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所在平台: Udemy |
课程主页: https://www.udemy.com/course/image-processing-using-opencv-from-zero-to-hero/
课程评论：没有评论
课程名称：使用OpenCV与Python进行实用图像处理及项目 概述： 欢迎参加“从零到英雄的OpenCV图像处理”课程！图像处理是数据科学的一个重要领域，在当今各行业中有着广泛的应用。许多行业正在寻找具有这些技能的数据科学家。本课程完全基于项目学习，您将在每个模块完成后进行相应的项目。课程内容涵盖图像处理从基础到高级技术，包括将应用的机器学习算法和模型应用于图像。 您将学习到： - 图像基础知识 - 绘图 - 图像平移 - 图像处理技术 - 平滑滤波器 - 过滤器 - OpenCV中的图形用户界面（GUI） - 阈值处理 课程亮点： 1. 第1至7部分将从加载和显示图像的基础知识入手，理解图像背后的数学基础，同时教授绘图和视频相关概念。 2. 在模块项目中，您将学习到目标检测，包括使用Viola-Jones算法进行人脸检测、基于深度神经网络的（SSD ResNet 10, Caffe实现）人脸检测以及实时人脸检测与面部特征检测。 3. 第8至11部分将进入图像处理的概念，如图像变换（平移、翻转、旋转和裁剪），同时教授OpenCV中的算术操作。 4. 在第12、13部分，您将学习位运算和掩模概念，包括真值表及“与”、“或”、“非”、“异或”的各种位运算。 5. 第14部分将讨论平滑滤波器的扩展内容，包括平均模糊、Gaussian模糊、中值模糊和双边滤波等技术。 6. 第15部分的项目将涉及自动面部模糊处理。 7. 第16部分深入阈值滤波，探讨BINARY、TOZERO、TRUNC、ADAPTIVE MEAN和ADAPTIVE GAUSSIAN的概念，并在OpenCV和Python中进行实现。 您将完全访问本课程中使用的图像、数据和Jupyter Notebook文件。课程中使用的代码设计合理，可以直接用于实际场景中获取输出。 数据科学无处不在。
Welcome to "Image Processing using OpenCV from Zero to Hero"!!!Image Processing is one of the areas of Data Science and has a wide variety of applications in the industries in the current world. Many industries looking for a Data Scientist with these skills. This course is completely project-based learning. Where you will do the project after completion of every module. Here I will cover the image processing from basics to advanced techniques including applied machine learning algorithms and models to images. WHAT YOU WILL LEARN?Image BasicsDrawingsImage TranslationImage Processing TechniquesSmoothing FiltersFiltersGraphical Use Interphase (GUI) in OpenCVThresholdingKey Highlights in Section 1 to 7We will start the course with very basic like load, display images. With that, we will understand the basic mathematics background behind the images. Also, I will teach you the concepts of Drawings and Videos. Projects (Object Detection):Face Detection using Viola-Jones AlgorithmFace Detection using Deep Neural Networks (SSD ResNet 10, Caffe Implementation)Real-Time Face DetectionFacial Landmark DetectionKey Highlights in Section 8 to 11 We will slowly move into image processing concepts related to image transformations like image translation, flipping, rotating, and cropping. I will also teach arithmetic operations in OpenCV.Project (Brightness Control): 5. GUI based Brightness Control in Images 6. Real-Time Brightness ControlKey Highlights in Section 12,13In these sections, I will introduce new concepts on bitwise operations and masking, where you will learn the truth table and different bitwise operations like "AND", "OR", "NOT", "XOR".Key Highlights in Section 14Then we will extend our discussion on Smoothing Filter which is a very important image processing technique. In this section, I will teach smoothing techniques like Average Blur, Gaussian Blur, Median Blur & Bilateral Filter.Key Highlights in Section 15Project on automatics facial blurKey Highlights in Section 16Thresholding filter: Here we will deep dive into thresholding concepts (BINARY, TOZERO, TRUNC, ADAPTIVE MEAN, ADAPTIVE GAUSSIAN) and implement with OpenCV and PythonYou will have complete access to Images, Data, Jupyter Notebook files that are used in this course. The code used in this course is written in such a way that you can directly plug the function into the real-time scenario and get the output. ------------Data Science Anywhere
