Upload app.py

app.py

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+import streamlit as st
+from PIL import Image
+import numpy as np
+from tensorflow.keras.models import load_model
+from tensorflow.keras.preprocessing import image
+from tensorflow.keras.applications.vgg16 import preprocess_input
+
+# Load your trained model
+model = load_model('/Users/abhinavyadav/Downloads/BT(Deploy).h5')  # Replace with your model's path
+
+# Set Streamlit page config for a better layout
+st.set_page_config(page_title="Brain Tumor Detection", page_icon="🧠", layout="centered")
+
+# Add a title and description
+st.title("Brain Tumor Detection 🧠")
+st.markdown("""
+    Upload a brain MRI scan to detect whether it contains a brain tumor or not. 
+    Our model uses advanced deep learning to analyze your scan and provide a prediction.
+    """)
+
+# File uploader with custom styling
+uploaded_file = st.file_uploader("Upload a Brain MRI Scan", type=["jpg", "png", "jpeg"], label_visibility="collapsed")
+
+
+# Function to preprocess the image
+def preprocess_image(img):
+    img = img.resize((224, 224))  # Resize to 224x224
+    img_array = np.array(img)  # Convert image to numpy array
+    img_array = np.expand_dims(img_array, axis=0)  # Add batch dimension
+    img_array = preprocess_input(img_array)  # Preprocess image for VGG16
+    return img_array
+
+
+if uploaded_file is not None:
+    # Display the uploaded image
+    img = Image.open(uploaded_file)
+    st.image(img, caption="Uploaded MRI Scan", use_column_width=True)
+
+    # Preprocess and predict
+    try:
+        processed_image = preprocess_image(img)
+        st.write("Image successfully preprocessed!")
+
+        # Model prediction
+        prediction = model.predict(processed_image)
+
+        # Display prediction result with styling
+        st.subheader("Prediction Results")
+        if prediction[0][0] > 0.5:
+            st.markdown('<p style="font-size:18px;color:red;">⚠️ Brain Tumor Detected</p>', unsafe_allow_html=True)
+        else:
+            st.markdown('<p style="font-size:18px;color:green;">✅ No Brain Tumor Detected</p>', unsafe_allow_html=True)
+
+    except Exception as e:
+        st.error(f"Error in preprocessing or prediction: {e}")
+
+# Add footer and additional information
+st.markdown("""
+    ---
+    **Developed with 💙 by [Abhinav]**  
+    This project is aimed at helping doctors detect brain tumors from MRI scans using deep learning models.
+    """)
+
+# Custom styling for Streamlit components
+st.markdown("""
+    <style>
+        .css-1v0mbdj {
+            font-size: 20px;
+            font-weight: bold;
+        }
+        .css-5wyi5j {
+            background-color: #f0f0f5;
+        }
+    </style>
+""", unsafe_allow_html=True)