Update app.py

app.py

@@ -137,37 +137,57 @@
 
 
 
-import gradio as gr
 import numpy as np
-from PIL import Image
 from tensorflow.keras.models import load_model
+from PIL import Image
+import gradio as gr
 from models import create_vgg19_model
 from gradcam_utils import generate_heatmap_tf_explain
 
 # Load models
 ensemble_model = load_model("ensemble_model_best(92.3).h5")
-vgg_model = create_vgg19_model()  # Used for Grad-CAM
+vgg_model = create_vgg19_model()  # Used only for Grad-CAM
 
 def get_class_name(class_id):
     return "Normal" if class_id == 0 else "Pneumonia"
 
 def predict_and_heatmap(image):
-    # Preprocess input image
+    # Resize and normalize image for prediction
     img = image.resize((224, 224))
     img_array = np.array(img) / 255.0
     img_array = np.expand_dims(img_array, axis=0)
 
-    # Predict using ensemble model
+    # Predict with ensemble model
     prediction = ensemble_model.predict(img_array)
     class_id = int(np.argmax(prediction[0]))
     result = get_class_name(class_id)
 
-    # Generate heatmap using tf-explain and VGG19
-    heatmap_img = generate_heatmap_tf_explain(image, vgg_model, class_index=class_id)
+    # Generate heatmap with tf-explain using VGG19
+    heatmap_img = generate_heatmap_tf_explain(img, vgg_model, class_index=class_id)
 
     return result, heatmap_img
 
-# Gradio Interface
+# 🎨 Custom CSS styling
+custom_css = """
+body {
+    background-color: #1c1c1e;
+    font-family: 'Segoe UI', sans-serif;
+}
+h1, h2, .output_class {
+    color: #ffffff;
+    text-align: center;
+}
+.gr-button {
+    background-color: #007aff !important;
+    color: white !important;
+}
+.gr-image-preview {
+    box-shadow: 0 0 20px rgba(0,0,0,0.5);
+    border-radius: 8px;
+}
+"""
+
+# Launch Gradio Interface
 interface = gr.Interface(
     fn=predict_and_heatmap,
     inputs=gr.Image(type="pil", label="Upload Chest X-ray"),
@@ -175,10 +195,10 @@ interface = gr.Interface(
         gr.Label(label="Prediction"),
         gr.Image(label="Grad-CAM Heatmap")
     ],
-    title="Pneumonia Detection Using Deep Learning",
-    description="Upload a chest X-ray to detect Pneumonia and see the heatmap visualization (Grad-CAM powered by tf-explain)."
+    title="🩺 Pneumonia Detection Using Deep Learning",
+    description="Upload a chest X-ray to detect Pneumonia and see the heatmap visualization (powered by tf-explain and VGG19).",
+    css=custom_css
 )
 
 if __name__ == "__main__":
     interface.launch()
-