Update app.py

app.py

@@ -5,21 +5,20 @@ from medmnist import INFO
 from model import load_model
 from PIL import Image
 
-# Class names
+
 info = INFO["dermamnist"]
 class_names = list(info["label"].values())
 
-# Load model
+
 model = load_model()
 
-# Transforms (match training)
 transform = transforms.Compose([
     transforms.Resize((224, 224)),
     transforms.ToTensor(),
     transforms.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
 ])
 
-# Prediction function
+
 def predict(image):
     if image is None:
         return {"Error": 1.0}
@@ -32,13 +31,13 @@ def predict(image):
 
     return {class_names[i]: float(probs[i]) for i in range(len(class_names))}
 
-# Gradio UI
+
 demo = gr.Interface(
     fn=predict,
     inputs=gr.Image(type="pil"),
     outputs=gr.Label(num_top_classes=3),
     title="Skin Disease Classifier",
-    description="Upload a skin image and the model will predict potential skin cancer(melanoma), tumor or moles using EfficientNet-B2 fine-tuned on DermMNIST."
+    description="Upload a skin image and our model will predict potential skin cancer(melanoma), tumor or moles using EfficientNet-B2 fine-tuned on DermMNIST."
 )
 
 if __name__ == "__main__":