Computer Vision : OCR using Python - GenAI with LLM & RAG

🚀 Computer Vision: OCR using Python 👁️‍🗨️

A Comprehensive Course for Aspiring Computer Vision - OCR Specialists

Why This Course?

This course, Computer Vision: OCR using Python, stands out due to its practical approach and in-depth coverage of the subject matter. Here's why you should consider enrolling:

• 🛠️ Hands-On Projects: Engage with 5 in-demand Computer Vision projects that are thoroughly explained with detailed code walkthroughs, ensuring they work effectively in real-world scenarios.

• ⚡ In-Course Support: Receive dedicated support within 24 hours for any issues you encounter during your learning journey.

• 📚 Deep Dive into Deep Learning: Get a comprehensive understanding of two cutting-edge text detection models, CTPN and EAST, through practical implementations.

The Future of Data Extraction is Here

Optical Character Recognition (OCR) is revolutionizing the way industries handle text data extraction from images and PDFs. As a key driver in digitization, OCR technologies are not only streamlining workflows across various sectors but also enhancing customer experiences. The OCR market is booming, with projections to reach $13.4 billion by 2025, as reported by recent market research.

Course Highlights:

• OCR Architecture: Understand the intricacies of building an OCR system from scratch.

• Text Detection from Image: Master the art of identifying text within images using OpenCV and Deep Learning Models.

• Text Recognition from Image: Learn to extract text content from images with Tesseract and OCR techniques.

• Pixels and Image Basics: Gain insights into image processing fundamentals.

• Image Properties: Explore various image properties that affect OCR outcomes.

• Kernel and Feature Map: Discover how these tools are instrumental in feature extraction for text detection.

• Preprocessing Techniques: Learn essential preprocessing techniques like binarization, thresholding, rescaling, and noise removal through morphology, dilation, erosion, and more.

• Image Segmentation: Understand the segmentation of images into meaningful parts for better text recognition.

• EasyOCR: Simplify your OCR tasks with this powerful library.

• PyTesseract Operations: Dive deep into Tesseract operations and their applications in OCR.

• Named Entity Recognition: Use Spacy to recognize and categorize named entities within text.

• Regular Expression for Text and Dates: Learn to use regular expressions effectively for extracting text and dates from images.

• Deep Learning Model Training: Train the CTPN and EAST models on datasets like SIROE for robust text detection and recognition.

• Real-World OCR Solutions: Implement OCR solutions for practical scenarios such as Invoice Processing, KYC Digitization, Business Card Recognition, and Vehicle Number Plate Recognition.

What You Will Learn:

• OCR Architecture
• Text Detection from Image
• Text Recognition from Image
• Pixels and Image Basics
• Image Properties
• Kernel and Feature Map
• Preprocessing Techniques (Binarisation, Thresholding, Rescaling)
• Noise Removal Techniques (Morphology, Dilation, Erosion, Blurring, Orientation, Deskewing, Borders, Perspective Transformation)
• Image Segmentation
• EasyOCR
• PyTesseract Operations
• Tesseract
• Named Entity Recognition with Spacy
• Regular Expression for Text and Dates
• Training of CTPN and EAST Deep Learning Models on SIROE Dataset
• CTPN Model for Text Detection & Recognition
• EAST Model for Text Detection & Recognition
• Invoice Processing OCR Solution with python code
• Invoice Structured Output in XML Format Solution with python code
• Vehicle Nameplate OCR Solution with python code
• Business Card Recognition OCR Solution with python code
• KYC Digitization OCR Solution with python code

With 33 downloadable source code resources and projects, this course is a treasure trove for anyone looking to become an expert in Computer Vision with a specialization in OCR. Don't miss the opportunity to be at the forefront of this exciting and rapidly evolving field!