Python Developer / Web Scraping Specialist for collecting and classifying architectural images

Budget: 10000 UAH Deadline: 1 day

Hello!

We can connect an external specialist or team for tasks related to image collection and classification.

1. Are you considering involving an external contractor or team for these tasks?
2. What tasks and technologies need to be prioritized?

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About us

We are dZENcode – a full-cycle IT development company: from design and programming to integrations and post-release support of digital solutions. We create projects from scratch, as well as connect to existing solutions that need refinement, development, or technical support.

You can find detailed information about our services and rates on our official website: Freelancehunt

Take a look – after that we can discuss the details and agree on the next steps.

⚠️ After clarifying all the details, we will determine the scope of work, the suitable format of cooperation: task-based, outsourcing, or outstaffing – and the final cost.

With us, projects are guaranteed to reach release:
• 10+ years providing IT services;
• 90+ in-house specialists;
• 250+ public reviews since 2015;
• We support products under SLA after launch;
• We work under NDA and a contract with the company! Expand

Budget: 20000 UAH Deadline: 20 days

I will start with the first stage: I will analyze the sources, evaluate the scraping approach in Python, the storage structure, image quality, deduplication, and the classification logic of Exterior / Interior / Exterior Top View.

Your main risk right now is that you can quickly upload a large array of images but end up with duplicates, corrupted files, poor quality, and mixed categories that will then need to be cleaned manually?

The budget and deadlines will be discussed in personal correspondence after reviewing the data sources and the required volume of images.

Budget: 2000 UAH Deadline: 2 days

Good day. I have extensive experience in Web Scraping with Python. I work with large volumes of data - Pandas. Budget and deadlines - after evaluating the websites.

Budget: 2000 UAH Deadline: 2 days

Hello!

I have relevant experience specifically for this project:

— Developed commercial scrapers using Playwright + BeautifulSoup with bypassing anti-bot protection and proxy rotation
— Collected and normalized large volumes of data (27,000+ records) with subsequent storage in PostgreSQL
— Experience in uploading files in maximum quality through network request analysis
— Integrated OpenAI Vision API into production projects — can use it for image classification

Proposed approach:
1. Analyze the structure of the Source — anti-bot protection, availability of full-quality images
2. Async parser on Playwright/aiohttp for parallel collection
3. Classification by categories Exterior / Interior / Exterior Top View using OpenAI Vision API or by metadata (depending on the Budget)
4. Saving in structured folders + CSV report

Budget: from $50 per Source (final price after reviewing the Sources)
Timeline: 3–5 days per Source

I would be happy to discuss the details after reviewing the Links to the Sources! Expand

Budget: 4000 UAH Deadline: 3 days

I can do it quickly and efficiently. We need to discuss in more detail. I would be happy to collaborate.

Budget: 12000 UAH Deadline: 12 days

Hello! I have experience working with Python and can implement automated collection and uploading of images (asynchronously, for speed). For the most complex part — classification into Exterior/Interior — I suggest using [here specify your approach: for example, integration with a ready-made Computer Vision API or using a pre-trained model]. I am ready to analyze your data sources and provide an estimate on the timeline.

Budget: 8000 UAH Deadline: 7 days

Hello. I have extensive experience in developing parsers. Can I get acquainted with the websites that need to be parsed?

Budget: 2000 UAH Deadline: 3 days

Hello! Your project caught my attention. I am ready to start working and ensure high quality execution.

Budget: 5000 UAH Deadline: 15 days

I have experience specifically in this stack: Python scrapers (Scrapy / Playwright), bulk image uploading and classification via CLIP/EfficientNet.
Approach briefly:
1. Source analysis - strategy selection (static HTML / JS rendering / API)
2. Asynchronous collection with maximum quality upload
3. Auto-classification: Exterior / Interior / Exterior Top View through zero-shot or fine-tuned model
4. Structured dataset with metadata

Timeline: 2–3 weeks after start (depends on volume)
Budget: we will discuss after reviewing the sources

I look forward to the details! Expand