AI Textile Design Generation Tool Using Computer Vision & Generative AI

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@shadabkhan92

As an AI developer, I understand the need for your textile generation tool to go beyond prototype and truly integrate into your existing workflows. My experience in building agentic AI that operates inside ERP, LLM integrations, RAG pipelines, and more is what sets me apart. I believe this aligns perfectly with your project as you're looking for an AI system not just as a standalone tool but something that works autonomously within your groundwork. I've worked extensively in Python, MongoDB and have hands-on expertise in Generative AI - well within the project's preferred tech stack. My work spans boundaries, intelligently fusing AI with hardware and embedding agents into enterprise software. This, I believe, aligns uniquely with your computer vision & generative AI-driven platform which transforms multiple types of textile-related images into production-ready designs. Let my proven skills in image segmentation teamed with my experience deploying AI applications help design an efficient system for you. For example, my previous projects involving powerful data processing like layer separation and background/garment removal provide me with a tactical edge for your needs. And yes, we can discuss your thoughts on a paid prototype milestone before committing to full development. Let's realize this revolutionary textile design generation tool together!

@jaroslavcaprata

Hello, I have strong experience building AI-powered image processing and generative design systems using Python, OpenCV, PyTorch, Stable Diffusion, FastAPI, and React-based interfaces. I can develop a textile AI platform capable of fabric extraction, segmentation, perspective correction, seamless pattern generation, editable layer workflows, watermark handling, and high-resolution export pipelines including PSD/TIFF/PNG outputs. I also have experience deploying GPU-intensive AI applications on AWS with scalable full-stack architecture and modular training/inference workflows.

@kshubham102

Hi, I’ve worked on long-running Playwright/Python systems where the real challenge is not building the automation once — it’s keeping unstable third-party vendor workflows reliable in production. Your architecture already sounds solid, so my focus would be: Stabilizing fragile vendor automations Improving retry/recovery/session management Reducing breakage from DOM/UI changes Debugging intermittent Playwright failures Optimizing concurrent browser execution and worker reliability Key areas I can help with: Robust selector strategies (fallback chains, semantic locators, iframe handling) Session persistence & auth recovery Async Playwright + queue worker optimization Auto-retry/circuit-breaker patterns Vendor workflow observability & logging Docker/Linux production debugging Handling JS-heavy and legacy iframe portals Technical Stack: Python + Playwright Async task orchestration Dockerized multi-service environments Background workers/queue systems Automation monitoring & resiliency tooling What I’d deliver: Stabilized vendor modules Refactored automation reliability layer Improved logging/debugging visibility Documentation for future maintenance Production-tested fixes with minimal disruption I’m comfortable stepping directly into existing production systems and improving reliability without rewriting the entire platform. Shubham Sharma

@usamaansari786

What you’re building is not a simple “image generation tool” but a full AI textile processing pipeline where the hardest part is maintaining production-grade pattern accuracy while combining segmentation, reconstruction, seamless tiling, and editable layer logic into one scalable workflow. I specialize in AI-powered full stack systems involving computer vision pipelines, image reconstruction workflows, and GPU-backed processing architectures where performance and output consistency matter just as much as the model itself. For a platform like this, I’d approach the architecture in modular stages rather than trying to overfit one model into every task. Typically the cleanest structure is: • Segmentation + garment/background isolation • Perspective/fold normalization using CV preprocessing • Pattern extraction + seamless repeat generation • Layer assignment/edit workflow • Generative enhancement/upscaling pipeline • Production export engine (PSD/TIFF/CMYK) I’ve a couple of quick questions regarding your setup Q) Do you already have sample datasets/examples of expected textile outputs so the reconstruction quality target can be benchmarked early Q) For layered PSD export do you expect true editable semantic layers (pattern/background/objects) or primarily region-separated production layers Let’s have a 10 minute discovery call. I. Best Usama F

@mubashir021

Transforming textile design with cutting-edge AI technology is my passion, and I am excited about the opportunity to create an AI-powered textile fabric generation and layer separation platform. With extensive experience in computer vision and generative AI, I can develop a solution that processes a variety of textile-related images to produce high-resolution designs with editable layers. My approach involves leveraging Python, OpenCV, and frameworks like PyTorch or TensorFlow to ensure robust image processing capabilities. I will implement features such as garment/background removal, layer separation, and watermark removal, while providing a user-friendly editing system. Additionally, I will ensure that the platform supports multiple export formats, including PSD and TIFF, to meet industry standards. I have successfully completed similar projects in the past and can share my portfolio showcasing relevant work. I understand the importance of clear communication and regular updates throughout the project, and I am committed to delivering a high-quality product on time. Let's discuss your vision further and how I can help bring it to life.

@zaheerdiedericks

I’m a great match for this task. Your need for a clean, professional, and user-friendly platform that seamlessly processes and generates high-resolution textile designs with editable layer separation aligns perfectly with my expertise. I specialize in full-stack AI development with strong skills in Python, OpenCV, PyTorch, and React, and have delivered AI-powered image processing solutions. While I am new to freelancer, I have tons of experience and have done other projects off site involving computer vision and generative AI, ensuring automated, integrated workflows that meet production standards. How do you envision the layer editing interface balancing complexity with ease of use? I would love to chat more about your project! Regards, Zaheer Diedericks

@hxptechnologies

Hi there ?, I’ve carefully reviewed your project titled "AI Textile Design Generation Tool Using Computer Vision & Generative AI" and can confidently deliver a production-ready solution with clean UI and smooth performance. Let's discuss your specific requirements — I can start right away!

@ahtishamulhaque1

With over a decade of expertise in full-stack development and an eye for scalable architecture, I'm confident that I can deliver your AI Textile Design Generation Tool with exceptional value. My proficiency in Python and MongoDB is the right set of skills your project demands, bolstered by my extensive experience in Computer Vision, Image Segmentation, and Generative AI. I have successfully engineered various AI-powered applications, particularly in SaaS platforms. It would be worth mentioning my work with n8n workflow automation which aligns well with your requirement for an Editable Layer Workflow feature. Ensuring high-performance and clean architecture are at the heart of my deliveries, precisely what you need for an AI tool of this scale. Moreover, I have deployed numerous production-grade systems using AWS/GPU instances akin to your hardware setup. A fitting example was my utilization of FastAPI/Flask to build a responsive backend system that impressed clients with its quick turnaround time and reliable performance. I am inclined towards building something meaningful than just trading code lines - this drives me to create systems that automate processes, reduce manual work, and increase business efficiency. Participating in a paid prototype milestone sets the right pace to build trust and ascertain a seamless collaboration experience throughout the project lifecycle. I look forward to transforming your vision into reality using the power of AI.

@michaeltorresos9

Hello, how are you? I am very happy to bid on this really interesting project. ? I have strong experience building AI-powered computer vision platforms using Python, OpenCV, PyTorch, Stable Diffusion, FastAPI, and React/Next.js. I can develop a scalable textile-generation workflow with segmentation, layer separation, seamless tiling, watermark removal, and production-ready exports including PSD/TIFF. I’m also experienced with GPU deployment and AI SaaS architecture, making me well-suited for your prototype and long-term development goals. Best regards.

@Br1je5h

Worked on generative AI image processors at OpenAI scaling visual data models. Your textile extraction challenge is exactly that architecture: layer-separated, production-ready outputs from complex input. Built a retail mockup pipeline for FolioDynamix processing 1000+ product images/day with PyTorch segmentation & Stable Diffusion—achieving 94% accuracy on fabric separation. Approach: Week 1 - Garment removal + fold correction (OpenCV). Week 2 - Layer decomposition (PyTorch). Week 3 - Generative refinement (Stable Diffusion API) + exports. Week 4 - React UI + AWS Lambda. Risk reversal: Delivering paid prototype before full commitment. Clarification: What's priority—layer accuracy or time-to-market? — Brijesh, Sonraj Labs

@semyi

I would treat this as a paid prototype first, not overpromise the whole production SaaS in one step. For the first milestone I can build a working Python/OpenCV + lightweight AI pipeline that takes sample fabric/garment/swatch images, removes background where feasible, normalizes perspective/crop, produces repeatable seamless-tile candidates, and exports PNG plus a documented layer/mask handoff. I can also include a small FastAPI/React preview UI if you want the workflow visible in-browser. The important early deliverable is a measurable proof: sample inputs, generated outputs, reproducible scripts, known limitations for watermark/layer separation, and a practical plan for the heavier PSD/CMYK/GPU phase. This keeps cost controlled and lets you decide whether to continue into full PyTorch/Stable Diffusion deployment after seeing real textile outputs.