Update app.py

app.py

@@ -70,15 +70,8 @@ def predict(image):
 # Get all example images
 example_images = glob.glob("All/*")
 
-# Select a few for the examples grid (6 images)
-examples = [
-    ["All/Captura de pantalla 2025-10-08 110957.png"],
-    ["All/Captura de pantalla 2025-10-08 111037.png"],
-    ["All/cigar.jpg"],
-    ["All/fotonoticia_20120215131819_1200.jpg"],
-    ["All/Joos_van_Craesbeeck_-_The_Smoker.jpg"],
-    ["All/a-group-of-young-people-at-a-party-taking-a-selfie-photo.jpg"]
-]
+examples = [[img] for img in example_images[:12]]  # Takes the 12 images
+
 
 # Function to get random sample
 def get_random_sample():
@@ -112,17 +105,19 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
         with gr.Column():
             output_label = gr.Label(num_top_classes=2, label="Prediction")
     
-    gr.Markdown("### 📸 Try these examples:")
-    gr.Examples(
-        examples=examples,
-        inputs=input_image,
-        outputs=output_label,
-        fn=predict,
-        cache_examples=True
-    )
+            gr.Markdown("### 📸 Try these examples:")
+            gr.Examples(
+                examples=examples,
+                inputs=input_image,
+                outputs=output_label,
+                fn=predict,
+                cache_examples=True
+            )
     
     gr.Markdown(
         """
+        ===================================================================================================
+        
         ### About this model
         
         - **Architecture:** ResNet34 + LoRA adapters (rank=8)