Update app.py

app.py

@@ -8,8 +8,6 @@ import hashlib
 import shutil
 import base64
 import pytz
-import exifread
-import numpy as np
 
 # Load environment variables
 load_dotenv()
@@ -34,290 +32,164 @@ except Exception as e:
     raise
 
 # Valid milestones
-VALID_MILESTONES = ["Planning", "Foundation", "Walls Erected", "Completed"]
+VALID_MILESTONES = ["Foundation", "Walls Erected", "Planning", "Completed"]
 
-# Adjust the timezone
+# Adjust the timezone to your local timezone (replace 'Asia/Kolkata' with your timezone if needed)
 local_timezone = pytz.timezone("Asia/Kolkata")
 
-# Mock AI model for milestone detection
-def detect_milestone(image_path):
-    """
-    Detect construction milestone using filename, EXIF metadata, and image histogram.
-    Returns (milestone, confidence) tuple.
-    """
-    try:
-        # Initialize confidence score
-        confidence = 0.5  # Base confidence
-
-        # Extract EXIF metadata
-        with open(image_path, 'rb') as img_file:
-            tags = exifread.process_file(img_file, details=False)
-            image_date = tags.get('EXIF DateTimeOriginal', None)
-            image_size = os.path.getsize(image_path)
-
-        # Analyze filename keywords
-        filename = os.path.basename(image_path).lower()
-        keywords = {
-            "plan": ("Planning", 0.9),
-            "blueprint": ("Planning", 0.9),
-            "siteprep": ("Planning", 0.8),
-            "foundation": ("Foundation", 0.9),
-            "concrete": ("Foundation", 0.9),
-            "slab": ("Foundation", 0.8),
-            "wall": ("Walls Erected", 0.9),
-            "structure": ("Walls Erected", 0.8),
-            "beam": ("Walls Erected", 0.8),
-            "interior": ("Completed", 0.9),
-            "electrical": ("Completed", 0.9),
-            "plumbing": ("Completed", 0.9),
-            "finish": ("Completed", 0.9),
-            "completed": ("Completed", 0.95)
-        }
+# 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)
 
-        detected_milestone = "Planning"
-        for keyword, (milestone, keyword_conf) in keywords.items():
-            if keyword in filename:
-                detected_milestone = milestone
-                confidence = max(confidence, keyword_conf)
-                break
-
-        # Adjust based on image histogram (simulate scene detection)
-        img = Image.open(image_path).convert("RGB")
-        histogram = np.array(img.histogram())
-        # Normalize histogram
-        histogram = histogram / histogram.sum()
-        # Heuristic: High gray (concrete) suggests Foundation, high variety suggests Completed
-        gray_intensity = histogram[128:192].sum()  # Middle range for gray
-        color_variety = np.std(histogram)  # Standard deviation for color diversity
-
-        if gray_intensity > 0.3 and detected_milestone in ["Planning", "Foundation"]:
-            detected_milestone = "Foundation"
-            confidence = max(confidence, 0.7)
-        elif color_variety > 0.05 and detected_milestone in ["Planning", "Foundation", "Walls Erected"]:
-            detected_milestone = "Completed"
-            confidence = max(confidence, 0.8)
-
-        # Adjust based on timestamp (newer images indicate later milestones)
-        if image_date:
-            try:
-                img_datetime = datetime.strptime(str(image_date), "%Y:%m:%d %H:%M:%S")
-                days_old = (datetime.now() - img_datetime).days
-                if days_old < 30 and detected_milestone in ["Planning", "Foundation"]:
-                    detected_milestone = "Walls Erected"
-                    confidence = max(confidence, 0.75)
-                elif days_old < 15 and detected_milestone != "Completed":
-                    detected_milestone = "Completed"
-                    confidence = max(confidence, 0.85)
-            except ValueError:
-                pass
-
-        # Adjust confidence based on image size (larger images often from later stages)
-        if image_size > 5 * 1024 * 1024:
-            if detected_milestone != "Completed":
-                detected_milestone = "Completed"
-                confidence = max(confidence, 0.8)
-        elif image_size > 2 * 1024 * 1024 and detected_milestone == "Planning":
-            detected_milestone = "Foundation"
-            confidence = max(confidence, 0.7)
-
-        return detected_milestone, confidence
+    img_bytes = img.tobytes()
+    img_hash = int(hashlib.sha256(img_bytes).hexdigest(), 16)
 
-    except Exception as e:
-        print(f"Error in milestone detection: {str(e)}")
-        return "Planning", 0.5
+    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(images, project_name):
+def process_image(image, project_name):
     try:
-        if not images or len(images) == 0:
-            return "Error: Please upload at least one image.", "Pending", "", "", 0
-        if not project_name:
-            return "Error: Project name is required.", "Failure", "", "", 0
-
-        # Process each image
-        milestone_scores = {m: 0.0 for m in VALID_MILESTONES}
-        file_urls = []
-        for image in images:
-            # Validate image
-            img = Image.open(image)
-            image_size_mb = os.path.getsize(image) / (1024 * 1024)
-            if image_size_mb > 20:
-                return "Error: Image exceeds 20MB.", "Failure", "", "", 0
-            if not str(image).lower().endswith(('.jpg', '.jpeg', '.png')):
-                return "Error: Only JPG/PNG images supported.", "Failure", "", "", 0
-
-            # Save image temporarily
-            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 to base64
-            with open(saved_image_path, 'rb') as image_file:
-                image_data = base64.b64encode(image_file.read()).decode('utf-8')
-
-            # Upload to Salesforce
-            try:
-                content_version = {
-                    'Title': image_filename,
-                    'PathOnClient': saved_image_path,
-                    'VersionData': image_data
-                }
-                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}"
-                file_urls.append(file_url)
-            except Exception as e:
-                return f"Error: Failed to upload image to Salesforce - {str(e)}", "Failure", "", "", 0
-
-            # Detect milestone
-            milestone, confidence = detect_milestone(image)
-            milestone_scores[milestone] += confidence
-
-        # Determine final milestone (highest weighted score)
-        final_milestone = max(milestone_scores, key=milestone_scores.get)
-        milestone_completion_map = {
-            "Planning": 10,
-            "Foundation": 30,
-            "Walls Erected": 50,
-            "Completed": 100
+        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')
+
+        # Create the ContentVersion record in Salesforce
+        content_version = {
+            'Title': image_filename,
+            'PathOnClient': saved_image_path,
+            'VersionData': image_data
         }
-        percent_complete = milestone_completion_map.get(final_milestone, 0)
 
-        # Completion details
+        # Upload the file to Salesforce
+        try:
+            content_version_result = sf.ContentVersion.create(content_version)
+            content_version_id = content_version_result['id']
+
+            # Generate the public URL for the uploaded file in Salesforce
+            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)
         completion_details = {
             "Planning": {
                 "completed": [
-                    "Initial project outline and objectives established.",
-                    "Preliminary designs and architectural plans drafted.",
-                    "Stakeholder meetings and initial approvals completed."
+                    "Project outline and goals set, initial designs done."
                 ],
                 "not_completed": [
-                    "Detailed construction plans pending finalization.",
-                    "Permits and regulatory approvals not yet obtained.",
-                    "Contractor selection and procurement not complete."
+                    "Detailed plans, permits, and contractor hiring pending."
                 ]
             },
             "Foundation": {
                 "completed": [
-                    "Site preparation, including clearing and leveling, finished.",
-                    "Excavation for foundation completed.",
-                    "Concrete pouring for foundation done.",
-                    "Initial structural inspections passed."
+                    "Foundation work is complete, concrete is poured."
                 ],
                 "not_completed": [
-                    "Plumbing and electrical groundwork pending.",
-                    "Backfilling and site grading not done.",
-                    "Above-ground structural work not started."
+                    "Plumbing, electrical groundwork not yet done."
                 ]
             },
             "Walls Erected": {
                 "completed": [
-                    "Concrete framework, including columns and beams, in place.",
-                    "All structural walls erected and stabilized.",
-                    "Temporary scaffolding and safety measures installed.",
-                    "Initial inspections for structural integrity completed."
+                    "All structural walls are up."
                 ],
                 "not_completed": [
-                    "Roofing installation and weatherproofing pending.",
-                    "Windows, doors, and exterior cladding not installed.",
-                    "Interior walls, electrical, and plumbing not implemented."
+                    "Roofing, windows, and internal walls are not yet finished."
                 ]
             },
             "Completed": {
                 "completed": [
-                    "Concrete framework fully constructed.",
-                    "Exterior walls, windows, and cladding installed.",
-                    "Interior work, including electrical and plumbing, completed.",
-                    "Finishing touches, such as flooring and painting, done.",
-                    "All phases finished, including final inspections."
+                    "All phases of the project are finished, including final touches."
                 ],
                 "not_completed": [
-                    "No pending work as project is fully completed."
+                    "There should be no more pending work."
                 ]
             }
         }
 
-        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])
-
-        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>
-            <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;">{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>
-
-            <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>
-                <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;">
-                <summary style="color: #2c3e50; font-weight: bold;">Completed Tasks</summary>
-                <ul style="padding-left: 20px;">
-                    {completed_html}
-                </ul>
-            </details>
-
-            <details style="margin-bottom: 20px;">
-                <summary style="color: #2c3e50; font-weight: bold;">Not Completed Tasks</summary>
-                <ul style="padding-left: 20px;">
-                    {not_completed_html}
-                </ul>
-            </details>
-
-            <h3 style="color: #2c3e50;">Uploaded Images</h3>
-            <ul style="padding-left: 20px;">
-                {"".join([f'<li><a href="{url}" target="_blank">{url}</a></li>' for url in file_urls])}
-            </ul>
-        </div>
-        """
+        # Get the detailed completion information based on the detected milestone
+        completed_work = "\n".join([f"{idx+1}. {task}" for idx, task in enumerate(completion_details[milestone]["completed"])])
+        not_completed_work = "\n".join([f"{idx+1}. {task}" for idx, task in enumerate(completion_details[milestone]["not_completed"])])
 
-        now = datetime.now(local_timezone)
-        local_time = now.strftime("%Y-%m-%dT%H:%M:%S") + now.strftime("%z")[:-2] + ":" + now.strftime("%z")[-2:]
+        # Adjust the current time to local timezone
+        local_time = datetime.now(local_timezone).strftime("%Y-%m-%dT%H:%M:%S%z")  # Corrected ISO 8601 format with timezone
 
+        # Create the Salesforce record with the image URL and AI prediction
         record = {
             "Name__c": project_name,
-            "Current_Milestone__c": final_milestone,
+            "Current_Milestone__c": milestone,
             "Completion_Percentage__c": percent_complete,
-            "Last_Updated_On__c": local_time,
+            "Last_Updated_On__c": local_time,  # Corrected format for Salesforce
             "Upload_Status__c": "Success",
-            "Comments__c": f"{final_milestone} (based on {len(images)} images)",
-            "Last_Updated_Image__c": file_urls[-1] if file_urls else ""
+            "Comments__c": f"{milestone} with {confidence_score*100}% confidence",  # Removed "AI Prediction:"
+            "Last_Updated_Image__c": file_url
         }
 
+        # Upload the record to Salesforce
         try:
             sf.Construction__c.create(record)
         except Exception as e:
             return f"Error: Failed to update Salesforce - {str(e)}", "Failure", "", "", 0
 
-        return result_html, "Success", final_milestone, f"{percent_complete}%"
+        # Return the detailed result in the desired format
+        result = f"""
+        Completed:
+        
+        {completed_work}
+
+        Not Completed:
+
+        {not_completed_work}
+
+        Confidence Score: {confidence_score * 100}%
+        """
+
+        return result, "Success", milestone, f"Confidence Score: {confidence_score}", percent_complete
 
     except Exception as e:
-        return f"Error: {str(e)}", "Failure", "", "", "0%"
+        return f"Error: {str(e)}", "Failure", "", "", 0
 
-# Gradio UI
+# Gradio UI with added styling
 with gr.Blocks(css="""
     .gradio-container {
         background-color: #f0f4f8;
-        font-family: Arial, sans-serif;
+        font-family: Arial;
     }
     .title {
         color: #2c3e50;
@@ -337,50 +209,24 @@ with gr.Blocks(css="""
     .gradio-container .button {
         display: block;
         margin: 0 auto;
-        background-color: #3498db;
-        color: white;
-        border: none;
-        padding: 10px 20px;
-        border-radius: 5px;
-        cursor: pointer;
-    }
-    .gradio-container .button:hover {
-        background-color: #2980b9;
-    }
-    progress::-webkit-progress-value {
-        background-color: #2ecc71;
-        border-radius: 5px;
-    }
-    progress::-webkit-progress-bar {
-        background-color: #ecf0f1;
-        border-radius: 5px;
-    }
-    details summary {
-        cursor: pointer;
-        padding: 10px;
-        background-color: #ecf0f1;
-        border-radius: 5px;
-    }
-    details ul {
-        margin-top: 10px;
     }
 """) as demo:
-    gr.Markdown("<h1 class='title'>Construction Progress Analyzer</h1>")
+    gr.Markdown("<h1 class='title'></h1>")
     with gr.Row():
-        image_input = gr.Files(type="filepath", label="Upload Construction Site Photos (JPG/PNG, ≤ 20MB)")
+        image_input = gr.Image(type="filepath", label="Upload Construction Site Photo (JPG/PNG, ≤ 20MB)")
         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")
+    output_text = gr.Textbox(label="Result")
     upload_status = gr.Textbox(label="Upload Status")
     milestone = gr.Textbox(label="Detected Milestone")
-    progress = gr.Textbox(label="Completion Percentage", interactive=False)
+    confidence = gr.Textbox(label="Confidence Score")
+    progress = gr.Slider(0, 100, label="Completion Percentage", interactive=False, value=0)
 
     submit_button.click(
         fn=process_image,
         inputs=[image_input, project_name_input],
-        outputs=[output_html, upload_status, milestone, progress]
+        outputs=[output_text, upload_status, milestone, confidence, progress]
     )
 
-if __name__ == "__main__":
-    demo.launch()
+demo.launch(share=True)