Update app.py

app.py

@@ -1,18 +1,18 @@
-import random
-import os
-import shutil
-import base64
+import os  # Import the os module
 import gradio as gr
 import cv2
 import numpy as np
 import mediapipe as mp
+from sklearn.linear_model import LinearRegression
+import random
+import base64
+import joblib
+from datetime import datetime
+import shutil
 from reportlab.lib.pagesizes import letter
-from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Image as PDFImage
+from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
 from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
 from reportlab.lib import colors
-from datetime import datetime
-import joblib
-from sklearn.linear_model import LinearRegression
 
 # Initialize the face mesh model
 mp_face_mesh = mp.solutions.face_mesh
@@ -55,7 +55,8 @@ try:
     spo2_model = joblib.load("spo2_model_simulated.pkl")
     hr_model = joblib.load("heart_rate_model.pkl")
 except FileNotFoundError:
-    print("Error: One or more .pkl model files are missing. Please upload them.")
+    print(
+        "Error: One or more .pkl model files are missing. Please upload them.")
     exit(1)
 
 models = {
@@ -119,10 +120,11 @@ def build_table(title, rows):
     return html
 
 
-# Function to save health report as PDF
-def save_results_to_pdf(patient_details, test_results, pdf_filename):
+# Function to save the health report to PDF
+def save_results_to_pdf(test_results, filename):
     try:
-        doc = SimpleDocTemplate(pdf_filename, pagesize=letter)
+        # Create a PDF document
+        doc = SimpleDocTemplate(filename, pagesize=letter)
         styles = getSampleStyleSheet()
         
         # Define custom styles
@@ -146,23 +148,19 @@ def save_results_to_pdf(patient_details, test_results, pdf_filename):
         
         # Build the PDF content
         flowables = []
-
-        # Patient details section
-        flowables.append(Paragraph(f"Patient: {patient_details['name']}", title_style))
-        flowables.append(Paragraph(f"Age: {patient_details['age']} | Gender: {patient_details['gender']}", body_style))
-        flowables.append(Spacer(1, 12))
-
+        
+        # Add title
+        flowables.append(Paragraph("Health Report", title_style))
+        
         # Add test results to the report
-        for section, data in test_results.items():
-            flowables.append(Paragraph(f"<u>{section}</u>", title_style))
-            for test, result in data.items():
-                flowables.append(Paragraph(f"{test}: {result}", body_style))
-                flowables.append(Spacer(1, 6))
+        for label, value in test_results.items():
+            line = f"{label}: {value}"
+            flowables.append(Paragraph(line, body_style))
             flowables.append(Spacer(1, 12))
-
+        
         # Build the PDF
         doc.build(flowables)
-        return f"PDF saved successfully as {pdf_filename}", pdf_filename
+        return f"PDF saved successfully as {filename}", filename
     except Exception as e:
         return f"Error saving PDF: {str(e)}", None
 
@@ -174,30 +172,55 @@ def build_health_card(profile_image, test_results, summary, patient_name="", pat
     
     html = f"""
     <div id="health-card" style="font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; max-width: 700px; margin: 20px auto; border-radius: 16px; background: linear-gradient(135deg, #e3f2fd 0%, #f3e5f5 100%); border: 2px solid #ddd; box-shadow: 0 8px 32px rgba(0, 0, 0, 0.15); padding: 30px; color: #1a1a1a;">
-        <div style="display: flex; justify-content: space-between;">
-            <div>
-                <h2>{patient_name}</h2>
-                <p>Age: {patient_age} | Gender: {patient_gender}</p>
-                <p>Report Date: {current_date}</p>
+        
+        <div style="background-color: rgba(255, 255, 255, 0.9); border-radius: 12px; padding: 20px; margin-bottom: 25px; border: 1px solid #e0e0e0;">
+            <div style="display: flex; align-items: center; margin-bottom: 15px;">
+                <div style="background: linear-gradient(135deg, #64b5f6, #42a5f5); padding: 8px 16px; border-radius: 8px; margin-right: 20px;">
+                    <h3 style="margin: 0; font-size: 16px; color: white; font-weight: 600;">HEALTH CARD</h3>
+                </div>
+                <div style="margin-left: auto; text-align: right; color: #666; font-size: 12px;">
+                    <div>Report Date: {current_date}</div>
+                    {f'<div>Patient ID: {patient_id}</div>' if patient_id else ''}
+                </div>
             </div>
-            <div>
-                <img src="data:image/png;base64,{profile_image}" style="width: 120px; height: 120px; border-radius: 50%;" />
+            <div style="display: flex; align-items: center;">
+                <img src="data:image/png;base64,{profile_image}" alt="Profile" style="width: 90px; height: 90px; border-radius: 50%; margin-right: 20px; border: 3px solid #fff; box-shadow: 0 4px 12px rgba(0,0,0,0.1);">
+                <div>
+                    <h2 style="margin: 0; font-size: 28px; color: #2c3e50; font-weight: 700;">{patient_name if patient_name else "Lab Test Results"}</h2>
+                    <p style="margin: 4px 0 0 0; color: #666; font-size: 14px;">{f"Age: {patient_age} | Gender: {patient_gender}" if patient_age and patient_gender else "AI-Generated Health Analysis"}</p>
+                    <p style="margin: 4px 0 0 0; color: #888; font-size: 12px;">Face-Based Health Analysis Report</p>
+                </div>
             </div>
         </div>
 
-        <div style="margin-top: 20px;">
-            {test_results}
+        <div style="background-color: rgba(255, 255, 255, 0.95); border-radius: 12px; padding: 25px; margin-bottom: 25px; border: 1px solid #e0e0e0;">
+            {test_results['Hematology']}
+            {test_results['Iron Panel']}
+            {test_results['Liver & Kidney']}
+            {test_results['Electrolytes']}
+            {test_results['Vitals']}
         </div>
 
-        <div style="margin-top: 30px;">
-            <h4>📝 Summary & Recommendations</h4>
-            <div>{summary}</div>
+        <div style="background-color: rgba(255, 255, 255, 0.95); padding: 20px; border-radius: 12px; border: 1px solid #e0e0e0; margin-bottom: 25px;">
+            <h4 style="margin: 0 0 15px 0; color: #2c3e50; font-size: 18px; font-weight: 600;">📝 Summary & Recommendations</h4>
+            <div style="color: #444; line-height: 1.6;">
+                {summary}
+            </div>
         </div>
 
+        <div style="display: flex; gap: 15px; justify-content: center; flex-wrap: wrap;">
+            <button onclick="window.print()" style="padding: 12px 24px; background: linear-gradient(135deg, #4caf50, #45a049); color: white; border: none; border-radius: 8px; cursor: pointer; font-weight: 600; font-size: 14px; box-shadow: 0 4px 12px rgba(76, 175, 80, 0.3); transition: all 0.3s;">
+                📥 Download Report
+            </button>
+            <button style="padding: 12px 24px; background: linear-gradient(135deg, #2196f3, #1976d2); color: white; border: none; border-radius: 8px; cursor: pointer; font-weight: 600; font-size: 14px; box-shadow: 0 4px 12px rgba(33, 150, 243, 0.3);">
+                📞 Find Labs Near Me
+            </button>
+        </div>
     </div>
     """
     return html
 
+
 # Initialize global variable for patient details
 current_patient_details = {'name': '', 'age': '', 'gender': '', 'id': ''}
 
@@ -206,22 +229,22 @@ def analyze_face(input_data):
     if isinstance(input_data, str):  # Video input (file path in Replit)
         cap = cv2.VideoCapture(input_data)
         if not cap.isOpened():
-            return None, None  # Return None for both parts if error occurs
+            return "<div style='color:red;'>⚠️ Error: Could not open video.</div>", None
         ret, frame = cap.read()
         cap.release()
         if not ret:
-            return None, None  # Return None for both parts if error occurs
+            return "<div style='color:red;'>⚠️ Error: Could not read video frame.</div>", None
     else:  # Image input
         frame = input_data
         if frame is None:
-            return None, None  # Return None for both parts if error occurs
+            return "<div style='color:red;'>⚠️ Error: No image provided.</div>", None
 
     # Resize image to reduce processing time
     frame = cv2.resize(frame, (640, 480))  # Adjust resolution for Replit
     frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
     result = face_mesh.process(frame_rgb)
     if not result.multi_face_landmarks:
-        return None, None  # Return None for both parts if no face is detected
+        return "<div style='color:red;'>⚠️ Error: Face not detected.</div>", None
     landmarks = result.multi_face_landmarks[
         0].landmark  # Fixed: Use integer index
     features = extract_features(frame_rgb, landmarks)
@@ -302,11 +325,9 @@ def analyze_face(input_data):
         current_patient_details['id']
     )
     
-    # Generate PDF filename dynamically
+    # Generate PDF and return for download
     pdf_filename = f"Health_Report_{datetime.now().strftime('%Y-%m-%d_%H-%M-%S')}.pdf"
-    
-    # Pass the pdf_filename along with test_results to save_results_to_pdf
-    pdf_result, pdf_filepath = save_results_to_pdf(current_patient_details, test_results, pdf_filename)
+    pdf_result, pdf_filepath = save_results_to_pdf(test_results, pdf_filename)
     
     if pdf_filepath:
         # Copy the PDF to a temporary directory for Gradio to serve it