the client's request.

Models and stack
At the generation level, it makes sense to look towards modern diffusion/architectural rendering models with good image-to-image control, and to preserve geometry — use a ControlNet-like approach, depth/control maps, or inpainting pipeline.

At the computer vision level, a separate segmentation layer is needed, as it determines how accurately the system will work with the facade, windows, roofing, and other zones, rather than just "redrawing the entire photo."

From the production implementation side, I can help design the web part, API integrations, task queues, result storage, and infrastructure for scaling, which aligns well with my experience in web development, SaaS, and AWS/VPS infrastructure.

Scaling
Looking ahead, this should be built not as a one-time "effect on the site," but as the core of a future product: today it is facade visualization, next — material selection, area calculation, preliminary cost estimation, manager's office, and ordering system.

Therefore, architecturally, I would immediately lay out the separation into frontend, AI-processing layer, storage, asynchronous task queue, and CRM/order layer, so that in the future it would be easy to add a material calculator.

Show original

Translate

Hello!

The task is interesting, I have experience with a similar stack (segmentation + generative models for inpainting). I will describe the optimal approach as I see it for starting.

Architecture:
1. Facade segmentation — SAM 2 from Meta + GroundingDINO for isolating walls separately from windows, doors, and the roof. The material will only be applied to the walls.
2. Generation of variants — I suggest using Gemini 2.5 Flash Image (Nano Banana) via API instead of self-hosted diffusion models. Reasons:
• Generation speed — a few seconds versus 15-30 in SDXL
• Supports multi-image input (photo of the house + reference material)
…
Stack: Python, FastAPI, Celery + Redis for the queue, PostgreSQL, S3 for storage. GPUs are not needed at all at the start — everything through API.

I am immediately planning for scaling: a queue with priorities, versioning of prompts and models, logging parameters of each generation (for reproducibility and A/B tests), auto-scaling of workers.

Show original

Translate

Good day!

I am ready to complete your project. I work with web development and design, have practical experience and a portfolio.

I have worked with clients from Ukraine and Europe, adhere to deadlines, and am always in touch.

I am ready to discuss the details and offer the optimal solution. I can start as soon as possible.

Show original

Translate

Good day! To begin with, if this is a block, we need to understand what backend is being used??? Also, which provider would you like to use for this? Or perhaps you have your own model or LLM for implementing image generation. I have previously practiced similar solutions using Python + Fast API + AI agent. The scheme is as follows - I send a photo or several photos from the front of the site, my backend forms a request to the AI model, the AI processes it according to the prepared prompt, and returns the result to the backend, which saves the result to storage and provides the frontend with a link to the generated photo or series of photos.

Regarding scaling, Fast API has practically unlimited possibilities for scaling, without questions about segmenting the backend into microservices, as well as for the database. As for calculations - usually calculators are used, but if done correctly, a Python parser should be implemented that will collect prices from competitors every night, generate a price table, and based on this table calculate current offers.

If interested, we can discuss it, create a more detailed technical specification, calculate the number of hours for design and implementation, and develop it.

I think such a project will cost $22 - $24 per hour. There are many nuances and calculations involved, so it won't be easy to do it well, or it might be done but it will be a mess with side effects and ambiguous results. For example - I generated girls based on several photographs, so as not to waste tokens, I first checked if the photo was of a girl, if it was a figure, if it was a face, and so on, and only then I started the generation, otherwise in the initial tests one could upload a photo of a flower and prompt to create a slender girl, everything would be generated, but it was not what was needed, as the girl was random.

Show original

Translate

Hello! I am Roman, an individual developer with 4 years of professional experience in full-stack development and automation, and I am professionally implementing an AI block for facade visualization, as I have experience working with generative models and complex interfaces. For your task, the optimal technical approach will be to use a ControlNet-based architecture (MLSD or Canny models) to preserve the geometry of the house and segmentation (SAM from Meta) for precise highlighting of facade areas, which will allow for material application without distorting windows or doors. With technical expertise in Python and experience building high-load systems, I propose using Stable Diffusion (via ComfyUI or Diffusers) to generate 2-3 design options with strict adherence to material textures. For scalability, I will lay out an architecture based on FastAPI with Celery/Redis task queues, which will allow for easy future integration of a facade area calculation and material cost calculator. I work exclusively as a freelancer through FOP, which guarantees you direct communication, legal transparency, and clean code, and you can familiarize yourself with my approach to complex technical solutions at the following links: https://3magency.co/, https://jk-solution.com.ua/, https://farfieworldwide.com/, Behance.

Show original

Translate

Hello! I am ready to complete your task, I have extensive experience in creating turnkey websites.

The price for 1 block ranges from $60 to $110 (depending on the format of the website you choose)
* includes the design development of the first block in two concepts to choose from
* includes the preparation of the layout for desktop/mobile versions
* includes 3 free iterations of revisions

I am ready to discuss your budget here and come up with the best option for you.

… Portfolio: Behance
Behance

Examples of websites:
creotivity-tm.com.ua/the-one
creotivity-tm.com.ua/oak-yard
https://creotivity-tm.com.ua/car4soul/
https://creotivity-tm.com.ua/fidelity-office/
https://creotivity-tm.com.ua/skylead/

Write to me — we will discuss the details.

Show original

Translate

Good day! We have reviewed your project, and the task is very promising. We have experience in AI integrations and can help implement a smart AI block for the website with further scaling into a full-fledged product.

What we can offer:
• User-uploaded photos of the house
• AI identification of the facade / zones of the house
• Application of facade materials and textures
• Generation of 2–3 design options
• Request form for estimation after the result
• Saving leads in CRM / Telegram / email
…
The technical stack we can build on:
• OpenAI / Gemini / Flux / SDXL
• Computer Vision / segmentation models
• Web frontend + API backend
• Cloud infrastructure with scaling capabilities

We can also immediately lay the architecture for the future application:
• Material calculation
• Cost estimation
• Client cabinet
• Ordering system

We are ready to discuss the best technical path, budget, and MVP launch.

Our website: https://benefit-it.net/
Sincerely, Benefit Studio

Show original

Translate

⭐️⭐️⭐️⭐️⭐️
Hello! Here is my Portfolio: Behance
From me:
* I will help with your specifications
* I will select the necessary style according to your preferences (2-3 free options)
* All corrections to your project are free.
* I commit to meet the deadlines.
I am ready to take on your project. Contact me to agree on the terms.

Show original

Translate

Hello! Are you planning to use ready-made AI models for image generation, or do you need a custom model tailored to your materials? I will discuss the timelines and budget more precisely in personal correspondence.

1. I will conduct an analysis and select the optimal model (for example, Stable Diffusion) for facade segmentation and texture overlay.
2. I will set up the image processing pipeline: uploading photos → segmentation → generating 2-3 design options.
3. I will design the architecture with scalability in mind (adding material calculations and cost estimation in the future).

Thank you for considering my proposal. I look forward to the opportunity to work with you!

Show original

Translate

I am among the top 10 developers in the category of "Artificial Intelligence and Machine Learning" among ~2100 specialists on the platform.
I guarantee:
- Fast and high-quality execution of the task
- Strict adherence to deadlines
- Regular communication throughout the entire process
I would be happy to discuss the details of your project in private messages.

Show original

Translate

Good day, Natalia!

The key point here is to immediately establish a scalable architecture so that in the future it can be expanded into a full-fledged platform (materials, cost calculation, orders, CRM), rather than just a one-time AI function.

Approach:
image segmentation + generation of facade options
use of diffusion models (Stable Diffusion + ControlNet) and segmentation models
separate AI service with API
task queue for load and scaling
… saving results and versions of generations

Also, for your reference regarding my development experience, I am sending cases:

1. Website of a digital marketing company
https://freelancehunt.com/showcase/work/sayt-digital-marketingovoyi-kompaniyi/1993142.html

2. Website for selling luxury cars
https://freelancehunt.com/showcase/work/sayt-dlya-prodazhu-laksheri-avto/1993140.html

3. Website about an app for women
https://freelancehunt.com/showcase/work/sayt-pro-dodatok-dlya-zhinok/1993139.html

4. Car rental website in Kyiv and Lviv
https://freelancehunt.com/showcase/work/sayt-orendi-avtomobiliv-kievi-ta/1993137.html

In the future, the system can be easily expanded into a product with material calculations, cost, and commercial applications.

I can also assist with further promotion of the project — setting up advertising and attracting traffic for testing hypotheses and scaling the product.

I can propose an optimal stack, architecture, and timeline estimate after clarifying the details.

Show original

Translate

Good day, I am interested in your project and can help with its implementation!

Recent works!

https://wall-master.artbud.pro/
https://www.cardanmash.com.ua/
http://floridagardendesigns.com/
https://advilion.com
http://axiomaplus.com.ua/
… https://maxinstal.ch/
http://otpad.com.ua/
http://spectrum.net.ua/
https://sugacards.com/

Detailed discussion, advice, preferences, evaluation in personal discussions!

Respectfully, Vasily...

Show original

Translate

Do you have a catalog of facade materials/brands for demonstration and 5–10 references of desired styles? Also, please let us know if photo visualizations without precise material calculations are sufficient at the first stage.

We are a team with JS + Python (React on the frontend, FastAPI/Flask on the backend, Postgres/Redis), 4 years commercially. We offer an MVP approach: uploading photos → facade segmentation → applying materials → 2–3 design options → application. For generation and segmentation, we will use ready-made models (for example, SDXL + ControlNet and SAM via API), a task queue for scaling, saving results, and a simple admin panel. We will create a clean UI/UX for quick material selection.

We are ready to start and assemble the MVP in 2–3 weeks. If convenient, we can schedule a short call to clarify requirements and agree on a timeline.

Show original

Translate