Update app.py

app.py

@@ -1,21 +1,6 @@
 import gradio as gr
 from transformers import pipeline
 from PIL import Image
-#import os
-
-def load_images_from_current_directory():
-    images = []
-    current_directory = os.getcwd()
-    for filename in os.listdir(current_directory):
-        if filename.endswith(".jpg") or filename.endswith(".png"):
-            img_path = os.path.join(current_directory, filename)
-            img = Image.open(img_path)
-            if img is not None:
-                images.append(img)
-    return images
-
-# Example: Load images from the current directory
-#example_images = load_images_from_current_directory()
 
 # Define the image classification function
 def classify_image(image):
@@ -57,11 +42,9 @@ article = "<p style='text-align: center'>Image Classification | Demo Model</p>"
 
 
 # Prepare examples with loaded images
-#examples = []
-#for img in example_images:
-#    examples.append([np.array(img), os.path.basename(os.path.splitext(img.filename)[0])])
+examples = ["Normal_0.jpg", "Normal_1.jpg", "Normal_2.jpg", "Tumor_0.jpg", "Tumor_1.jpg", "Tumor_2.jpg"]
 
-demo = gr.Interface(fn=classify_image, inputs=image, outputs=label, description=description, article=article, title=title)
+demo = gr.Interface(fn=classify_image, inputs=image, outputs=label, description=description, article=article, title=title, examples=examples)
 
 # Launch the Gradio interface
 demo.launch()