Add app.py to the repo

app.py

+import streamlit as st
+from keras.models import load_model
+from PIL import Image
+import numpy as np
+import io
+import matplotlib.pyplot as plt
+
+# Load the model
+loaded_model = load_model('advanced_car_classification_model_md.h5', compile=False)
+
+# Define car classes
+car_classes = ["alto_modified", "civic_modified", "wagonr_modified"]
+
+# Create file uploader widget
+st.title("Advanced Modified Car Classification")
+st.write("Upload an image and let the model predict the car class.")
+
+uploader = st.file_uploader(
+    label="Upload an image",
+    type=["jpg", "jpeg", "png"],
+    accept_multiple_files=False
+)
+
+# Define prediction function
+def predict_car(image_data):
+    img = Image.open(image_data)
+    img = img.resize((150, 150))  # Resize to 150x150
+    img_array = np.array(img) / 255.0
+    img_array = np.expand_dims(img_array, axis=0)
+
+    predictions = loaded_model.predict(img_array)[0]
+    predicted_class_index = np.argmax(predictions)
+    predicted_car_class = car_classes[predicted_class_index]
+    
+    return predicted_car_class, predictions
+
+# Display uploaded image and prediction
+if uploader:
+    st.subheader("Uploaded Image")
+    uploaded_image = uploader.read()
+    st.image(uploaded_image, caption='Uploaded Image', use_column_width=True)
+
+    predicted_car, prediction_probs = predict_car(io.BytesIO(uploaded_image))
+    
+    st.subheader("Prediction")
+    st.write(f"Predicted Car: {predicted_car}")
+
+    st.subheader("Prediction Probabilities")
+    col1, col2 = st.columns(2)
+    with col1:
+        st.write("Alto Modified")
+        st.write("Civic Modified")
+    with col2:
+        st.write(f"{prediction_probs[0]:.2%}")
+        st.write(f"{prediction_probs[1]:.2%}")
+
+    st.subheader("Prediction Probability Chart")
+    # Create a simple pie chart using Matplotlib
+    fig, ax = plt.subplots()
+    ax.pie(prediction_probs, labels=car_classes, autopct='%1.1f%%', startangle=90)
+    ax.axis('equal')  # Equal aspect ratio ensures the pie chart is circular.
+    st.pyplot(fig)