10.Using EasyOCR for OCR Processing скачать в хорошем качестве

10.Using EasyOCR for OCR Processing

In this video, we continue from our previous session where we filtered regions of interest (ROI) to extract text blocks from images. Now, we dive into the powerful EasyOCR library to perform Optical Character Recognition (OCR) on those extracted areas. 🔍 What You’ll Learn: -Introduction to EasyOCR and how it works -Installation steps for EasyOCR, with and without GPU support -Verifying PyTorch installation and GPU availability -Using the Reader class and readtext method -Different ways to extract text: basic usage, paragraph grouping, and clean text-only output -Final example combining detected text into paragraphs, while preserving bounding boxes and confidence scores ⚙️ Whether you're working with scanned documents, receipts, or any text-based images, this tutorial will give you a practical guide to integrating OCR using Python and EasyOCR. 📚 Links and Documentation: EasyOCR Documentation: https://www.jaided.ai/easyocr PyTorch Installation: https://pytorch.org/get-started/locally 💬 If you have any questions or want to see more tutorials like this, leave a comment below! 👍 Don’t forget to Like, Subscribe, and hit the Notification Bell for updates on upcoming content. #EasyOCR #PythonOCR #TextRecognition #DeepLearning #ComputerVision #PyTorch