# Cyclic Consistent Image Style Transformation: From Model to System
## 4 Method
### Design of an Image Style Transfer System Based on C3 GAN  
In common cases, software systems are required to be efficient and stable. We followed these principles when designing our image style transfer system based on our C3 GAN model, such that our system can generate high-quality style transfer images under a short time limit. Additionally, we established an algorithm database for quick implementation of different algorithms. Meanwhile, our system also focused on security problems and user privacy. The architecture of our system is illustrated in Figure 6.  
Our system is developed using Python and MySQL. Python serves as the core programming language, Flask is utilized as the web framework for frontend and backend interactions, and MySQL is employed as a lightweight database to store user and image information. Python is a high-level, easy-to-learn, open-source, and cross-platform language suitable for data science, artificial intelligence, web development, and other fields. Flask, a Python-based web framework, provides straightforward routing, template rendering, and request processing functionalities, making it ideal for small to medium-sized web application development. MySQL, a lightweight relational database management system that supports various platforms and is widely used in web application development. In this design, Python, Flask, and MySQL collaboratively build the development environment for the image style transfer system based on our C3 GAN. To be more specific, our system consists mainly of the User Login Module and the Main Interface Module. User login module. The function of the user login module of this system is to verify the identity of different users and then display the main interface. The module supports two user types: ordinary users and user administrators. The module automatically jumps to different main interfaces according to the user type. Firstly, we created a web application based on Python Flask, then we created a Flask application named \"app\" and defined two routes, namely the root route \"/\", \"/login\" and \"/uploader\", and the sub-route \"/admin\". Among them, the root route \"/\" corresponds to the login page; the route \"/login\" is used to receive the submission of the login form, verify the user's identity, and jump to different main interfaces according to the user type; the routes \"/uploader\" and \"/admin\" correspond to the main interfaces of ordinary users and administrators. The user information is stored in the database, and the MySQL database is accessed by using the SQLAlchemy module of Python Flask. After reading the user information in MySQL, it is compared with the content filled in the form. If the username matches, the password is judged. If both match, the login is successful, otherwise the login fails. Figure 6: System architecture of our image style transfer system. Main interface module. The main interface of the system shows the effect of image style transfer based on the C3 GAN model, as shown in Figure 7. The image upload interface has a button for uploading files and an area for displaying images, allowing users to upload their own images and perform style transfer, and then download the images. The website's graphical user interface is simple and beautiful, using the Bootstrap framework and providing important information and functions so that users can better use the system. The overall workflow of the system is illustrated in Figure 8. The frontend user interface provides a user-friendly page with options to upload files, allowing users to select and upload images for style conversion. The Flask backend processes user requests, invokes the C3 GAN model for image style conversion, and returns the results to the front end. The pre-trained C3 GAN model, loaded in the backend, performs the image style conversion, trained for tasks such as art style changes (e.g., Ukiyo-e) and seasonal changes. The main steps are as follows:  
1. Upload Data: The system receives the image file uploaded by the user. 2.