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所在平台: Udemy |
课程主页: https://www.udemy.com/course/build-a-web-app-with-python-and-opencv-image-editing-app/
课程评论：没有评论
**课程名称：** 使用 Python 和 OpenCV 构建 Web 应用：图像编辑应用 **课程概述：** 本课程将指导您使用 Streamlit——一个基于 Python 的强大框架，从零开始快速构建一个现代化的图像编辑 Web 应用原型。您将学习如何实现多种图像处理技术，包括灰度化、调整对比度、亮度、锐度以及模糊度，并将这些功能集成到应用中，允许用户自由选择和控制。此外，您还将学习如何创建用于人脸和眼睛检测、图像卡通化以及边缘检测的函数。 **课程内容：** * **第一部分：入门** * Anaconda 下载与安装 * 导入必要的库/软件包 * **第二部分：应用主界面设置** * 设置应用的标题和副标题 * 创建“检测”功能区域 * 创建“关于”信息区域 * **第三部分：连接图像处理技术到应用** * 灰度化 * 对比度调整 * 亮度调整 * 模糊化 * 锐化 * 显示原始图像 * **第四部分：功能实现与扩展** * 设置功能选择框 * 人脸检测（第一部分） * 设置 Haar Cascade 文件 * 人脸检测（第二部分） * 眼睛检测 * 图像卡通化（第一部分） * 图像卡通化（第二部分） * 图像卡通化（第三部分）
In this course you are going to build a modern prototype of a web application: image editing app using streamlit which is a python-based framework that provides you with all the tools to build your app from scratch in a simple and fast way. Through this course you are going to learn how to implement different image processing techniques like: gray-scaling, contrast, brightness, sharpness and blurriness and connect them to your application giving the hand to users to choose and control the degree of each one. You will also, learn how to create functions that allow you to detect faces and eyes in images, functions that create cartoon version of your images and other to detect edges of different objects and regions in images. The content of this course: Section 1: First steps: - Anaconda download and installation - Importing the libraries / packagesSection 2: Set up the main part of the app - Setting a title and a subtitle for the app - Create the " Detection " part - Create the " About " partSection 3: Connect the image processing techniques to the app - Option 1: Gray-scaling - Option 2: Contrast - Option 3: Brightness - Option 4: Blurriness - Option 5: Sharpness - Option 6: Original Section 4: Set up the main part of the app - Set the features selectbox - Detect faces (part 1) - Set the haar cascade files - Detect faces (part 2) - Detect eyes - Cartoonize an image (part 1) - Cartoonize an image (part 2) - Cannize an image
