Update app.py

app.py

@@ -2,16 +2,38 @@ from PIL import Image
 import numpy as np
 import streamlit as st
 
+from PIL import Image
+import numpy as np
+
 # Define function to process uploaded image
 def process_image(image):
     # Convert image to numpy array
     img_array = np.array(image)
 
     # Dummy sidewalk segmentation (replace with your actual segmentation algorithm)
-    segmentation_result = np.zeros_like(img_array)
-    segmentation_result[:, :, 1] = 255  # Set sidewalk area to green (RGB: 0, 255, 0)
+    patch_size = 128
+    step = 128
+
+    all_img_patches = []
+
+    for i in range(0, img_array.shape[0] - patch_size + 1, step):
+        for j in range(0, img_array.shape[1] - patch_size + 1, step):
+            single_patch_img = img_array[i:i + patch_size, j:j + patch_size]
+            all_img_patches.append(single_patch_img)
+
+    images = np.array(all_img_patches)
+
+    # Perform your actual image processing here
+    # Replace the code below with your segmentation algorithm or any other processing you need
+    # This is just a dummy example to show how to process the image
+    processed_images = []
+    for img in images:
+        processed_image = np.mean(img, axis=-1)  # Example: Convert to grayscale
+        processed_images.append(processed_image)
+
+    processed_images = np.array(processed_images)
 
-    return segmentation_result
+    return processed_images
 
 # Define Shiny app
 def main():