Update app.py

app.py

@@ -51,19 +51,24 @@ milestone_percentage_map = {
 # Adjust the timezone to your local timezone
 local_timezone = pytz.timezone("Asia/Kolkata")
 
-# AI model prediction (for simulation)
+# Enhanced AI model prediction with heuristic for completion
 def mock_ai_model(image):
     img = image.convert("RGB")
     max_size = 1024
     img.thumbnail((max_size, max_size), Image.Resampling.LANCZOS)
 
+    # Simple heuristic for Final Completion (100%)
+    img_data = list(img.getdata())
+    color_variation = max(max(pixel) - min(pixel) for pixel in img_data)  # Measure color uniformity
+    if color_variation < 20 and all(sum(pixel) / 3 > 200 for pixel in img_data[:1000]):  # Bright and uniform
+        return "Final Completion", 100, 0.95
+
+    # Fallback to hash-based simulation
     img_bytes = img.tobytes()
     img_hash = int(hashlib.sha256(img_bytes).hexdigest(), 16)
 
-    # Assign milestone based on hash (for simulation)
     milestone_index = img_hash % len(milestone_percentage_map)
     milestone = list(milestone_percentage_map.keys())[milestone_index]
-
     confidence_raw = 0.85 + ((img_hash % 1000) / 1000) * (0.95 - 0.85)
     confidence_score = round(confidence_raw, 2)
 
@@ -141,11 +146,11 @@ def process_image(images, project_name, project_type):
         record = {
             "Name__c": project_name,
             "Project_Type__c": project_type,
-            "Completion_Percentage__c": total_percent_complete,  # Updated to total percentage
+            "Completion_Percentage__c": total_percent_complete,
             "Current_Milestone__c": all_milestones_str,
             "Last_Updated_On__c": local_time,
             "Upload_Status__c": "Success",
-            "Comments__c": f"Project {project_name} at {dominant_milestone or 'no milestone detected'} with {total_percent_complete}% completion",
+            "Comments__c": f"Project {project_name} with {total_percent_complete}% completion",
             "Last_Updated_Image__c": dominant_image_url or ""
         }
 
@@ -159,13 +164,11 @@ def process_image(images, project_name, project_type):
         for result in results:
             output_html += f"<li>{result}</li>"
         output_html += "</ul>"
-        output_html += f"<p><strong>Project Record Created:</strong> {project_name} - {dominant_milestone or 'No milestone detected'} (Total: {total_percent_complete}%, Milestones: {all_milestones_str})</p>"
+        output_html += f"<p><strong>Project Record Created:</strong> {project_name} (Total: {total_percent_complete}%)</p>"
         output_html += f"<p><strong>Note:</strong> Only the image with the highest completion percentage is stored in Salesforce due to field length constraints.</p>"
-        if not dominant_milestone:
-            output_html += "<p><strong>Warning:</strong> No valid milestone was set as dominant due to restricted picklist constraints (prior to conversion).</p>"
         output_html += "</div>"
 
-        return output_html, "Success", dominant_milestone or "", f"Max Confidence: {max([conf for _, conf in milestone_confidences], default=0)}", f"{total_percent_complete}%"
+        return output_html, "Success", "", f"Max Confidence: {max([conf for _, conf in milestone_confidences], default=0)}", f"{total_percent_complete}%"
 
     except Exception as e:
         return f"<p style='color: red;'>Error: {str(e)}</p>", "Failure", "", "", "0%"