Satisfied with the collaboration. The work was done qualitatively, the performer took into account all comments and remarks, was open to revisions, and proposed good solutions during the process. Thank you for the responsible approach.
41
0
Budget: 15000 UAH Deadline: 10 days
I have successful experience in developing automated data collection and processing systems for large datasets. I understand that for architectural projects, it is critically important to maintain high image resolution and ensure accurate classification (Exterior, Interior, Top View).
My technical approach:
Data Collection:
I will develop parsers based on Playwright or Selenium (depending on the complexity of the sources) that allow downloading original files in the highest available quality, bypassing bot protection.
Classification (AI-driven):
To avoid errors in manual sorting, I will use pre-trained computer vision models (such as ResNet or EfficientNet via PyTorch) configured to recognize architectural types. This will allow for the automatic sorting of thousands of images into categories (Exterior, Interior, Exterior Top View) with high accuracy.
Structuring:
Images will be automatically distributed into appropriate folders, and their metadata (if needed) will be saved in a structured CSV or JSON file.
Delivery:
The completed dataset will be provided via Google Drive or another cloud storage as a structured archive.
Estimated timelines and costs:
Stage 1 (Source analysis and pilot collection): 2–3 days.
Stage 2 (Classifier setup and full collection): 7–10 days.
Cost: 15,000 – 25,000 UAH (depending on the number of sources and the total volume of images, which we will determine in the first stage).
My experience:
I have previously worked on projects for automating content collection for e-commerce and architectural platforms, where it was necessary to maintain quality and file hierarchy.
I am ready to conduct a detailed analysis of the sources and provide a workload estimate after you send the links to the resources. Would it be convenient for you to discuss the details in private messages?
2
1
Budget: 4000 UAH Deadline: 12 days
Hello!
I have relevant experience in developing automated data collection and processing systems, particularly using computer vision for image classification. I have already implemented similar pipelines — from parsing to structured result transmission.
**Proposed approach:**
• Image collection — Playwright/Scrapy with support for JavaScript sites (Archdaily, Dezeen, and other architectural sources), downloading in maximum quality, deduplication through perceptual hashing
• Classification — CLIP model (OpenAI) for categorizing into Exterior / Interior / Exterior Top View with a confidence threshold to filter out doubtful cases
• Structuring — folders by categories + CSV/JSON with metadata (source, URL, date, category, confidence score)
• Transmission — automatic upload to Google Drive via the official API
**Timeline:** 8–12 working days depending on the number of images and sources
**Cost:** $200–350 — final figure after clarifying the scope
In the first stage, I am ready to conduct a free analysis of the sources and provide an accurate estimate with an example of the classifier's work.
I am open to discussing the details.
6
0
Budget: 700 UAH Deadline: 1 day
There are very few details to provide you with a technical approach, timelines, or cost estimates. Can you provide more details?
14
0
Budget: 10000 UAH Deadline: 1 day
Hello! I can implement it. Please message me privately to discuss all the details. I would be happy to collaborate!
0
0
Budget: 9000 UAH Deadline: 5 days
Hello! The task is completely clear, and the workload is substantial. I have experience in developing asynchronous parsers in Python, optimized for downloading large arrays of media files without quality loss and bypassing limits of web sources.
My proposed technical approach:
1. Analysis and collection: I will write a Python script (Playwright / Scrapy + aiohttp) that will asynchronously and in multiple threads download images in maximum resolution.
2. Classification (Exterior/Interior/Top View): I will implement a combined approach. The script will read metadata/tags from the primary source, and for unstructured photos, we will connect a lightweight pre-trained computer vision model (based on PyTorch / HuggingFace) that automatically and accurately sorts them into the required folders.
3. Cataloging: The data will be clearly structured, and I will upload the results to your Google Drive.
I am ready to conduct a free analysis of your sources and propose the best solution. Feel free to message me!
1
1
Budget: 27000 UAH Deadline: 3 days
Good day. I am ready to complete this project as I have extensive experience in app development.
15
0
Budget: 6500 UAH Deadline: 6 days
Hello, Olga!
The task is clear: we need not just a parser, but a full-fledged pipeline — collection in maximum quality, AI classification into Exterior / Interior / Exterior Top View, and a structured dataset with metadata.
Approach:
— Collection: Playwright with bypassing anti-bot protection, downloading originals (not previews), deduplication
— Classification: CLIP/Vision model with confidence score — so you can see not only the category but also the model's confidence for each image
— Result: structured folders + CSV with metadata (source, URL, category, date)
— Transfer via Google Drive
The first step is to analyze the sources: I will assess the volume, structure of the sites, and the presence of protection. After that, I will provide exact deadlines and final costs.
Approximately: 6000-7000 UAH, 5-7 days after the start.
I have relevant work examples - ready to show. When is it convenient to discuss the details?
10
0
Budget: 1000 UAH Deadline: 1 day
Good day.
I have experience in automating the collection and processing of data from open web sources, including image parsing, filtering, classification, and structuring.
To implement the project, I plan to first analyze the available sources, assess the quality and completeness of the data, after which I will build an automated process for collecting images in the highest available quality, followed by classification into the categories of Exterior, Interior, and Exterior Top View.
The result will be delivered in the form of a structured database with a clear cataloging system and a convenient method of transfer.
I suggest discussing the implementation details, timelines, and costs in private messages.
I look forward to collaborating.
4
0
Budget: 1000 UAH Deadline: 1 day
Hello!
I have extensive experience in developing solutions for parsing and processing data (various sources, protection against blocking, automation). I am ready to complete the assigned task in the shortest possible time.
I suggest discussing the details in private messages.
41
4
Budget: 1000 UAH Deadline: 3 days
Good evening!
I have experience in web scraping and working with large datasets, including APIs and Google Drive. Proposed technical approach: Python (BeautifulSoup/Scrapy, Pillow, scikit-learn/TensorFlow Lite), cloud storage. Estimated timeline: [please specify the timeframe, for example, 2-4 weeks].
12
0
Budget: 10000 UAH Deadline: 10 days
Olga, hello!
I can do the collection + upload in maximum quality + classification of architectural images into 3 categories: Exterior / Interior / Exterior Top View - with a proper folder structure and a report so that it can be used as a dataset.
Approach (briefly):
1) Source analysis
2) Collection. I will upload the highest available quality, with a log of errors and retries
3) Deduplication
4) Classification
5) Export
To give you an accurate estimate on timelines and costs, please send 3-5 examples of sources/websites you want to parse, and an estimate of the volume (for example: "need 20k/50k/100k images")
74
1
Budget: 4000 UAH Deadline: 4 days
Good day. I have extensive experience in parsing. I can do it quickly and efficiently. I will create a convenient structure. We need to discuss in more detail. I would be happy to collaborate.
38
2
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. Storage in structured folders + CSV report
Budget: from $50 per source (final price after reviewing the sources)
Timeline: 3-5 days per source
Ready to discuss details after receiving links to the sources!
28
0
Budget: 1000 UAH Deadline: 2 days
Ready to complete, write to discuss the details...................
Budget: 7999 UAH Deadline: 3 days
Good day! I can perform automated collection and structuring of architectural images (Exterior / Interior / Top View), classification, and storage in a database + cloud storage.
18
3
Budget: 1000 UAH Deadline: 1 day
Hello! I have extensive experience in automated data collection and media content classification. Since the project description does not specify particular websites, I need to see the data sources first for an accurate assessment of costs and timelines. I am ready to discuss the details in the chat and suggest an optimal approach.
5
0
Budget: 2000 UAH Deadline: 1 day
Good day!
Collection and AI classification of architectural images is our specialized area, and the task is fully understood.
Proposed approach:
Source analysis: we will assess the volume, the quality of the originals available, the presence of pagination and anti-bot measures, and choose the optimal collection scheme.
Collection: a parser with proxies and throttling, downloading files in the highest available quality (originals only, not previews).
Classification Exterior / Interior / Exterior Top View — automatically through a vision model, with accuracy verification on a sample before the full run.
Cataloging: clear folder structure + metadata (source, category, resolution), transfer via Google Drive or another convenient method for you.
We constantly work with web source parsing and image processing, so we will approach the task quickly and accurately.
Details, volume, and cost will be discussed in private. Write to us.
9
1
Budget: 2000 UAH Deadline: 3 days
Hello! I have reviewed your project and am ready to start working. I can guarantee excellent results in a short time.
123
0
Budget: 7499 UAH Deadline: 15 days
I have experience specifically in this stack: Python scrapers (Scrapy / Playwright), bulk image uploading and classification using 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 using zero-shot or fine-tuned model
4. Structured dataset with metadata
Timeline: 2–3 weeks after start (depends on volume)
Budget: to be discussed after reviewing sources.
77
1
Budget: 2000 UAH Deadline: 3 days
Good day. I have extensive experience in Python parsing. I will upload the images in the highest available quality. I will perform the classification using OpenAI. The deadlines and cost will be determined after evaluating the websites.
0
0
Budget: 2999 UAH Deadline: 7 days
Good day! I am interested in your project. I have experience in web scraping (Python, BeautifulSoup/Selenium/Scrapy) and data collection automation. I have also worked with uploading and processing media files.
Proposed technical approach:
I suggest the following algorithm:
1. Analyze the sources you provided or search for new open sources (architectural websites, stock sites).
2. Write a script to crawl pages and download original images.
3. Classification: can be implemented based on metadata/tags from donor sites, or (if there are no tags) connect a basic computer vision model (for example, via OpenAI API or a local neural network) for sorting into Exterior, Interior, Exterior Top View.
4. Save into structured folders and upload the archive to Google Drive.
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