Optical Character Recognition
AI Training Data For OCR
Optimize data digitization with high-quality Optical Character Recognition (OCR) training data to build intelligent ML models.
Reduce the learning curve of AI models with reliable OCR Training Dataset
Deciphering and digitizing scanned images of text is a challenge for many businesses developing reliable AI and Deep Learning models. With Optical Character Recognition, a specialized process, it is possible to search, index, extract and optimize data into machine-readable format. This scanned document dataset is being used to extract information from handwritten documents, invoices, bills, receipts, travel tickets, passports, medical labels, street signs and more. To develop reliable and optimized models, it should be trained on OCR datasets that have extracted data from thousands of scanned documents.
How our expertise in developing accurate OCR training datasets works in YOUR favor?
• We provide client-specific OCR training dataset solutions that help customers develop optimized AI models.
• Our capabilities extend to offering scanned PDF datasets and covering different letter sizes, fonts and symbols from documents.
• We combine the precision of technology & human experience to provide a scalable, reliable and affordable solution for clients.
OCR Use Cases
Freestyle handwritten text datasets to develop powerful ML models.
Collect / Source thousands of high-quality handwritten datasets in hundreds of languages and dialects to train machine learning (ML) and deep learning (DL) models. We can also help in extracting text within an image.
Handwritten Forms Dataset
Freestyle Handwritten Text Paragraphs Datasets
Receipt/Invoice
Datasets consisting of invoice/ receipt where several items were purchased e.g., coffee shop, Restaurant bills, Grocery, Online shopping, Toll receipts, Airport cloakroom, Lounge, Fuel bill, Bar invoice, internet bills, shopping bills, taxi receipts, restaurant bills, etc. collected from different region and in different languages as required for the ML model. Save significant time and money by transcribing key data from invoices and receipts effectively and accurately.
Receipt Data Collection: Data Extraction of Receipts with OCR
Invoice Data Collection: Transcribe reliable data with Scanned Invoice Datasets
Tickets: Flight tickets, Taxi tickets, Parking ticket, Train tickets, Movie Ticket Processing with OCR
Transcription of Multi-category Scanned Documents: Newsletters, Resume, Forms with checkbox, Multi-document in a single image, User manual, Tax forms etc.
Multilingual Document
Multilingual handwritten data collection services for pattern recognition, computer vision, and other machine learning solutions to train Optical Character Recognition models.
OCR – Multilingual document 1
OCR – Multilingual document 2
Scene Data Collection
Medicine bottle with labels, English Street/Road scene with car license plate, English Street/Road scene with instruction/info board etc.
Transcribe Medical Labels or Drug Labels with OCR
Number Plate Recognition using OCR
Detecting Street/Road & Extract Information Street Board data with OCR
OCR Datasets
Text & Image Optical Character Recognition (OCR) Datasets to get you going in order to train real-world applications. Can’t find the data you need? Contact Us Today.
Barcode Scanning Video Dataset
5k videos of barcodes with a duration of 30-40 sec from multiple geographies
- Use Case: Object Recognition Model
- Format: Videos
- Volume: 5,000+
- Annotation: No
Invoices, PO, Receipts Image Dataset
15.9k images of receipts, invoices, purchase orders in 5 languages i.e. English, French, Spanish, Italian & Dutch
- Use Case: Doc. Recognition Model
- Format: Images
- Volume: 15,900+
- Annotation: No
German & UK Invoice Image Dataset
Delivered 45k images of German & UK Invoices
- Use Case: Invoice Recog. Model
- Format: Images
- Volume: 45,000+
- Annotation: No
Vehicle License Plate Dataset
3.5k images of Vehicle License Plates from different angles
- Use Case: No. Plate Recognition
- Format: Images
- Volume: 3,500+
- Annotation: No
Handwritten Document Image Dataset
Collected and annotated 90K documents in English, French, Spanish, German, Italian, Portuguese and Korean
- Use Case: OCR Model
- Format: Images
- Volume: 90,000+
- Annotation: Yes
Document Dataset for OCR
23.5k docs in Japanese, Russian & Korean languages from Signs, Storefronts, Bottles, Documents, Posters, Flyers.
- Use Case: Multilingual OCR Model
- Format: Images
- Volume: 23,500+
- Annotation: Yes
European Receipt Image Dataset
11.5k+ images of receipt from major European cities
- Use Case: Object detection model
- Format: Images
- Volume: 11,500+
- Annotation: No
Invoice/Receipt Dataset
75k+ receipts in multiple languages
- Use Case: Receipt AI Models
- Format: Images
- Volume: 75,000+
- Annotation: No
Featured Clients
Empowering teams to build world-leading AI products.
Our Capability
People
Dedicated and trained teams:
- 7000+ collaborators for Data Collection, Labeling & QA
- Credentialed Project Management Team
- Experienced Product Development Team
- Talent Pool Sourcing & Onboarding Team
Process
Highest process efficiency is assured with:
- Robust 6 Sigma Stage-Gate Process
- A dedicated team of 6 Sigma black belts – Key process owners & Quality compliance
- Continuous Improvement & Feedback Loop
Platform
The patented platform offers benefits:
- Web-based end-to-end platform
- Impeccable Quality
- Faster TAT
- Seamless Delivery
Recommended Resources
Buyer’s Guide
Image Annotation & Labeling for Computer Vision
Computer vision is all about making sense of the visual world to train computer vision applications. Its success completely boils down to what we call image annotation – the fundamental process behind the technology that makes machines make intelligent decisions and this is exactly what we are about to discuss and explore.
Infographics
What is Data Labeling? Everything a Beginner Needs to Know
Intelligent AI models need to be trained extensively for being able to identify patterns, objects, and eventually make reliable decisions. However, the trained data cannot be fed randomly and must be labeled to help the models understand, process, and learn comprehensively from the curated input patterns.
Solutions
Sentiment Analysis Services & Solutions
Analyze human emotions and sentiments by interpreting nuances in customer reviews, financial news, social media etc. Shaip offers you different techniques i.e. emotion detection, sentiment classification, fine-grained analysis, multilingual analysis, etc. to uncover meaningful insights from user emotions & sentiments.
Let’s discuss your OCR Training Data needs today