Update app.py

app.py

@@ -44,29 +44,32 @@ if choice == "Upload Image":
     image_= st.file_uploader("📤 Upload an image (JPG, JPEG, PNG)", type=["jpg", "jpeg", "png"])
 else:
     image_= Image.open(r"dog.jpg").convert('RGB')
-
+try:
 # Preprocess image
-image_resized = image_.resize((224, 224))
-x = image.img_to_array(image_resized)
-x = np.expand_dims(x, axis=0)
-x = preprocess_input(x)
+    image_resized = image_.resize((224, 224))
+    x = image.img_to_array(image_resized)
+    x = np.expand_dims(x, axis=0)
+    x = preprocess_input(x)
 
 # Prediction
-preds = model.predict(x)
-pred_class = decode_predictions(preds, top=1)[0][0]
-st.markdown(f"**Predicted:** `{pred_class[1]}` with `{pred_class[2]*100:.2f}%` confidence")
+    preds = model.predict(x)
+    pred_class = decode_predictions(preds, top=1)[0][0]
+    st.markdown(f"**Predicted:** `{pred_class[1]}` with `{pred_class[2]*100:.2f}%` confidence")
 
 # Grad-CAM
-heatmap = make_gradcam_heatmap(x, model, last_conv_layer_name)
-img_cv = np.array(image_resized)
-heatmap = cv2.resize(heatmap, (img_cv.shape[1], img_cv.shape[0]))
-heatmap = np.uint8(255 * heatmap)
-heatmap = cv2.applyColorMap(heatmap, cv2.COLORMAP_JET)
-superimposed_img = cv2.addWeighted(img_cv, 0.6, heatmap, 0.4, 0)
+    heatmap = make_gradcam_heatmap(x, model, last_conv_layer_name)
+    img_cv = np.array(image_resized)
+    heatmap = cv2.resize(heatmap, (img_cv.shape[1], img_cv.shape[0]))
+    heatmap = np.uint8(255 * heatmap)
+    heatmap = cv2.applyColorMap(heatmap, cv2.COLORMAP_JET)
+    superimposed_img = cv2.addWeighted(img_cv, 0.6, heatmap, 0.4, 0)
 
 # Display images
-col1, col2 = st.columns(2)
-with col1:
-    st.image(image_resized, caption="Original Image", use_container_width=True)
-with col2:
-    st.image(superimposed_img, caption="Grad-CAM", use_container_width=True)
+    col1, col2 = st.columns(2)
+    with col1:
+        st.image(image_resized, caption="Original Image", use_container_width=True)
+    with col2:
+        st.image(superimposed_img, caption="Grad-CAM", use_container_width=True)
+
+except Exception as e:
+    st.write("Upload image")