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所在平台: Udemy |
课程主页: https://www.udemy.com/course/build-self-checkout-machine-virtual-keyboard-with-opencv/
课程评论：没有评论
课程名称：使用OpenCV构建自助结账机和虚拟键盘 课程概述：欢迎参加《使用OpenCV构建自助结账机和虚拟键盘》课程。这是一门综合性项目课程，将一步一步教您如何利用OpenCV、Keras、卷积神经网络、Media Pipe和Tkinter构建一个全自动自助结账系统和互动虚拟键盘。课程结合了计算机视觉和物体检测，适合希望提高编程技能并深化零售自动化技术知识的学习者。 在课程的引导部分，您将学习自助结账系统的基本原理，包括案例研究、所用技术及技术挑战。在接下来的部分，您将了解自助结账机的工作原理，包括数据收集、预处理、模型训练、物体检测、产品与数据集的匹配，以及显示产品名称和价格。之后，您将创建训练数据，包括一张包含产品图像的文件夹和一个包含产品信息（如产品ID、产品名称、价格和折扣）的Excel文件。 课程的第一个项目将是使用CNN和Keras训练自助结账模型，然后使用Tkinter构建简单的用户界面，并嵌入OpenCV摄像头。用户将能够扫描产品，系统会自动计算总价。此外，我们还会创建一个简单的支付模拟功能，让用户输入支付金额，系统将检查输入金额是否大于总价，并相应地显示找零或提示输入正确金额。 在第二个项目部分，我们将利用OpenCV和Media Pipe构建一个互动虚拟键盘。该系统能够识别手势，为用户提供无接触输入体验。构建完这两个模型后，我们会进行测试，以确保它们正常工作且逻辑正确。 最后，在课程结束时，我们将把虚拟键盘集成到自助结账机中，用户将能够通过手势在虚拟键盘中输入支付金额，从而实现流畅高效的结账体验。 本课程将帮助您了解自助结账机和零售自动化的知识，包括用例、技术限制和所需技术；学习自助结账机的工作流程、训练数据创建、产品扫描及支付处理；了解虚拟键盘的原理以及如何使用手势打字；使用OpenCV和Tkinter构建自助结账机和虚拟键盘等。 通过参与这一创新项目，您将掌握可以在多个行业中应用的自动化技能。
Welcome to Building Self Checkout Machine & Virtual Keyboard with OpenCV course. This is a comprehensive project based course where you will learn step by step on how to build a fully automated self checkout system and interactive virtual keyboard using OpenCV, Keras, Convolutional Neural Networks, Media Pipe, and Tkinter. This course is a perfect combination between computer vision and object detection, making it an ideal opportunity to practice your programming skills while improving your technical knowledge in retail automation. In the introduction session, you will learn the basic fundamentals of the self checkout system, such as getting to know its use cases, technologies that will be used, and some technical challenges. Then, in the next section, you will learn how the self checkout machine works. This section will cover data collection, preprocessing, model training, object detection, matching the product to the dataset, displaying product name and price. Afterward, we will create training data which will consist of one folder containing product images and an excel file containing product information like product ID, product name, price, and discount. Once, everything is all set, we will start the first project, firstly, we will train the self checkout model using CNN and Keras, after that we will build simple user interface using Tkinter and we will also embed OpenCV webcam to the interface, once the camera has been activated, the user will be able to scan products and the system will automatically calculate the total price. In addition, we will also create a simple payment simulation where users can enter the payment amount and the system will check if the entered payment amount is more than the total price, if yes, then it will display the change but if the entered payment amount is less than total price, the system will ask the user to enter the right amount. Meanwhile, in the second project section, we will build an interactive virtual keyboard using OpenCV and Media Pipe. This system will be able to recognise hand gestures and provide users with touchless typing experience. After building these two models, we will be conducting testing to make sure these models have been fully functioning and all logics have been implemented correctly. Lastly, at the end of the course, we will integrate the virtual keyboard to a self checkout machine, enabling users to scan products and complete payments by entering the payment amount directly on the virtual keyboard using a hand gesture, ensuring a smooth and efficient checkout experience.First of all, before getting into the course, we need to ask ourselves this question: why should we build an automated self checkout machine and virtual keyboard? Well, here is my answer, long queues and slow checkout processes in retail can frustrate customers and affect store efficiency. Building an automated self-checkout machine and a virtual keyboard can greatly enhance the retail experience by streamlining transactions and improving customer satisfaction. The self-checkout machine speeds up the checkout process, reduces wait times, and minimizes the need for human labors, leading to increased operational efficiency. Meanwhile, the virtual keyboard offers a touchless input method, enhancing hygiene and convenience in high traffic environments. Moreover, by building these innovative projects, you will gain valuable skills in automation that are transferable across various industries.Below are things that you can expect to learn from this course:Learn about self checkout machine and retail automation, such as getting to know its use cases, technical limitations, and technologies that will be usedLearn how self checkout machines work. This section will cover training data creation, preprocessing, model training, product scanning, displaying product information, and paymentLearn about virtual keyboard and how this technology enables users to type in using finger movement without physically touching the keyboardLearn how to create training data consisting of product images and products informations like product ID, product name, price, and discountLearn how to activate webcam using OpenCVLearn how to create function to load product images from training dataLearn how to train self checkout model using Convolutional Neural Network and KerasLearn how to build self checkout machine using OpenCV and TkinterLearn how to create function to detect object and recognize productLearn how to create function for payment processing simulationLearn how to design custom virtual keyboard layoutLearn how to integrate hand tracking and detection system to virtual keyboardLearn how to build virtual keyboard using OpenCV, Tkinter and MediaPipeLearn how to design simple graphical user interface and create button using TkinterLearn how to conduct performance testing on self checkout machine and virtual keyboardLearn how to integrate virtual keyboard to self checkout machine
