Update app.py

app.py

@@ -32,26 +32,32 @@ except Exception as e:
 # Valid milestones
 VALID_MILESTONES = ["Foundation", "Walls Erected", "Planning", "Completed"]
 
-# Updated deterministic AI prediction based on image hash
+# Updated deterministic AI prediction with accurate completion percentages
 def mock_ai_model(image):
     img = image.convert("RGB")
     max_size = 1024
     img.thumbnail((max_size, max_size), Image.Resampling.LANCZOS)
 
-    # Convert image bytes to a hash value
+    # Hash image bytes for deterministic output
     img_bytes = img.tobytes()
     img_hash = int(hashlib.sha256(img_bytes).hexdigest(), 16)
 
-    # Use the hash to deterministically pick milestone and percentages
     milestone_index = img_hash % len(VALID_MILESTONES)
-    completion_choices = [10, 30, 50, 80, 100]
-    completion_index = (img_hash // 10) % len(completion_choices)
+    milestone = VALID_MILESTONES[milestone_index]
+
+    # Map milestones to fixed completion percentages
+    milestone_completion_map = {
+        "Planning": 10,
+        "Foundation": 30,
+        "Walls Erected": 50,
+        "Completed": 100,
+    }
+    completion_percent = milestone_completion_map.get(milestone, 0)
+
+    # Deterministic confidence score between 0.85 and 0.95
     confidence_raw = 0.85 + ((img_hash % 1000) / 1000) * (0.95 - 0.85)
     confidence_score = round(confidence_raw, 2)
 
-    milestone = VALID_MILESTONES[milestone_index]
-    completion_percent = completion_choices[completion_index]
-
     return milestone, completion_percent, confidence_score
 
 # Gradio function