Build an AI Image Generator App With Tkinter
Here, We’ll look at how to create an app using Tkinter and Stable Diffusion from Stability AI. While generative models like Flow-based models, Variational Autoencoders (VAEs), and Generative Adversarial Networks (GANs) are well-known, diffusion models are more advanced, effective, and produce better results.
Building the App
We’ll walk through creating a basic GUI application using a custom Tkinter. The goal is to set up an application window that can serve as the foundation for the “Text to Image” converter. Below is a snippet of Python code that demonstrates the creation of a basic GUI application:
from customtkinter import *
app = CTk()
# Setting the width and height of the app
app.geometry("500x500")
# Theme of the app
set_appearance_mode('light')
# Title
app.title('Text to Image')
app.mainloop()
Output:
Setting Up the Inline Text Bar and Clickable Button
By using customtkinter to build upon our basic GUI design, we can improve the user interface by including interactive elements like buttons and input fields. This is an upgrade to our earlier code that adds an action-triggering button and an entry widget for text input.
# Setting the inline text bar for entering the prompt by user
prompt = CTkEntry(app, height=30, width=350, font=("Arial", 15), text_color="black", fg_color="white")
prompt.place(x=10, y=10)
# Generate button for image generation
trigger = CTkButton(app, height=30, width=120, font=("Arial", 15), text_color="white", fg_color="#3DB7E4")
trigger.configure(text="Generate")
trigger.place(x=370, y=10)
Output
Adding a Label to Display Images
Let’s add a label widget to our GUI application to enhance it even more. It will act as a placeholder for images that are created based on the text input.
# Adding a label for displaying the image
lmain = CTkLabel(app, height = 400, width = 400, bg_color = '#f1ac85', corner_radius = 15)
lmain.place(x=50, y=70)
Output
Build an AI Image Generator App With Tkinter
Let’s take a brief look at the field of diffusion models, which are used to text to create images. Using a Markov chain, a diffusion model gradually adds noise to the data before reversing the process and creating the necessary data sample from the noise. Notable diffusion models are StabilityAI’s Stable diffusion, Google’s Imagen, and OpenAI’s DALLE2.
Contact Us