Update app.py

app.py

@@ -1,71 +1,30 @@
-from flask import Flask, render_template, request, jsonify
-import os
+import streamlit as st
 from PIL import Image
 import numpy as np
 
-app = Flask(__name__)
+st.title("Tree Counter App")
 
-# Ensure uploads directory exists
-if not os.path.exists('uploads'):
-    os.makedirs('uploads')
+# Upload image via Streamlit
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png", "jpeg"])
 
-# Define the HTML template for the Tree Counter page
-@app.route('/')
-def index():
-    return render_template('index.html')
-
-# Define the API endpoint for uploading images
-@app.route('/upload_image', methods=['POST'])
-def upload_image():
-    if 'image' not in request.files:
-        return jsonify({'message': 'No file part'}), 400
-    
-    image = request.files['image']
-    if image.filename == '':
-        return jsonify({'message': 'No selected file'}), 400
-    
-    try:
-        # Save the uploaded image
-        image_path = os.path.join('uploads', 'image.jpg')
-        image.save(image_path)
-        
-        # Open and process the image
-        img = Image.open(image_path)
-        width, height = img.size
-        if width > 1024 or height > 1024:
-            return jsonify({'message': 'Image is too large. Please crop it.'}), 400
-        else:
-            # Simulate tree detection using YOLO8 model
-            # Replace this with actual model implementation
-            trees = np.random.randint(0, 100)
-            return jsonify({'message': f'Number of Trees: {trees}'})
-    except Exception as e:
-        return jsonify({'message': f'Error processing image: {str(e)}'}), 500
-
-# Define the API endpoint for cropping images
-@app.route('/crop_image', methods=['POST'])
-def crop_image():
-    if 'image' not in request.files:
-        return jsonify({'message': 'No file part'}), 400
+if uploaded_file is not None:
+    # Open the image
+    img = Image.open(uploaded_file)
+    st.image(img, caption="Uploaded Image.", use_column_width=True)
     
-    image = request.files['image']
-    if image.filename == '':
-        return jsonify({'message': 'No selected file'}), 400
+    # Check image dimensions
+    width, height = img.size
+    if width > 1024 or height > 1024:
+        st.error("Image is too large. Please crop it.")
+    else:
+        # Simulate tree detection using random number
+        trees = np.random.randint(0, 100)
+        st.success(f"Number of Trees: {trees}")
 
-    try:
-        # Save the uploaded image
-        image_path = os.path.join('uploads', 'image.jpg')
-        image.save(image_path)
-        
-        # Open and crop the image
-        img = Image.open(image_path)
-        cropped_img = img.crop((0, 0, min(1024, img.width), min(1024, img.height)))
-        
-        # Save the cropped image
-        cropped_img.save(os.path.join('uploads', 'cropped_image.jpg'))
-        return jsonify({'message': 'Image cropped successfully'})
-    except Exception as e:
-        return jsonify({'message': f'Error cropping image: {str(e)}'}), 500
+# Image cropping functionality
+if uploaded_file is not None and st.button("Crop Image to 1024x1024"):
+    cropped_img = img.crop((0, 0, min(1024, img.width), min(1024, img.height)))
+    st.image(cropped_img, caption="Cropped Image.", use_column_width=True)
+    cropped_img.save("cropped_image.jpg")
+    st.success("Image cropped successfully.")
 
-if __name__ == '__main__':
-    app.run(debug=True)