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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+best_model.keras filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,53 @@
+import streamlit as st
+from tensorflow.keras.models import load_model
+import cv2
+import numpy as np
+from PIL import Image
+
+# Load the model
+model = load_model('best_model.keras')
+
+def preprocess_image(image):
+    # Resize the image as required by the model
+    img = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+    img = cv2.resize(img, (220, 220))  # Resize to match the model input
+    # Normalize the image
+    img = img.astype('float32') / 255.0
+    # Add a batch dimension
+    img = np.expand_dims(img, axis=0)
+    return img
+
+def run():
+    # Create title
+    st.title('Detecting Fire in Forest Images')
+
+    # Create a form for image input
+    with st.form('form_forest_fire_detection'):
+        # Image upload
+        uploaded_image = st.file_uploader('Upload an image', type=['jpg', 'jpeg', 'png'])
+        
+        # Submit button
+        submitted = st.form_submit_button('Detect Fire or No Fire')
+
+    if uploaded_image:
+        # Display the uploaded image
+        st.image(uploaded_image, caption='Uploaded Image', use_column_width=True)
+
+        if submitted:
+            # Preprocess the image
+            image = Image.open(uploaded_image)
+            preprocessed_image = preprocess_image(image)
+
+            # Predict using the model
+            prediction = model.predict(preprocessed_image)
+            
+            # For example, if prediction > 0.5 classify as 'No Fire', otherwise 'Fire'
+            fire_probability = prediction[0][0]
+            result = 'No Fire' if fire_probability > 0.5 else 'Fire'
+
+            st.write('## Prediction: ', result)
+            st.write('## Raw Prediction Output: ', prediction)
+
+
+if __name__ == '__main__':
+    run()

best_model.keras

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:587506ed2de9f937aab1fd196f0d644df71cb5106dbc643b875441a88bbf112f
+size 494759003

requirements.txt

@@ -0,0 +1,10 @@
+streamlit
+opencv-python
+seaborn
+matplotlib
+Pillow
+tensorflow
+numpy
+pandas
+scikit-learn
+datasets