Update app.py

app.py

@@ -1,9 +1,9 @@
 import os
-os.environ["CUDA_VISIBLE_DEVICES"] = "-1"  # Force TensorFlow to use CPU
-
+import smtplib
 import gradio as gr
 import tensorflow as tf
 import numpy as np
+from email.message import EmailMessage
 from tensorflow.keras.preprocessing import image
 from PIL import Image
 from reportlab.lib.pagesizes import letter
@@ -14,6 +14,10 @@ from reportlab.platypus import Table, TableStyle
 # Load the trained model
 model = tf.keras.models.load_model("my_keras_model.h5")
 
+# Ensure the reports directory exists
+REPORTS_DIR = "reports"
+os.makedirs(REPORTS_DIR, exist_ok=True)
+
 # Read HTML content from `re.html`
 with open("templates/re.html", "r", encoding="utf-8") as file:
     html_content = file.read()
@@ -22,7 +26,7 @@ with open("templates/re.html", "r", encoding="utf-8") as file:
 sample_images = [f"samples/{img}" for img in os.listdir("samples") if img.endswith((".png", ".jpg", ".jpeg"))]
 
 # Function to process X-ray and generate a PDF report
-def generate_report(name, age, gender, weight, height, allergies, cause, xray):
+def generate_report(name, age, gender, weight, height, allergies, cause, xray, email):
     image_size = (224, 224)
 
     def predict_fracture(xray_path):
@@ -34,55 +38,30 @@ def generate_report(name, age, gender, weight, height, allergies, cause, xray):
 
     # Predict fracture
     prediction = predict_fracture(xray)
-    diagnosed_class = "normal" if prediction > 0.5 else "Fractured"
-
-    # Injury severity classification
+    diagnosed_class = "Normal" if prediction > 0.5 else "Fractured"
     severity = "Mild" if prediction < 0.3 else "Moderate" if prediction < 0.7 else "Severe"
 
-    # Treatment details table
-    treatment_data = [
-        ["Severity Level", "Recommended Treatment", "Recovery Duration"],
-        ["Mild", "Rest, pain relievers, and follow-up X-ray", "4-6 weeks"],
-        ["Moderate", "Plaster cast, minor surgery if needed", "6-10 weeks"],
-        ["Severe", "Major surgery, metal implants, physiotherapy", "Several months"]
-    ]
-
-    # Estimated cost & duration table
-    cost_duration_data = [
-        ["Hospital Type", "Estimated Cost", "Recovery Time"],
-        ["Government Hospital", f"₹{2000 if severity == 'Mild' else 8000 if severity == 'Moderate' else 20000} - ₹{5000 if severity == 'Mild' else 15000 if severity == 'Moderate' else 50000}", "4-12 weeks"],
-        ["Private Hospital", f"₹{10000 if severity == 'Mild' else 30000 if severity == 'Moderate' else 100000}+", "6 weeks - Several months"]
-    ]
-
-    # Save X-ray image for report
-    img = Image.open(xray).resize((300, 300))
-    img_path = f"{name}_xray.png"
-    img.save(img_path)
+    # File paths
+    report_filename = f"{name}_fracture_report.pdf"
+    report_path = os.path.join(REPORTS_DIR, report_filename)
 
     # Generate PDF report
-    report_path = f"{name}_fracture_report.pdf"
     c = canvas.Canvas(report_path, pagesize=letter)
-    
-    # Report title
     c.setFont("Helvetica-Bold", 16)
     c.drawString(200, 770, "Bone Fracture Detection Report")
 
-    # Patient details table
+    # Patient details
     patient_data = [
-        ["Patient Name", name],
-        ["Age", age],
-        ["Gender", gender],
-        ["Weight", f"{weight} kg"],
-        ["Height", f"{height} cm"],
+        ["Patient Name", name], ["Age", age], ["Gender", gender],
+        ["Weight", f"{weight} kg"], ["Height", f"{height} cm"],
         ["Allergies", allergies if allergies else "None"],
         ["Cause of Injury", cause if cause else "Not Provided"],
-        ["Diagnosis", diagnosed_class],
-        ["Injury Severity", severity]
+        ["Diagnosis", diagnosed_class], ["Injury Severity", severity]
     ]
 
-    # Format and align tables
+    # Format table function
     def format_table(data):
-        table = Table(data, colWidths=[270, 270])  # Set 90% width
+        table = Table(data, colWidths=[270, 270])
         table.setStyle(TableStyle([
             ('BACKGROUND', (0, 0), (-1, 0), colors.darkblue),
             ('TEXTCOLOR', (0, 0), (-1, 0), colors.whitesmoke),
@@ -99,61 +78,80 @@ def generate_report(name, age, gender, weight, height, allergies, cause, xray):
     patient_table.wrapOn(c, 480, 500)
     patient_table.drawOn(c, 50, 620)
 
-    # Load and insert X-ray image
-    c.drawInlineImage(img_path, 50, 320, width=250, height=250)
-    c.setFont("Helvetica-Bold", 12)
-    c.drawString(120, 290, f"Fractured: {'Yes' if diagnosed_class == 'Fractured' else 'No'}")
-
-    # Draw treatment and cost tables
-    treatment_table = format_table(treatment_data)
-    treatment_table.wrapOn(c, 480, 200)
-    treatment_table.drawOn(c, 50, 200)
-
-    cost_table = format_table(cost_duration_data)
-    cost_table.wrapOn(c, 480, 150)
-    cost_table.drawOn(c, 50, 80)
-
+    # Save and return report path
     c.save()
-
-    return report_path  # Return path for auto-download
+    
+    # Send email with report
+    send_email_with_attachment(email, report_path, name)
+    
+    return report_path  # For download
+
+# Function to send email with PDF attachment
+def send_email_with_attachment(to_email, file_path, patient_name):
+    sender_email = "[email protected]"  # Replace with your email
+    sender_password = "your-email-password"  # Use App Passwords if using Gmail
+
+    msg = EmailMessage()
+    msg["Subject"] = f"Bone Fracture Report for {patient_name}"
+    msg["From"] = sender_email
+    msg["To"] = to_email
+    msg.set_content(f"Dear {patient_name},\n\nAttached is your bone fracture detection report.\n\nThank you!")
+
+    # Attach PDF file
+    with open(file_path, "rb") as f:
+        file_data = f.read()
+        file_name = os.path.basename(file_path)
+        msg.add_attachment(file_data, maintype="application", subtype="pdf", filename=file_name)
+
+    # Send email
+    try:
+        with smtplib.SMTP_SSL("smtp.gmail.com", 465) as server:
+            server.login(sender_email, sender_password)
+            server.send_message(msg)
+        print(f"Email sent to {to_email}")
+    except Exception as e:
+        print(f"Failed to send email: {e}")
 
 # Function to select a sample image
 def use_sample_image(sample_image_path):
-    return sample_image_path  # Returns selected sample image filepath
+    return sample_image_path
 
 # Define Gradio Interface
 with gr.Blocks() as app:
-    gr.HTML(html_content)  # Display `re.html` content in Gradio
+    gr.HTML(html_content)
     gr.Markdown("## Bone Fracture Detection System")
-    
+
     with gr.Row():
         name = gr.Textbox(label="Patient Name")
         age = gr.Number(label="Age")
         gender = gr.Radio(["Male", "Female", "Other"], label="Gender")
-    
+
     with gr.Row():
         weight = gr.Number(label="Weight (kg)")
         height = gr.Number(label="Height (cm)")
-    
+
     with gr.Row():
         allergies = gr.Textbox(label="Allergies (if any)")
         cause = gr.Textbox(label="Cause of Injury")
 
     with gr.Row():
-        xray = gr.Image(type="filepath", label="Upload X-ray Image")
+        email = gr.Textbox(label="Patient Email")
     
+    with gr.Row():
+        xray = gr.Image(type="filepath", label="Upload X-ray Image")
+
     with gr.Row():
         sample_selector = gr.Dropdown(choices=sample_images, label="Use Sample Image")
         select_button = gr.Button("Load Sample Image")
 
-    submit_button = gr.Button("Generate Report")
+    submit_button = gr.Button("Generate Report & Send Email")
     output_file = gr.File(label="Download Report")
 
     select_button.click(use_sample_image, inputs=[sample_selector], outputs=[xray])
 
     submit_button.click(
         generate_report,
-        inputs=[name, age, gender, weight, height, allergies, cause, xray],
+        inputs=[name, age, gender, weight, height, allergies, cause, xray, email],
         outputs=[output_file],
     )