Update app.py

app.py

@@ -31,8 +31,14 @@ except Exception as e:
     print(f"Salesforce connection failed: {str(e)}")
     raise
 
-# Valid milestones
+# Valid milestones in sequential order
 VALID_MILESTONES = ["Planning", "Foundation", "Walls Erected", "Completed"]
+MILESTONE_WEIGHTS = {
+    "Planning": 1,
+    "Foundation": 2,
+    "Walls Erected": 3,
+    "Completed": 4
+}
 
 # Adjust the timezone to your local timezone
 local_timezone = pytz.timezone("Asia/Kolkata")
@@ -42,9 +48,13 @@ def process_image(images, project_name):
     try:
         if not images or len(images) == 0:
             return "Error: Please upload at least one image to proceed.", "Pending", "", "", 0
+        if len(images) < 2:
+            return "Error: Please upload at least one indoor and one outdoor image for accurate milestone detection.", "Pending", "", "", 0
 
         # Process each image
-        milestones = []
+        image_milestones = []
+        image_types = []
+        
         for image in images:
             img = Image.open(image)
             image_size_mb = os.path.getsize(image) / (1024 * 1024)
@@ -80,23 +90,44 @@ def process_image(images, project_name):
             except Exception as e:
                 return f"Error: Failed to upload image to Salesforce - {str(e)}", "Failure", "", "", 0
 
-            # Mock AI model to detect milestone based on image content
-            img_bytes = img.tobytes()
-            img_hash = int(hashlib.sha256(img_bytes).hexdigest(), 16)
-            milestone_index = img_hash % len(VALID_MILESTONES)
-            milestone = VALID_MILESTONES[milestone_index]
+            # Classify image as indoor or outdoor based on filename
+            filename_lower = os.path.basename(image).lower()
+            is_indoor = any(keyword in filename_lower for keyword in ["indoor", "interior", "inside"])
+            image_type = "Indoor" if is_indoor else "Outdoor"
+            image_types.append(image_type)
 
-            # Adjust milestone detection based on internal/external features
-            if milestone == "Walls Erected" and any("interior" in img_text.lower() for img_text in [os.path.basename(image)] if img_text):
-                if any(keyword in str(os.path.basename(image)).lower() for keyword in ["electrical", "plumbing", "wiring", "pipes"]):
-                    milestone = "Completed"
-                else:
-                    milestone = "Walls Erected"
+            # Enhanced milestone detection logic
+            # Use filename keywords to simulate content analysis
+            milestone = "Planning"  # Default
+            if any(keyword in filename_lower for keyword in ["site", "clearing", "planning", "design"]):
+                milestone = "Planning"
+            elif any(keyword in filename_lower for keyword in ["foundation", "footing", "slab", "excavation"]):
+                milestone = "Foundation"
+            elif any(keyword in filename_lower for keyword in ["wall", "structure", "beam", "column", "facade"]):
+                milestone = "Walls Erected"
+            elif any(keyword in filename_lower for keyword in ["electrical", "plumbing", "hvac", "finish", "completed"]):
+                milestone = "Completed"
 
-            milestones.append(milestone)
+            # Adjust milestone based on image type
+            if image_type == "Indoor" and milestone in ["Planning", "Foundation"]:
+                milestone = "Walls Erected"  # Indoor images imply at least walls are up
+            elif image_type == "Outdoor" and milestone == "Completed":
+                milestone = "Walls Erected"  # Outdoor completion needs indoor confirmation
+
+            image_milestones.append(milestone)
+
+        # Validate and aggregate milestones
+        if not any(t == "Indoor" for t in image_types) or not any(t == "Outdoor" for t in image_types):
+            return "Error: Both indoor and outdoor images are required for accurate milestone detection.", "Pending", "", "", 0
+
+        # Ensure sequential milestone logic
+        max_milestone_index = max(MILESTONE_WEIGHTS[m] for m in image_milestones)
+        final_milestone = [m for m, w in MILESTONE_WEIGHTS.items() if w == max_milestone_index][0]
+
+        # If "Completed" is detected, ensure indoor images confirm it
+        if final_milestone == "Completed" and not any(m == "Completed" and t == "Indoor" for m, t in zip(image_milestones, image_types)):
+            final_milestone = "Walls Erected"
 
-        # Determine overall milestone (most advanced detected)
-        final_milestone = max(set(milestones), key=milestones.count) if milestones else "Planning"
         milestone_completion_map = {
             "Planning": 10,
             "Foundation": 30,
@@ -164,6 +195,9 @@ def process_image(images, project_name):
         completed_html = "".join([f'<li style="color: green;">✔ {task}</li>' for task in completed_tasks])
         not_completed_html = "".join([f'<li style="color: red;">✘ {task}</li>' for task in not_completed_tasks])
 
+        # Enhanced result HTML with image type feedback
+        image_summary = "".join([f'<li>{os.path.basename(img)} ({img_type}): {milestone}</li>' for img, img_type, milestone in zip(images, image_types, image_milestones)])
+        
         result_html = f"""
         <div style="font-family: Arial, sans-serif; padding: 20px; background-color: #f9f9f9; border-radius: 10px;">
             <h2 style="color: #2c3e50; text-align: center;">Project Summary</h2>
@@ -179,6 +213,11 @@ def process_image(images, project_name):
                 </div>
             </div>
 
+            <h3 style="color: #2c3e50;">Image Analysis</h3>
+            <ul style="padding-left: 20px; margin-bottom: 20px;">
+                {image_summary}
+            </ul>
+
             <h3 style="color: #2c3e50;">Milestone Timeline</h3>
             <div style="display: flex; justify-content: space-between; align-items: center; margin-bottom: 20px;">
                 <span style="color: {'#2ecc71' if final_milestone == 'Planning' else '#bdc3c7'};">Planning</span>
@@ -264,7 +303,7 @@ with gr.Blocks(css="""
         background-color: #2ecc71;
         border-radius: 5px;
     }
-    progress::-webkit-progress-bar {
+    .gradio-container progress::-webkit-progress-bar {
         background-color: #ecf0f1;
         border-radius: 5px;
     }
@@ -279,6 +318,12 @@ with gr.Blocks(css="""
     }
 """) as demo:
     gr.Markdown("<h1 class='title'>Construction Progress Analyzer</h1>")
+    gr.Markdown("""
+        <p style='text-align: center; color: #34495e;'>
+            Upload at least one indoor and one outdoor image of the construction site (JPG/PNG, ≤ 20MB each).<br>
+            Use descriptive filenames (e.g., 'outdoor_foundation.jpg', 'indoor_electrical.jpg') for best results.
+        </p>
+    """)
     with gr.Row():
         image_input = gr.Files(type="filepath", label="Upload Construction Site Photos (JPG/PNG, ≤ 20MB)")
         project_name_input = gr.Textbox(label="Project Name (Required)", placeholder="e.g. Project_12345")
@@ -295,4 +340,4 @@ with gr.Blocks(css="""
         outputs=[output_html, upload_status, milestone, progress]
     )
 
-demo.launch(share=True)
+demo.launch(share=True)