Create main.py

main.py

@@ -0,0 +1,57 @@
+import streamlit as st
+from PIL import Image
+import numpy as np
+from tensorflow.keras.models import load_model
+
+model = load_model('yolo8_model.h5')
+
+def detect_trees(image):
+    # Preprocess the image
+    img = np.array(image)
+    img = img / 255.0
+
+    # Make predictions
+    predictions = model.predict(img)
+
+    # Process the predictions
+    trees = []
+    for prediction in predictions:
+        x, y, w, h, confidence = prediction
+        if confidence > 0.5:
+            trees.append((x, y, w, h))
+
+    return trees
+
+def main():
+    st.title('Tree Counter')
+    st.write('Upload an image to count the trees')
+
+    col1, col2, col3 = st.columns([1, 1, 1])
+    with col1:
+        st.button('Detect Trees')
+    with col2:
+        st.button('Crop Image')
+    with col3:
+        st.button('Reset')
+
+    uploaded_file = st.file_uploader('Choose an image', type=['jpg', 'png', 'jpeg'])
+    if uploaded_file is not None:
+        image = Image.open(uploaded_file)
+        st.image(image, caption='Uploaded Image')
+
+        width, height = image.size
+        if width > 1024 or height > 1024:
+            if st.button('Crop Image'):
+                # Crop the image
+                cropped_image = image.crop((100, 100, 300, 300))
+                st.image(cropped_image, caption='Cropped Image')
+        else:
+            if st.button('Detect Trees'):
+                trees = detect_trees(image)
+                st.write(f'Number of Trees: {len(trees)}')
+
+    st.write('Google Earth Integration')
+    st.map()
+
+if __name__ == '__main__':
+    main()