![]() |
Computer Vision - OCR using Python - Printable Version +- Softwarez.Info - Software's World! (https://softwarez.info) +-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone) +--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials) +--- Thread: Computer Vision - OCR using Python (/Thread-Computer-Vision-OCR-using-Python) |
Computer Vision - OCR using Python - AD-TEAM - 03-26-2025 ![]() Computer Vision - OCR using Python MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + srt | Duration: 53 lectures (3h 37m) | Size: 611.2 MB Computer Vision | OCR | Tesseract | Optical Character Recognition | OpenCV | Image Basics | Spacy | RegEx | Python |EAST What you'll learn: Understand the Image Basics and apply it for Image Processing Learn to implement OCR - Text Detection with OpenCV and Deep Learning Models Use Tesseract and EasyOCR to implement OCR - Text Recognition Work with OCR - Text Labelling using Spacy and Regular Expression Use OpenCV and Tesseract to apply Noise Removal Techniques including Thresholding, Rescaling, Dilation, Erosion and Deskewing Executable Code of CTPN and EAST Model implementation for Text Detection and Text Recognition Build OCR Solutions for Invoice Processing, Vehicle Nameplate, Business Card Recognition and KYC Digitization A quick starter on OCR Architecture, Commercial Solutions and Use Cases in Industry Requirements Basic Programming skills in Python Description **** This course is a quick starter for people who would like to become Computer Vision - Optical Character Recognition (OCR) Specialist **** Optical Character Recognition commonly called as OCR is the new buzzword in industry which is driving digitization in the enterprises. Every enterprise wants to adopt OCR to achieve easier and quicker access to their streams of data in digital format. An OCR implementation not only speed up the workflow of Text processes across various industries but also help in providing better customer experience. In fact, as per a recent research report, OCR market which was around 7.2 billion US Dollar is expected to see a huge growth in market size and will reach 13.4 billion US dollar by 2025. Enroll in this course to get a complete understanding of Optical Character Recognition (OCR) for Data Extraction from Images and PDF using Python. The course explains the theory of concepts followed by code demonstration to make you an expert in computer vision OCR. It provides hands-on guidance on Text Detection with OpenCV and Deep Learning Models, Text Recognition with Tesseract and OCR along with Text Labelling through Spacy and Regular Expression. It guides you to create technical solutions on most relevant OCR uses cases in the industry Here are just few of the topics we will be learning: OCR Architecture Pixels and Image Basics Kernel and Feature Map Preprocessing Techniques (Binarisation, Thresholding, Rescaling) Noise Removal Techniques (Morphology, Dilation, Erosion, Blurring, Orientation, Deskewing, Borders, Perspective Transformation) EasyOCR PyTesseract Operations Tesseract Named Entity Recognition Regular Expression for Text and Dates CTPN Model for Text Detection & Text Recognition EAST Model for Text Detection & Text 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 Who this course is for Beginners to Computer Vision OCR Engineer OCR Specialist Machine Learning Professionals Anyone looking to become more employable as a Computer Vision Expert ![]() AusFile Code: https://ausfile.com/hgzi0dvfjnlb/Computer_Vision_OCR_using_Python_GenAI_with_LLM_RAG.part1.rar Code: https://rapidgator.net/file/65c7cec4429dcaed101eb01891ffab0d/Computer_Vision_OCR_using_Python_GenAI_with_LLM_RAG.part1.rar Code: https://turbobit.net/7h5wocfh9etm/Computer_Vision_OCR_using_Python_GenAI_with_LLM_RAG.part1.rar.html |