app.py

import os
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
from reportlab.pdfgen import canvas
from reportlab.lib import colors
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()

# List of sample images
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, email):
    image_size = (224, 224)

    def predict_fracture(xray_path):
        img = Image.open(xray_path).resize(image_size)
        img_array = image.img_to_array(img) / 255.0
        img_array = np.expand_dims(img_array, axis=0)
        prediction = model.predict(img_array)[0][0]
        return prediction

    # Predict fracture
    prediction = predict_fracture(xray)
    diagnosed_class = "Normal" if prediction > 0.5 else "Fractured"
    severity = "Mild" if prediction < 0.3 else "Moderate" if prediction < 0.7 else "Severe"

    # File paths
    report_filename = f"{name}_fracture_report.pdf"
    report_path = os.path.join(REPORTS_DIR, report_filename)

    # Generate PDF report
    c = canvas.Canvas(report_path, pagesize=letter)
    c.setFont("Helvetica-Bold", 16)
    c.drawString(200, 770, "Bone Fracture Detection Report")

    # Patient details
    patient_data = [
        ["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]
    ]

    # Format table function
    def format_table(data):
        table = Table(data, colWidths=[270, 270])
        table.setStyle(TableStyle([
            ('BACKGROUND', (0, 0), (-1, 0), colors.darkblue),
            ('TEXTCOLOR', (0, 0), (-1, 0), colors.whitesmoke),
            ('ALIGN', (0, 0), (-1, -1), 'CENTER'),
            ('FONTNAME', (0, 0), (-1, 0), 'Helvetica-Bold'),
            ('BOTTOMPADDING', (0, 0), (-1, 0), 12),
            ('GRID', (0, 0), (-1, -1), 1, colors.black),
            ('VALIGN', (0, 0), (-1, -1), 'MIDDLE')
        ]))
        return table

    # Draw patient details table
    patient_table = format_table(patient_data)
    patient_table.wrapOn(c, 480, 500)
    patient_table.drawOn(c, 50, 620)

    # Save and return report path
    c.save()
    
    # 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

# Define Gradio Interface
with gr.Blocks() as app:
    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():
        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 & 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, email],
        outputs=[output_file],
    )

# Launch the Gradio app
if __name__ == "__main__":
    app.launch()