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import streamlit as st |
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import tensorflow as tf |
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from tensorflow.keras.utils import load_img, img_to_array |
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from io import BytesIO |
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st.set_page_config(page_title="Forest Fire Detection", page_icon="🔥", layout="centered") |
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st.markdown( |
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""" |
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<div style='text-align: center; margin-bottom: 20px;'> |
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<h1>🔥 Forest Fire Detection Demo 🔥</h1> |
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<p style='font-size:20px;'>Upload a forest image and let AI detect fire!<br> |
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<span style='font-size:40px;'>🌲🌳🌴</span></p> |
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</div> |
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""", |
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unsafe_allow_html=True |
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) |
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st.sidebar.title("About") |
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st.sidebar.info( |
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"Upload a forest image to detect fire using a deep learning model. " |
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"This demo is powered by TensorFlow and Streamlit." |
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) |
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@st.cache_resource |
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def load_model(): |
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return tf.keras.models.load_model('FFD.keras') |
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model = load_model() |
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uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"]) |
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if uploaded_file is not None: |
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with st.spinner("Analyzing image..."): |
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img = load_img(BytesIO(uploaded_file.read()), target_size=(150, 150)) |
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img_array = img_to_array(img) / 255.0 |
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img_array = img_array.reshape(1, 150, 150, 3) |
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prediction = model.predict(img_array) |
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confidence = float(prediction[0][0]) |
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result = 'Fire Detected' if confidence > 0.5 else 'No Fire' |
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col1, col2 = st.columns([1.2, 1]) |
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with col1: |
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st.markdown("<div style='display:flex;justify-content:center;'>", unsafe_allow_html=True) |
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st.image(img, caption="Uploaded Image", width=260) |
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st.markdown("</div>", unsafe_allow_html=True) |
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with col2: |
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st.markdown( |
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f""" |
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<div style='background: rgb(38, 39, 48); border-radius: 16px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); padding: 24px; text-align: center; margin-top: 20px;'> |
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<h2 style='color:{"red" if result=="Fire Detected" else "green"}; margin-bottom: 10px;'> |
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{"🔥" if result=="Fire Detected" else "🌲"} {result} |
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</h2> |
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<div style='margin-bottom: 10px;'> |
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<progress value='{confidence:.2f}' max='1' style='width:80%; height:18px;'></progress> |
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</div> |
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<div style='font-size:18px; margin-bottom: 10px;'><b>Confidence:</b> {confidence:.2f}</div> |
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</div> |
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""", |
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unsafe_allow_html=True |
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) |
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st.markdown("<br>", unsafe_allow_html=True) |
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else: |
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st.info("Please upload an image to get started.") |
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st.markdown( |
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"<hr><div style='text-align:center;font-size:14px;'>" |
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"Made with ❤️ by CoderKP using Streamlit & TensorFlow" |
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"</div>", |
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unsafe_allow_html=True |
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) |
