commit

app.py

@@ -6,10 +6,8 @@ from PIL import Image
 # Define model repository
 model_name = "Aya-Ch/brain-tumor-classifier"
 processor = AutoImageProcessor.from_pretrained(model_name)
-
 model = AutoModelForImageClassification.from_pretrained(model_name)
 
-
 # Define brain tumor classes
 tumor_classes = ['meningioma', 'glioma', 'pituitary tumor']
 
@@ -30,15 +28,23 @@ def predict(image):
     except Exception as e:
         return {"Error": f"Failed to process image: {str(e)}"}
 
+# Define example images
+examples = [
+    ["examples/meningioma.jpg"],
+    ["examples/glioma.jpg"],
+    ["examples/pituitary_tumor.jpg"]
+]
 
-# Gradio Interface
+# Gradio Interface with Examples
 demo = gr.Interface(
     fn=predict, 
     inputs=gr.Image(type="pil"),  # Accepts image input
     outputs=gr.Label(label="Tumor Classification"), 
     title="Brain Tumor Classifier",
-    description="Upload an MRI scan to classify the type of brain tumor(meningioma, glioma or pituitary tumor)",
-    allow_flagging="never"
+    description="Upload an MRI scan to classify the type of brain tumor (meningioma, glioma or pituitary tumor)",
+    allow_flagging="never",
+    examples=examples  # Add preloaded example images
+    
 )
 
 # Launch the app