Собрали в одном месте самые важные ссылкии сделали Тренажер IT-инцидентов для DevOps/SRE
The main goal of this post is to show how to work with the NumPy array for OpenCV images. I will use a simple case to present how to extend the image with new pixels.
Table of Contents Achieving Optimal Speed and Accuracy in Object Detection (YOLOv4)
Detection frameworks have become increasingly fast and accurate, as seen in our last post on YOLOv1; however, most detection methods are still constrained to a small set of objects like 20 classes in PASCAL VOC and 80 classes in Microsoft COCO.
Table of Contents Understanding a Real-Time Object Detection Network: You Only Look Once (YOLOv1)
Table of Contents Text Detection and OCR with Microsoft Cognitive Services Microsoft Cognitive Services for OCR
In this tutorial, you will learn to improve text detection speed with OpenCV and GPUs.
In this tutorial, you will learn how to OCR video streams. This lesson is part 3 of a 4-part series on Optical Character Recognition with Python
In this tutorial, you will: Discover a technique for associating rows and columns together Learn how to detect tables of text/data in an image
In this tutorial, you will learn how to create U-Net, an image segmentation model in TensorFlow 2 / Keras. We will first present a brief introduction on image segmentation, U-Net architecture, and then walk through the code implementation with a Colab notebook.