Detecting Glaucoma with Machine Learning Techniques and CNN, and Visualizing Models in a Streamlit Web Application

First, we create a virtual environment. A virtual environment is an isolated Python environment that allows you to install packages and dependencies specific to a project without affecting the global Python installation. It helps manage project-specific dependencies efficiently. We might need a virtual environment for each of our project as each project might need a particular version of package or library, and using the same environment for multiple projects may lead to some features missing out on specific projects.

-> Create a project folder -> Open the command prompt in that directory -> Run the following command: python -m venv env -> After creating a virtual environment, run the following command to activate it: env\scripts\activate -> Now, our virtual environment is active. After you complete using the environment and want to deactivate it, just run the "deactivate" prompt to do the job.

-> All the required packages have been specified in the requirement.txt file. -> Copy the requirements.txt file into your project folder. -> After activating the virtual environment, run the following command to install required packages: pip install -r requirement.txt -> All required packages will be installed. -> to get the requirements from an existing environment, run the following command there: pip freeze > requirements.txt

Copy all the files into your project folder

-> First, open the project folder using VS Code and activate the environment using the following command in the terminal: env\scripts\activate -> Once the env is active, run the following command to get the streamlit app going: streamlit run app.py -> To stop running the app, just click "ctrl+C" in the terminal.

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