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所在平台: Udemy |
课程主页: https://www.udemy.com/course/python-for-computer-vision-with-opencv-and-deep-learning/
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《Python计算机视觉与深度学习课程总结》 欢迎来到我们的Python计算机视觉在线课程！该课程是学习如何使用Python编程语言进行计算机视觉的最佳资源。我们将探讨如何利用Python和OpenCV（开放计算机视觉库）分析图像和视频数据。如今，世界上最受欢迎的平台产生着前所未有的图像和视频数据量，例如，每60秒，用户在YouTube上上传超过300小时的视频，Netflix用户观看超过80,000小时的视频，而Instagram用户每天点赞超过200万张照片。因此，开发者需要掌握与图像和视频数据相关的必要技能。 计算机视觉使我们能够分析和利用图像与视频数据，应用广泛，包括自动驾驶汽车、社交网络应用、医学诊断等。作为一种快速增长的编程语言，Python非常适合利用现有的计算机视觉库来学习这一领域的知识。本课程旨在帮助您成为计算机视觉的专家，掘金这个预计将在未来几年达到200亿美元的行业。 课程内容包括： - 使用NumPy进行数值处理和图像操作 - OpenCV库基础：图像操作、处理和效果应用（如色彩映射、混合、阈值处理、梯度等） - 视频基础：从网络摄像头流媒体处理 - 直接视频主题：光流、目标检测，包括人脸检测和物体追踪 - 深度学习专题：图像识别与自定义图像分类 - 最新深度学习网络：YOLO（你只看一次）网络 课程涵盖的更多主题包括： - NumPy基础 - 图像和视频基本操作 - 图像阈值、模糊和光滑处理 - 形态学操作、梯度、直方图 - 物体检测、模板匹配、角点、边缘和网格检测 - 特征匹配、分水岭算法 - 面部检测和物体追踪 - 使用Keras进行深度学习、自定义深度学习网络、最先进的YOLO网络等。 如有任何问题，请随时通过Udemy与我联系。感谢您访问课程页面，希望在课程中见到您！
Welcome to the ultimate online course on Python for Computer Vision!This course is your best resource for learning how to use the Python programming language for Computer Vision.We'll be exploring how to use Python and the OpenCV (Open Computer Vision) library to analyze images and video data.The most popular platforms in the world are generating never before seen amounts of image and video data. Every 60 seconds users upload more than 300 hours of video to Youtube, Netflix subscribers stream over 80,000 hours of video, and Instagram users like over 2 million photos! Now more than ever its necessary for developers to gain the necessary skills to work with image and video data using computer vision.Computer vision allows us to analyze and leverage image and video data, with applications in a variety of industries, including self-driving cars, social network apps, medical diagnostics, and many more.As the fastest growing language in popularity, Python is well suited to leverage the power of existing computer vision libraries to learn from all this image and video data. In this course we'll teach you everything you need to know to become an expert in computer vision! This $20 billion dollar industry will be one of the most important job markets in the years to come.We'll start the course by learning about numerical processing with the NumPy library and how to open and manipulate images with NumPy. Then will move on to using the OpenCV library to open and work with image basics. Then we'll start to understand how to process images and apply a variety of effects, including color mappings, blending, thresholds, gradients, and more.Then we'll move on to understanding video basics with OpenCV, including working with streaming video from a webcam. Afterwards we'll learn about direct video topics, such as optical flow and object detection. Including face detection and object tracking.Then we'll move on to an entire section of the course devoted to the latest deep learning topics, including image recognition and custom image classifications. We'll even cover the latest deep learning networks, including the YOLO (you only look once) deep learning network.This course covers all this and more, including the following topics:NumPyImages with NumPyImage and Video Basics with NumPyColor MappingsBlending and Pasting ImagesImage ThresholdingBlurring and SmoothingMorphological OperatorsGradientsHistogramsStreaming video with OpenCVObject DetectionTemplate MatchingCorner, Edge, and Grid DetectionContour DetectionFeature MatchingWaterShed AlgorithmFace DetectionObject TrackingOptical FlowDeep Learning with KerasKeras and Convolutional NetworksCustomized Deep Learning NetworksState of the Art YOLO Networksand much more!Feel free to message me on Udemy if you have any questions about the course!Thanks for checking out the course page, and I hope to see you inside!Jose
