Development and implementation of a client-server application for classifying user images using the Python programming language

This work is aimed at developing an image classification application using a client-server architecture. The proposed application allows for the study and practical application of in-demand technology stacks widely used in the market. It not only demonstrates the process of developing a web application but also provides tools for working with pre-trained image classification models, emphasizing their practical importance. This work demonstrates the practical application of modern web technologies, including the development of the server part for processing user requests such as authorization and registration requests. It also showcases the use of cloud technologies. The main focus of this work is on analyzing methods of user authentication and authorization in a web application implemented using AWS CDK and Amplify. This includes studying various strategies for storing and processing user data, mechanisms for validating information, and ensuring the security of data transmission between the client and the server. The research conducted in this work covers several key aspects, including the analysis of modern web tools, the practical implementation of the server part for processing client requests for user authorization and registration, as well as efficient data management in the database. The main emphasis is on using modern technology stacks to create a web application and applying pre-trained models for image classification, highlighting the practical nature of the development and application of web services. Particular attention is paid to creating the server part for processing user requests such as authorization and registration, deploying the server part using AWS CDK, and storing user information in Amazon Cognito. The study examines concepts such as Amazon Web Services, Microsoft Azure, Google Cloud Platform, IaaS, PaaS, Amazon EC2, Amazon S3, AWS Identity and Access Management, ACL, AWS Lambda, and Amazon Kinesis. It describes the process of deploying the application using AWS CDK, creating an AWS Cognito User Pool, and using Amplify. Keywords: AWS Cloud Development Kit, AWS Serverless Application Model, Infrastructure as Code, AWS CloudFormation, YAML, JSON, AWS SDK, IAM permissions, OAuth, Amazon Pinpoint, localStorage, sessionStorage, sharedInMemoryStorage, CookieStorage. The work contains 35 images, 8 appendices, consists of 89 pages, and references 23 sources.