Create app.py

app.py

@@ -0,0 +1,109 @@
+import streamlit as st
+import os
+import numpy as np
+import tensorflow as tf
+from PIL import Image
+import zipfile
+
+# Path to your zipped model file
+ZIP_MODEL_PATH = '/app/your_trained_model.keras.zip'  # Correct this path if needed
+UNZIPPED_MODEL_PATH = '/app/your_trained_model.keras'  # Path where the model will be extracted
+
+# Unzip the model if it hasn't been unzipped already
+if not os.path.exists(UNZIPPED_MODEL_PATH):
+    with zipfile.ZipFile(ZIP_MODEL_PATH, 'r') as zip_ref:
+        zip_ref.extractall('/app')
+        print(f"Model unzipped to {UNZIPPED_MODEL_PATH}")
+
+# Load the model
+try:
+    model = tf.keras.models.load_model(UNZIPPED_MODEL_PATH)
+    print("Model loaded successfully!")
+except Exception as e:
+    print(f"Error loading model: {e}")
+
+# Define the function to predict decoration
+def predict_decoration(image: Image.Image):
+    # Preprocess the image to match the model input format
+    image = image.resize((224, 224))  # Resize to match model's expected input size
+    image_array = np.array(image) / 255.0  # Normalize the image to [0, 1]
+    image_array = np.expand_dims(image_array, axis=0)  # Add batch dimension
+
+    # Make prediction
+    prediction = model.predict(image_array)
+    return "Decorated" if prediction[0] > 0.5 else "Undecorated"
+
+# Set up Streamlit interface with Christmas theme
+st.set_page_config(page_title="Tree Decoration Predictor", page_icon="🎄")
+
+# Custom CSS for Christmas theme
+st.markdown("""
+    <style>
+        body {
+            background-color: #fae1dc; /* Soft pink background */
+            color: #1b5e20; /* Deep green text */
+            font-family: 'Comic Sans MS', cursive, sans-serif;
+        }
+        .css-18e3th9 {
+            background-color: #d32f2f; /* Christmas red button */
+            color: white;
+        }
+        .css-1lcbm2e {
+            background-color: #388e3c; /* Christmas green button */
+            color: white;
+        }
+        .stButton>button {
+            background-color: #f44336; /* Red button color */
+            color: white;
+            border-radius: 12px;
+            padding: 10px;
+            font-size: 16px;
+        }
+        .stButton>button:hover {
+            background-color: #c62828; /* Darker red on hover */
+        }
+        .stMarkdown {
+            font-size: 18px;
+        }
+        .stTab {
+            font-size: 20px;
+            font-weight: bold;
+            color: #388e3c; /* Christmas green */
+        }
+        .stImage {
+            border: 2px solid #388e3c; /* Green border around images */
+        }
+    </style>
+""", unsafe_allow_html=True)
+
+# Title of the page
+st.title("🎄 Tree Decoration Predictor 🎄")
+
+# Create tabs for better organization
+tab1, tab2 = st.tabs(["Upload Image", "Tree Image URLs"])
+
+# Upload Image Tab
+with tab1:
+    uploaded_image = st.file_uploader("Upload an image of a tree", type=["jpg", "jpeg", "png"])
+
+    if uploaded_image:
+        image = Image.open(uploaded_image)
+        st.image(image, caption="Uploaded Tree Image", use_container_width=True)
+
+        if st.button("Predict Decoration"):
+            prediction = predict_decoration(image)
+            st.write(f"Prediction: {prediction}")
+
+# Tree Image URLs Tab
+with tab2:
+    st.subheader("🎄 Tree Image Samples 🎄")
+    st.markdown("""
+        View some of my decorated and undecorated tree samples for the Model here:
+        [View Trees](https://www.dropbox.com/scl/fo/cuzo12z39cxv6joz7gz2o/ACf5xSjT7nHqMRdgh21GYlc?raw=1)
+        
+        Download the tree samples pictures to test them on the model yourself here:
+        [Download Trees](https://www.dropbox.com/scl/fo/cuzo12z39cxv6joz7gz2o/ACf5xSjT7nHqMRdgh21GYlc?raw=1&dl=1)
+    """)
+    
+    # Add download link for images if needed
+    st.markdown("[Download the image list](https://raw.githubusercontent.com/willco-afk/tree-samples/main/tree_images.txt)")