Train vision, OCR and document AI models on real-world images that contain real text. We collect photographs and scans of infographics, handwritten notes, billboards, shop fronts and numeric text, in any language and script your model needs to read.
Every image is captured to your brief, quality-checked and delivered with structured metadata, ready for annotation and training.
Image data collection is the process of capturing and curating photographs and scans that a machine learning model learns from. For text-in-image tasks such as OCR, scene text recognition and document understanding, the images need to show text as it really appears: on crumpled paper, curved shop signs, glossy posters and weathered billboards.
We plan the capture around your target languages, scripts, lighting and camera conditions, so the dataset covers the variety your model will meet in production.
Real-world images with readable text in many languages
Varied angles, lighting, fonts, handwriting styles and backgrounds
Metadata that makes the data easy to filter, annotate and audit
Models that read text in images only perform as well as the variety of images they were trained on.
Helps OCR and scene text models read text under blur, glare, odd angles and busy backgrounds.
Supports models that must read many languages and scripts, including right-to-left and mixed-script text.
Captures the lighting, distance, damage and clutter that clean scans and synthetic images miss.
Teaches models to interpret layouts, charts, forms and infographics, not only isolated words.
Process
We handle the complete pipeline from planning to delivery:
Types
Text-rich image categories for OCR, scene understanding and multimodal AI
Collect posters, charts, diagrams and data graphics in many languages and layouts for document and chart understanding models.
Bar, line and pie chart images
Posters, flyers and visual explainers
Diagrams, maps and process graphics
Mixed text-and-graphic layouts
Chart and layout understanding models
Gather handwriting from many writers, in many languages and scripts, on paper types and in styles that match real use.
Notes, forms and letters
Cursive, print and mixed handwriting
Different pens, paper and ink colors
Multi-script and multi-writer coverage
Handwriting recognition training
Capture large-format advertising and public signage at different distances, angles and times of day.
Roadside and building billboards
Street, transit and directional signs
Day, night and weather variation
Partial occlusion and glare cases
Scene text detection and recognition
Photograph storefronts and shop signs across markets, with local languages, fonts, hand-painted boards and mixed-script names.
Street-level storefront images
Signboards, hoardings and menu boards
Local fonts and hand-painted signs
Business category and region coverage
Local search and mapping AI
Collect images where digits carry the meaning, including different numeral systems used around the world.
Price tags, labels and receipts
Meter, dial and display readings
Scoreboards, house and room numbers
Western, Arabic-Indic and Devanagari digits
Digit and numeric OCR training
Languages
Tell us the languages your model must read. We build the collection around them, including right-to-left and mixed-script text. These are examples, not a limit.
English, Spanish, French, German, Portuguese, Italian, Turkish, Indonesian and more
Hindi, Marathi, Nepali, Bengali, Tamil, Telugu, Kannada, Malayalam, Gujarati, Punjabi
Arabic, Urdu, Persian and other right-to-left languages
Simplified and Traditional Chinese, Japanese, Korean
Russian, Ukrainian, Bulgarian, Serbian, Greek
Thai, Vietnamese, Khmer, Burmese, Lao
Hebrew, Amharic, Georgian, Armenian, Sinhala and more on request
Bilingual signs, transliterated names and different numeral systems in the same image
Our Advantage
Image datasets built around your languages, scenes and accuracy targets, with quality checks at every step.
Collect text-rich images across regions, languages and scripts.
Every batch is reviewed for sharpness, legibility and the right content.
Authentic photos from streets, shops, homes and workplaces, not studio setups.
Collection plans tailored to your model, domain and delivery format.
Our image datasets help teams train OCR, document AI and multimodal models that read the world as it looks. For spoken-language data see our audio data collection, and for written text see text data collection.
Infographics, charts and posters
Handwritten notes and documents
Billboards and outdoor signage
Shop fronts and storefront signs
Numbers and numeric text in different numeral systems
Multilingual images with metadata and optional annotations
Synthetic and scraped images are quick to get. Purpose-collected images give you control over language, content and rights.
| Feature | Purpose-Collected Images | Scraped or Synthetic Images |
|---|---|---|
| Language & Script Control |
|
Depends on the source |
| Real-World Conditions |
|
Often limited or staged |
| Rights & Consent |
|
Often unclear |
| Edge Cases |
|
Hard to guarantee |
| Speed & Cost |
|
Faster, lower cost |
We match the capture device to the content, from street-level signs to handwritten pages.
Everyday devices that match how most real-world images are taken.
Higher resolution for large signage and detailed documents.
Flat, even scans of handwritten pages, forms and printed material.
Street-level shots of shop fronts and billboards from varied distances.
File formats and folder structure are agreed with your team before collection starts.
Full-resolution photos and scans, named and organized consistently.
Optional language tags, text transcriptions and region annotations.
Language, script, category, device and capture details for every image.
A summary of quality checks and acceptance results for each delivery.
Share your languages, image types and volume. We will propose a collection plan, quality criteria and delivery format.
Answers to common questions about collecting multilingual image datasets for AI training.
It is the planned capture and curation of photographs and scans used to train computer vision, OCR and multimodal models. For text-in-image tasks, the images are collected to show real text in real conditions, in the languages and scripts your model must read.
Infographics and charts, handwritten notes and documents, billboards and outdoor signage, shop fronts and storefront signs, and images of numbers and numeric text such as price tags, meters and displays. Other text-rich categories can be scoped on request.
We collect in the languages your project needs, including Latin, Devanagari and other Indic scripts, Arabic script, Chinese, Japanese and Korean, Cyrillic, Southeast Asian scripts and mixed-script images. Tell us your target languages and we will confirm the collection plan for each.
Contributors write on paper using prompts or free text that match your use case, then photograph or scan the pages. We vary writers, pens, paper and writing styles, and review each page for legibility before delivery.
Collection guidelines tell contributors what not to capture, and we can exclude or blur faces and other personal details when your project requires it. Contributors participate with consent, and rights terms are agreed before collection starts.
Yes, if you need it. Images can be passed to our data annotation services for text-region boxes, transcription, language tagging and review, or delivered as raw images if you annotate in-house.
It depends on the model, the number of languages and how varied the images must be. A focused pilot is a practical way to measure results before scaling, so we usually start by agreeing a sample scope and acceptance criteria.
Use the Talk to Expert button to share your image types, languages, volume and file format needs. We will reply with a proposed plan and can discuss a small sample so you can test the data before committing.
Teams using Image Data Collection often combine it with these services to build a complete training dataset.
Custom text datasets for NLP, chatbots and language-model training.
Learn more →
Speech and sound recordings across languages, accents and environments.
Learn more →
Third-person video recorded from external viewpoints for scene-level and activity understanding.
Learn more →
First-person footage that shows tasks and interactions from the worker's own point of view.
Learn more →
See how image and video data is collected and prepared for computer vision models.
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An overview of the data types, workflows and quality steps behind AI training datasets.
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Get Started Today
Tell us the languages and image types your model needs to read. We will build a collection plan and a sample to match.
Specified by you