Update app.py

app.py

@@ -32,80 +32,81 @@ except Exception as e:
     raise
 
 # Valid milestones
-VALID_MILESTONES = ["Foundation", "Walls Erected", "Planning", "Completed"]
+VALID_MILESTONES = ["Planning", "Foundation", "Walls Erected", "Completed"]
 
 # Adjust the timezone to your local timezone
 local_timezone = pytz.timezone("Asia/Kolkata")
 
-# Deterministic AI prediction with fixed confidence and percent
-def mock_ai_model(image):
-    img = image.convert("RGB")
-    max_size = 1024
-    img.thumbnail((max_size, max_size), Image.Resampling.LANCZOS)
-
-    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]
-
-    milestone_completion_map = {
-        "Planning": 10,
-        "Foundation": 30,
-        "Walls Erected": 50,
-        "Completed": 100,
-    }
-    completion_percent = milestone_completion_map.get(milestone, 0)
-
-    confidence_raw = 0.85 + ((img_hash % 1000) / 1000) * (0.95 - 0.85)
-    confidence_score = round(confidence_raw, 2)
-
-    return milestone, completion_percent, confidence_score
-
 # Image processing and Salesforce upload
-def process_image(image, project_name):
+def process_image(images, project_name):
     try:
-        if image is None:
-            return "Error: Please upload an image to proceed.", "Pending", "", "", 0
-
-        img = Image.open(image)
-        image_size_mb = os.path.getsize(image) / (1024 * 1024)
-        if image_size_mb > 20:
-            return "Error: Image size exceeds 20MB.", "Failure", "", "", 0
-        if not str(image).lower().endswith(('.jpg', '.jpeg', '.png')): 
-            return "Error: Only JPG/PNG images are supported.", "Failure", "", "", 0
-
-        # Save image to public folder temporarily before uploading to Salesforce
-        upload_dir = "public_uploads"
-        os.makedirs(upload_dir, exist_ok=True)
-        unique_id = datetime.now().strftime("%Y%m%d%H%M%S")
-        image_filename = f"{unique_id}_{os.path.basename(image)}"
-        saved_image_path = os.path.join(upload_dir, image_filename)
-        shutil.copy(image, saved_image_path)
-
-        # Convert image to base64 before uploading to Salesforce
-        with open(saved_image_path, 'rb') as image_file:
-            image_data = base64.b64encode(image_file.read()).decode('utf-8')
+        if not images or not isinstance(images, list):
+            return "Error: Please upload at least one image to proceed.", "Pending", "", "", 0
+
+        # Process each image
+        milestones = []
+        for image in images:
+            img = Image.open(image)
+            image_size_mb = os.path.getsize(image) / (1024 * 1024)
+            if image_size_mb > 20:
+                return "Error: One or more images exceed 20MB.", "Failure", "", "", 0
+            if not str(image).lower().endswith(('.jpg', '.jpeg', '.png')):
+                return "Error: Only JPG/PNG images are supported.", "Failure", "", "", 0
+
+            # Save image to public folder temporarily before uploading to Salesforce
+            upload_dir = "public_uploads"
+            os.makedirs(upload_dir, exist_ok=True)
+            unique_id = datetime.now().strftime("%Y%m%d%H%M%S")
+            image_filename = f"{unique_id}_{os.path.basename(image)}"
+            saved_image_path = os.path.join(upload_dir, image_filename)
+            shutil.copy(image, saved_image_path)
+
+            # Convert image to base64 before uploading to Salesforce
+            with open(saved_image_path, 'rb') as image_file:
+                image_data = base64.b64encode(image_file.read()).decode('utf-8')
+
+            # Create the ContentVersion record in Salesforce
+            content_version = {
+                'Title': image_filename,
+                'PathOnClient': saved_image_path,
+                'VersionData': image_data
+            }
 
-        # Create the ContentVersion record in Salesforce
-        content_version = {
-            'Title': image_filename,
-            'PathOnClient': saved_image_path,
-            'VersionData': image_data
+            # Upload the file to Salesforce
+            try:
+                content_version_result = sf.ContentVersion.create(content_version)
+                content_version_id = content_version_result['id']
+                file_url = f"https://sathkruthatechsolutionspri8-dev-ed.develop.lightning.force.com/{content_version_id}"
+            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]
+
+            # Adjust milestone detection based on internal/external features
+            if milestone == "Walls Erected" and any("interior" in img_text.lower() for img_text in [img.filename] if img_text):
+                # Check for visible internal works like electrical/plumbing
+                if any(keyword in str(img).lower() for keyword in ["electrical", "plumbing", "wiring", "pipes"]):
+                    milestone = "Completed"  # Upgrade to Completed if internal works are detected
+                else:
+                    milestone = "Walls Erected"  # Retain if no internal works visible
+
+            milestones.append(milestone)
+
+        # 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,
+            "Walls Erected": 50,
+            "Completed": 100,
         }
+        percent_complete = milestone_completion_map.get(final_milestone, 0)
 
-        # Upload the file to Salesforce
-        try:
-            content_version_result = sf.ContentVersion.create(content_version)
-            content_version_id = content_version_result['id']
-            file_url = f"https://sathkruthatechsolutionspri8-dev-ed.develop.lightning.force.com/{content_version_id}"
-        except Exception as e:
-            return f"Error: Failed to upload image to Salesforce - {str(e)}", "Failure", "", "", 0
-
-        # AI-based milestone and completion prediction
-        milestone, percent_complete, confidence_score = mock_ai_model(img)
-
-        # Detailed Completion Breakdown (based on detected milestone)
+        # Detailed Completion Breakdown based on final milestone
         completion_details = {
             "Planning": {
                 "completed": [
@@ -159,9 +160,8 @@ def process_image(image, project_name):
             }
         }
 
-        # Format the completed and not completed tasks as HTML for collapsible sections
-        completed_tasks = completion_details[milestone]["completed"]
-        not_completed_tasks = completion_details[milestone]["not_completed"]
+        completed_tasks = completion_details[final_milestone]["completed"]
+        not_completed_tasks = completion_details[final_milestone]["not_completed"]
 
         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])
@@ -173,26 +173,21 @@ def process_image(image, project_name):
             <div style="display: flex; justify-content: space-around; margin-bottom: 20px;">
                 <div style="text-align: center;">
                     <h3 style="color: #34495e;">Detected Milestone</h3>
-                    <p style="font-size: 18px; font-weight: bold;">{milestone}</p>
+                    <p style="font-size: 18px; font-weight: bold;">{final_milestone}</p>
                 </div>
                 <div style="text-align: center;">
                     <h3 style="color: #34495e;">Completion</h3>
                     <progress value="{percent_complete}" max="100" style="width: 200px; height: 20px;"></progress>
                     <p>{percent_complete}%</p>
                 </div>
-                <div style="text-align: center;">
-                    <h3 style="color: #34495e;">Confidence Score</h3>
-                    <p style="font-size: 18px; font-weight: bold;">{confidence_score * 100}%</p>
-                    <small>The AI is {confidence_score * 100}% confident that this image represents the {milestone} stage.</small>
-                </div>
             </div>
 
             <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 milestone == 'Planning' else '#bdc3c7'};">Planning</span>
-                <span style="color: {'#2ecc71' if milestone == 'Foundation' else '#bdc3c7'};">Foundation</span>
-                <span style="color: {'#2ecc71' if milestone == 'Walls Erected' else '#bdc3c7'};">Walls Erected</span>
-                <span style="color: {'#2ecc71' if milestone == 'Completed' else '#bdc3c7'};">Completed</span>
+                <span style="color: {'#2ecc71' if final_milestone == 'Planning' else '#bdc3c7'};">Planning</span>
+                <span style="color: {'#2ecc71' if final_milestone == 'Foundation' else '#bdc3c7'};">Foundation</span>
+                <span style="color: {'#2ecc71' if final_milestone == 'Walls Erected' else '#bdc3c7'};">Walls Erected</span>
+                <span style="color: {'#2ecc71' if final_milestone == 'Completed' else '#bdc3c7'};">Completed</span>
             </div>
 
             <details style="margin-bottom: 20px;">
@@ -215,14 +210,14 @@ def process_image(image, project_name):
         now = datetime.now(local_timezone)
         local_time = now.strftime("%Y-%m-%dT%H:%M:%S") + now.strftime("%z")[:-2] + ":" + now.strftime("%z")[-2:]
 
-        # Create the Salesforce record
+        # Create the Salesforce record (removing confidence score)
         record = {
             "Name__c": project_name,
-            "Current_Milestone__c": milestone,
+            "Current_Milestone__c": final_milestone,
             "Completion_Percentage__c": percent_complete,
             "Last_Updated_On__c": local_time,
             "Upload_Status__c": "Success",
-            "Comments__c": f"{milestone} with {confidence_score*100}% confidence",
+            "Comments__c": f"{final_milestone}",
             "Last_Updated_Image__c": file_url
         }
 
@@ -231,7 +226,7 @@ def process_image(image, project_name):
         except Exception as e:
             return f"Error: Failed to update Salesforce - {str(e)}", "Failure", "", "", 0
 
-        return result_html, "Success", milestone, f"Confidence Score: {confidence_score}", f"{percent_complete}%"
+        return result_html, "Success", final_milestone, "", f"{percent_complete}%"
 
     except Exception as e:
         return f"Error: {str(e)}", "Failure", "", "", "0%"
@@ -290,14 +285,14 @@ with gr.Blocks(css="""
 """) as demo:
     gr.Markdown("<h1 class='title'>Construction Progress Analyzer</h1>")
     with gr.Row():
-        image_input = gr.Image(type="filepath", label="Upload Construction Site Photo (JPG/PNG, ≤ 20MB)")
+        image_input = gr.Image(type="filepath", label="Upload Construction Site Photos (JPG/PNG, ≤ 20MB)", file_count="multiple")
         project_name_input = gr.Textbox(label="Project Name (Required)", placeholder="e.g. Project_12345")
 
     submit_button = gr.Button("Process Image")
     output_html = gr.HTML(label="Result")  # Changed to HTML for richer output
     upload_status = gr.Textbox(label="Upload Status")
     milestone = gr.Textbox(label="Detected Milestone")
-    confidence = gr.Textbox(label="Confidence Score")
+    confidence = gr.Textbox(label="Confidence Score")  # Kept for compatibility, but unused
     progress = gr.Textbox(label="Completion Percentage", interactive=False)
 
     submit_button.click(