Product gallery generator bot for clothing store

Budget: 10000 UAH Deadline: 14 days

Good day. I am implementing a bot as a working MVP: accepting 1–4 photos, identifying the product, selecting a style, generating 6 frames, regenerating a specific frame, allowlisting, and accounting for expenses.

To start, I will compare Gemini Image and Flux on your test products and determine the best option based on quality/price. The estimated cost of the gallery is $0.3–1.2 depending on the model and the number of repetitions.

Stack: Python, Aiogram, AI API, PostgreSQL, Docker/VPS.
MVP deadline: 14 days. Cost: 10,000 UAH.

Is there an approved reference photo of the brand's face for a consistent model?

Budget: 10000 UAH Deadline: 5 days

Hello!

I develop bots for Telegram using NodeJS. I have experience with AI. Write to me, and we will discuss.

Budget: 10000 UAH Deadline: 3 days

Hello, I am ready to complete your project in the shortest possible time without any particular problems or difficulties. If you are interested in quality execution of the task - message me privately to discuss the details and we will do everything in the best way.

Budget: 10000 UAH Deadline: 2 days

Good day!
I am developing in Python!
I am ready to complete your task, I have a lot of experience with similar tasks.
Examples of similar work will be provided in private.
The cost of one image will be $0.10.
I suggest choosing Open Router as the provider - it has all available LLMs + very favorable pricing.
The bot itself will be on aiogram.
The price and deadlines are current.

Budget: 10000 UAH Deadline: 3 days

Hello, I can develop a Telegram bot that will accept 1-4 product photos and initiate AI generation of a gallery for cards on a website or marketplace. I have relevant experience in bot development, AI/LLM integrations, backend services, and image processing automation. I envision the implementation as follows: a Telegram bot in Python, a backend for task queuing and result storage, integration with an AI service for generating professional shots. Additionally, admin settings can be added for formats, number of shots, background style, and exporting finished images. After clarifying examples of the desired result, I will be able to assess the exact scope and propose an optimal architecture. github.com/onyx144

Budget: 10000 UAH Deadline: 11 days

Hello!
I carefully studied your technical specifications and the comment regarding the main priority of preserving the cut, prints, and logos "pixel-by-pixel." Unlike colleagues who offer standard text-based generation (where clothing inevitably "blurs") or preemptively state that "it won't work perfectly," I propose a strictly controlled pipeline.

How we will solve the "pixel-by-pixel" problem:
Exact fit of clothing: Instead of text prompts, we build a pipeline using Inpainting + Advanced ControlNet (Canny / Depth / SoftEdge) based on Flux.1. This means that the neural network takes the geometry, texture, and seams from your actual product photo and transfers them to the generated model, preserving the original proportions of the clothing without any distortions.
Consistent brand face: The face is fixed through LoRA / InstantID. The model will be guaranteed to be recognizable across all 6 frames (including dynamics) and between different product cards.
Savings and automation: No manual input. GPT-4o Vision instantly scans the photo, determines the type of item (e.g., "oversized jacket, men's"), and generates the correct technical prompt for Flux. The cost of this stage is fractions of a cent.

Technical implementation of the bot:
Stack: Python (aiogram 3) + PostgreSQL + Redis (for session caching and individual frame regeneration without restarting the entire gallery).
Cost control: The bot calculates the exact cost of generation via API (Fal.ai or Replicate) before pressing the "Start" button and maintains transparent statistics for managers. Access is strictly by allowlist.
Deployment: I will deliver the project in a Docker container turnkey on your VPS, setting up logging and auto-restart 24/7.
Financial parameters and deadlines: The cost of 1 gallery (6 frames): from $0.15 to $0.35 (about 6–15 UAH) due to prompt optimization and the selection of fast API endpoints.

My budget: 10,000.
Deadline: 11 days.

The pipeline on Flux.1 + ControlNet is the only way to achieve a commercial result that won't be embarrassing in front of buyers.
I am ready to start working soon.
Let's discuss the details in private messages! Expand

Budget: 10000 UAH Deadline: 2 days

I am implementing a Telegram bot in Python (aiogram) with AI integration for generating professional clothing photos. I will select the optimal AI service (Gemini/DALL·E/Flux) focusing on quality and cost, set up the generation of galleries with consistent models and styles, and ensure security and monitoring.
Contact me, and we can discuss everything in detail, and I can start working immediately.

Portfolio: Freelancehunt
Reviews: Freelancehunt

Budget: 12000 UAH Deadline: 14 days

Hello. My name is Volodymyr, I am a Python and Node.js developer, as well as the founder of the engineering agency Vaysed. I have thoroughly reviewed your task regarding the development of a Telegram bot for AI generation of professional product photos. I understand that the key challenge here is to maintain the original cut of the clothing and the consistency of the model's face in different poses and styles.

I would like to note immediately regarding the choice of artificial intelligence. Standard models like DALL-E or regular Midjourney are not suitable for this task, as they inevitably alter product details during generation. For accurate transfer of your clothing onto a person while preserving the brand's signature look, I strongly recommend using a pipeline based on Flux or Stable Diffusion XL with ControlNet and IP-Adapter technologies. We will be able to connect these models through reliable cloud APIs, such as Replicate or Fal.ai. For preliminary automatic recognition of clothing categories and prompt optimization, we will use GPT-4o-mini, which operates instantly and very cheaply.

The bot itself will be developed in Python using the aiogram 3 framework. We will implement a flexible interface where, after uploading a photo, the manager can choose a style, see the estimated API cost, and start the process. If one of the 6 frames turns out unsuccessful, it can be regenerated separately thanks to session context preservation in Redis. All team access limits and expense statistics will be securely stored in an SQLite or PostgreSQL database. The final code will be packaged in a Docker container for uninterrupted operation 24/7 on your VPS.

I have deep practical experience in integrating generative AI and developing complex Telegram infrastructures. In the Lumos project, I developed complex architectures using neural networks, and while creating PAYBACK CARTEL, I successfully set up a flexible billing and access management system.

Regarding the financial aspect. The estimated cost of generating one gallery with 6 high-quality frames through the Fal.ai or Replicate API will range from $0.15 to $0.40. The cost of developing the entire turnkey solution will approximately be $10,000 to $12,000, and the implementation period will take about 10-14 days, considering prompt setup and testing of the clothing preservation pipeline.

You can view my portfolio at this link: Freelancehunt

I suggest moving to personal messages to analyze test photos of your products and discuss the brand's stylistics in more detail. Expand

Budget: 10000 UAH Deadline: 14 days

The manager uploads a photo on a hanger — the bot returns a ready gallery with 6 frames featuring a consistent model, without manual description.

For the stack: I recommend Flux (via Replicate or fal.ai) for generation — it has the best quality for clothing and model consistency control through IP-Adapter or LoRA on the brand's face. DALL-E 3 is more expensive and maintains style between frames worse. The estimated cost of the gallery is 15-40 UAH depending on the provider.

Architecture: aiogram 3 + webhook on VPS, category/cut recognition through GPT-4o Vision (photo analysis without manual input), frame generation in parallel through queues (asyncio), allowlist + daily limits in SQLite, expense tracking per user with statistics. Each frame is stored separately — regenerating one does not affect the others.

Is there already an approved image of the "brand's face" (a specific person or reference photo), or does the model need to be selected/trained from scratch?

Budget: 14000 UAH Deadline: 16 days

Good day, Stanislav.
In this project, the main difficulty is not the Telegram bot interface, but preserving the actual appearance of the product: prints, cuts, colors, and small details, as well as maintaining a stable appearance of the model throughout the gallery. Regular generation based solely on a text prompt is not reliable enough for this.
I propose to build a reference-based pipeline: the bot analyzes 1–4 photos, determines the category and characteristics of the product, and then creates separate controllable frames with the model's image attached. Each frame will have its own status, allowing it to be regenerated or have its style changed without recreating the entire gallery.
I will implement photo acceptance, automatic product analysis, six types of frames, style presets, numbered JPG 4:5, allowlist for teams, daily limits, preliminary cost estimation, usage statistics, a generation queue, and launching via Docker on VPS.
At the first stage, I suggest testing Gemini and GPT Image on 5–10 of your products and agreeing on quality criteria. After that, we will finalize the optimal model, prompts, and acceptable cost for the gallery.
I just need to clarify: do you require the model's face to be literally the same in all future galleries, or is a stable brand type sufficient? This significantly affects the technology and cost of generation.

Budget: 10000 UAH Deadline: 7 days

Good day, Stanislav!

The development of a Telegram bot for automating the generation of product galleries is an interesting task that requires a deep understanding of AI and the specifics of your clothing store.

Your goal is to simplify the process of creating professional product images, which will significantly enhance sales efficiency. I have experience in developing bots and AI tools, which will allow me to meet your requirements.

To create an effective strategy, we first need to study the specifics of your product and technical requirements. I propose the following action plan:
1. I will familiarize myself with the provided product photos and your stylistic preferences.
2. We will discuss the specifics of product recognition and gallery generation.
3. I will develop a preliminary work plan and estimate the cost.

The preliminary cost for developing such a bot starts at $2000, with timelines ranging from 2 to 4 months depending on complexity.

In my profile, you can review examples of my work that confirm my skills in bot development and AI solutions: Freelancehunt.

I suggest we discuss the project details in private messages to understand your needs and develop an optimal action plan. Expand

Budget: 25000 UAH Deadline: 14 days

I understand the task — a bot is needed that transforms raw product photos into a professional gallery with various shot types through AI. The key challenge: a consistent model (one face in all shots) and product classification without manual description. Solution: 1) computer vision (OpenCV / TensorFlow) to determine clothing category; 2) generation via Stable Diffusion API with a fine-tuned model for the brand; 3) Telegram bot in Python (aiogram) with a task queue; 4) post-processing (cropping, exporting JPG 4:5). I have experience creating Telegram bots with automation: I developed a bot for managing Twitter accounts with parsing and analytics. (https://freelancehunt.com/showcase/work/programmnoe-obespechenie-dlya-twitter-avtomatizirovannoe-upravlenie/1874481.html) What AI models do you plan to use? Are there ready references for styles (streetwear, casual)?

Price: 25000 UAH
Deadline: 14 days

Budget: 9500 UAH Deadline: 14 days

Stanislav, the most expensive part of this bot is not the development, but the image generation. Six frames in the gallery through DALL·E already cost about $0.20 per item, and if you regenerate a single frame, the amount becomes too high for daily flow. I suggest building on Flux.1 — the quality of photo-realism there is better, and the price per frame is significantly lower, which is critical for product shots of clothing.

⚙️ Regarding the architecture of the bot:
— Generates 6 frames of your structure: model from the front/back, dynamic, flat, detail, ghost mannequin
— Access via allowlist with daily limits + display of estimated generation cost before starting
— Regeneration of a single frame without restarting the entire series

The main risk is the consistency of the brand's face across different galleries. This is the weakest point in all models: the face "floats" from frame to frame. I stabilize the face using a reference photo + style identifiers, so the same model remains recognizable. It won't always work perfectly — but there are currently no tools for 100% fixation available from any provider.

I work through Safe. First, I gather the core: taking photos + generating two test frames of your products — you will see the real result, then we move on to the full gallery and deploy on VPS.

Stanislav, one question regarding the essence: should the brand's face be a single fixed one for the entire store, or do you plan to have several models (for example, men's and women's lines)? This will affect the architecture. Expand

Budget: 10000 UAH Deadline: 14 days

Stanislav, I see you need a tool for content automation that will take on the routine work of preparing photos for product cards. The main challenge here is to maintain the identity of the model and the consistency of lighting for all frames in the gallery.

I am implementing a bot that, through integration with image generation models like Stable Diffusion (via LoRA for faces) and composition control through ControlNet, will produce a ready set of frames. This will allow you to get results immediately in the desired aspect ratio and with the correct zoning, without extra effort from the manager.

What method are you currently using to train the model for the face, or do you plan to use ready-made character presets for your brand? How many product items per day do you plan to process through the bot to calculate the optimal servers for generation?