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所在平台: Udemy |
课程主页: https://www.udemy.com/course/smile-detection-with-deep-learning/
课程评论：没有评论
**课程名称：** 使用深度学习进行微笑检测 **课程概述：** 本课程将教会您如何构建一个端到端的应用程序，用于在图像和视频中检测微笑。您将学习如何利用深度学习技术，具体来说是训练一个卷积神经网络（CNN）。课程将从使用包含微笑和非微笑面部的SMILES数据集进行CNN训练开始。 训练完成后，我们将按照以下步骤进行微笑检测： 1. **人脸检测：** 使用Haar级联分类器在图像中检测人脸。 2. **人脸区域提取：** 从图像中裁剪出检测到的人脸区域。 3. **模型预测：** 将裁剪出的人脸区域输入训练好的CNN模型进行微笑或非微笑的分类。 4. **结果标注：** 根据模型的预测结果，在原图像上标注“Smiling”（微笑）或“Not Smiling”（不微笑）。 **目标受众：** 本课程适合具有中级Python编程经验，并对深度学习和计算机视觉有一定了解的学习者。 **学习成果：** 完成本课程后，您将能够独立构建一个功能完备的微笑检测应用程序，并可将其应用于您自己的项目中。 **课程包含内容：** * 1小时高清视频教程 * 课程所需的源代码、示例图片和视频 * 永久访问课程内容的权限 * 优先技术支持 **课程内容主题：** * 数据加载 * 训练微笑检测器 * 将微笑检测器应用于图像 * 将微笑检测器应用于视频
In this course, we will be creating an end-to-end application that can detect smiles in images and videos.For that, we will use deep learning and start by training a convolutional neural network on the SMILES dataset which contains faces of people smiling and not smiling. Once the network is trained, we will go through the following steps to detect smiles in images and videos:We will use Haar cascades to detect a face in an image.We will then extract the face region from the image.then we will pass the face region to the network for classification.And finally, we will annotate the image with the label "smiling" or "not smiling" depending on the output of the network.This class was made for intermediate Python programmers that have some familiarity with deep learning and computer vision.By the end of this course, you'll have a fully functional smile detection application that you can use in your own projects.What you'll get:When you buy the course you'll receive:1 hour of HD video tutorialsSource code, example images, and videos used in the courseLifetime access to the coursePriority supportWhat is covered in this course:Just so that you have some idea of what you will learn in this course, these are the topics that we will cover:Load the DataTrain the Smile DetectorApply Our Smile Detector to ImagesApply Our Smile Detector to Videos
