Update app.py

app.py

@@ -8,6 +8,7 @@ import shutil
 import base64
 import pytz
 import hashlib
+import statistics
 
 # Load environment variables
 load_dotenv()
@@ -43,22 +44,23 @@ def analyze_image_with_hf(image_path):
     img = Image.open(image_path)
     detected_elements = []
     
-    # Enhanced mock detection based on image size and pixel data (simulating content analysis)
+    # Enhanced mock detection based on image size, pixel data, and color variance
     width, height = img.size
-    img_data = list(img.getdata())
-    gray_pixels = sum(1 for pixel in img_data if sum(pixel[:3]) / 3 < 128) / len(img_data)  # Proportion of dark pixels
     total_pixels = width * height
+    img_data = list(img.convert('RGB').getdata())
+    gray_pixels = sum(1 for pixel in img_data if sum(pixel[:3]) / 3 < 128) / len(img_data)  # Proportion of dark pixels
+    color_variance = statistics.variance([sum(pixel[:3]) / 3 for pixel in img_data]) if len(img_data) > 1 else 0  # Variance in brightness
     
     # Heuristic detection based on image characteristics
-    if total_pixels < 500000:  # Small image size, assume early planning stage
+    if total_pixels < 300000 or color_variance < 1000:  # Small size or low color variance, assume planning/design
         detected_elements.append("planning")
-    elif gray_pixels > 0.6 and width > 1000:  # High proportion of dark pixels, assume concrete/foundation
+    elif gray_pixels > 0.5 and total_pixels > 500000:  # High dark pixels and moderate size, assume foundation
         detected_elements.append("foundation")
-    elif gray_pixels > 0.4 and width > 1000 and height > 1000:  # Larger structure with columns, assume walls erected
+    elif gray_pixels > 0.3 and total_pixels > 1000000 and color_variance > 2000:  # Larger size with moderate dark pixels and high variance, assume walls
         detected_elements.append("walls")
-    elif any(keyword in os.path.basename(image_path).lower() for keyword in ["interior", "plumbing", "electrical", "ceiling"]) or (gray_pixels < 0.3 and total_pixels > 800000):  # Interior work or bright finished interior
+    elif gray_pixels < 0.2 or any(keyword in os.path.basename(image_path).lower() for keyword in ["interior", "plumbing", "electrical", "ceiling"]):  # Bright image or interior keywords
         detected_elements.extend(["interior", "electrical_wiring", "plumbing_pipes"])
-    else:  # Assume completed if no other clear indicators
+    else:  # Balanced colors and large size, assume completed
         detected_elements.extend(["roof", "windows", "doors", "cladding", "finished"])
 
     return detected_elements
@@ -180,7 +182,7 @@ def process_image(images, project_name):
             final_milestone = "Completed"
             percent_complete = 100
         else:
-            completed_tasks.extend(all_tasks["Planning"])  # Default to Planning if no specific stage detected
+            completed_tasks.extend(all_tasks["Planning"])  # Fallback to Planning if no clear stage
             final_milestone = "Planning"
             percent_complete = 10