Update app.py

app.py

@@ -1,9 +1,8 @@
 # Create a text-to-image interface with options to choose schedulers, sampling steps, and no default dark theme.
 import gradio as gr
 import numpy as np
-import matplotlib.pyplot as plt
+from PIL import Image
 import time
-import os
 
 # Define a function to generate an image based on the input text, scheduler, and sampling steps.
 def generate_image(text, scheduler, sampling_steps):
@@ -20,12 +19,13 @@ def generate_image(text, scheduler, sampling_steps):
     elif scheduler == "Euler":
         image = np.clip(image * (1 + sampling_steps / 20), 0, 1)
     
-    # Generate a unique filename for the image
+    # Generate a unique filename for the image using the current timestamp
     timestamp = int(time.time() * 1000)
     filename = f"image_{timestamp}.webp"
     
-    # Save the image in WEBP format
-    plt.imsave(filename, image, format="webp")
+    # Convert the numpy array to a PIL image and save it in WEBP format
+    image_pil = Image.fromarray((image * 255).astype(np.uint8))
+    image_pil.save(filename, format="WEBP")
     
     return filename
 
@@ -51,4 +51,6 @@ with gr.Blocks() as demo:
 if __name__ == "__main__":
     gr.load("models/stabilityai/stable-diffusion-3.5-large").launch()
     demo.launch(show_error=True)
+    
+