Update app.py

app.py

@@ -1,185 +1,150 @@
 import os
-import smtplib
 import gradio as gr
-import tensorflow as tf
-import numpy as np
+from fpdf import FPDF
+import smtplib
 from email.mime.multipart import MIMEMultipart
 from email.mime.text import MIMEText
 from email.mime.base import MIMEBase
 from email import encoders
-from tensorflow.keras.preprocessing import image
-from PIL import Image
-from reportlab.lib.pagesizes import letter
-from reportlab.pdfgen import canvas
-from reportlab.lib.utils import simpleSplit
 
-# Load the trained model
-model = tf.keras.models.load_model("my_keras_model.h5")
+# Set environment variable to disable GPU if needed
+os.environ["CUDA_VISIBLE_DEVICES"] = ""
+
+# Function to generate PDF report
+def generate_report(name, age, gender, weight, height, allergies, injury_cause, address, parent_name, email, xray):
+    # Ensure input limits
+    name = name[:50] if name else "N/A"
+    age = str(age) if age else "N/A"
+    gender = gender if gender else "N/A"
+    weight = str(weight) + " kg" if weight else "N/A"
+    height = str(height) + " cm" if height else "N/A"
+    allergies = allergies[:100] if allergies else "None"
+    injury_cause = injury_cause[:500] if injury_cause else "Not specified"
+    address = address[:150] if address else "N/A"
+    parent_name = parent_name[:50] if parent_name else "N/A"
+    
+    # Fake hospital details
+    hospital_name = "CityCare Orthopedic Hospital"
+    hospital_address = "123 Medical Lane, Health City, Country"
+    
+    # Create PDF
+    pdf = FPDF()
+    pdf.set_auto_page_break(auto=True, margin=15)
+    pdf.add_page()
+    
+    # Title
+    pdf.set_font("Arial", style="B", size=14)
+    pdf.cell(200, 10, hospital_name, ln=True, align="C")
+    pdf.set_font("Arial", size=10)
+    pdf.cell(200, 5, hospital_address, ln=True, align="C")
+    pdf.ln(10)
+
+    # Patient Information
+    pdf.set_font("Arial", style="B", size=12)
+    pdf.cell(200, 10, "Patient Report", ln=True, align="C")
+    pdf.ln(5)
+
+    pdf.set_font("Arial", size=10)
+    pdf.cell(200, 5, f"Patient Name: {name}", ln=True)
+    pdf.cell(200, 5, f"Age: {age}  |  Gender: {gender}", ln=True)
+    pdf.cell(200, 5, f"Weight: {weight}  |  Height: {height}", ln=True)
+    pdf.cell(200, 5, f"Allergies: {allergies}", ln=True)
+    pdf.cell(200, 5, f"Cause of Injury: {injury_cause}", ln=True)
+    pdf.cell(200, 5, f"Address: {address}", ln=True)
+    pdf.cell(200, 5, f"Parent/Guardian: {parent_name}", ln=True)
+    pdf.ln(10)
+
+    # X-ray image
+    if xray:
+        pdf.set_font("Arial", style="B", size=12)
+        pdf.cell(200, 10, "X-ray Image", ln=True, align="C")
+        pdf.ln(5)
+        xray_path = "temp_xray.png"
+        xray.save(xray_path)
+        pdf.image(xray_path, x=40, w=130)
+        os.remove(xray_path)
+        pdf.ln(10)
+
+    # Diagnosis and Recommendation
+    pdf.set_font("Arial", style="B", size=12)
+    pdf.cell(200, 10, "Diagnosis & Recommendations", ln=True)
+    pdf.set_font("Arial", size=10)
+    pdf.multi_cell(0, 5, "Based on the provided X-ray and details, the following suggestions are recommended:")
+    
+    pdf.set_font("Arial", style="I", size=10)
+    pdf.cell(200, 5, "- Immediate medical consultation is advised.", ln=True)
+    pdf.cell(200, 5, "- Pain management with prescribed medications.", ln=True)
+    pdf.cell(200, 5, "- Possible surgical intervention if required.", ln=True)
+    pdf.cell(200, 5, "- Rest and immobilization of the affected area.", ln=True)
+    pdf.cell(200, 5, "- Follow-up X-ray and rehabilitation therapy.", ln=True)
+    
+    pdf.ln(5)
+    pdf.set_font("Arial", style="B", size=10)
+    pdf.cell(200, 5, "Estimated Treatment Costs:", ln=True)
+    
+    pdf.set_font("Arial", size=10)
+    pdf.cell(200, 5, "Government Hospital: $500 - $1,200", ln=True)
+    pdf.cell(200, 5, "Private Hospital: $2,000 - $5,000", ln=True)
 
-# Sample images
-sample_images = [f"samples/{img}" for img in os.listdir("samples") if img.endswith((".png", ".jpg", ".jpeg"))]
+    # Save PDF
+    pdf_path = "patient_report.pdf"
+    pdf.output(pdf_path)
 
-# Email function
-def send_email(patient_email, patient_name, pdf_path):
-    sender_email = "[email protected]"
-    sender_password = "your_email_password"
-    
-    try:
-        msg = MIMEMultipart()
-        msg["From"] = sender_email
-        msg["To"] = patient_email
-        msg["Subject"] = "Your Bone Fracture Report"
+    # Send email
+    send_email(email, name, hospital_name, pdf_path)
 
-        body = f"Hello {patient_name},\n\nPlease find attached your bone fracture detection report from XYZ Hospital.\n\nBest regards,\nXYZ Hospital"
-        msg.attach(MIMEText(body, "plain"))
+    return pdf_path
 
-        with open(pdf_path, "rb") as attachment:
-            part = MIMEBase("application", "octet-stream")
-            part.set_payload(attachment.read())
-            encoders.encode_base64(part)
-            part.add_header("Content-Disposition", f"attachment; filename={pdf_path}")
-            msg.attach(part)
+# Function to send email with PDF report
+def send_email(email, patient_name, hospital_name, pdf_path):
+    sender_email = "your_email@gmail.com"
+    sender_password = "your_password"
+    subject = f"Patient Report - {patient_name}"
+    
+    message = MIMEMultipart()
+    message["From"] = sender_email
+    message["To"] = email
+    message["Subject"] = subject
+    body = f"Dear {patient_name},\n\nYour medical report from {hospital_name} is attached. Please review the details and consult a doctor if needed.\n\nBest regards,\n{hospital_name}"
+    message.attach(MIMEText(body, "plain"))
+
+    with open(pdf_path, "rb") as attachment:
+        part = MIMEBase("application", "octet-stream")
+        part.set_payload(attachment.read())
+        encoders.encode_base64(part)
+        part.add_header("Content-Disposition", f"attachment; filename={pdf_path}")
+        message.attach(part)
 
+    try:
         server = smtplib.SMTP("smtp.gmail.com", 587)
         server.starttls()
         server.login(sender_email, sender_password)
-        server.sendmail(sender_email, patient_email, msg.as_string())
+        server.sendmail(sender_email, email, message.as_string())
         server.quit()
-
-        return "Report sent successfully!"
+        print("Email sent successfully!")
     except Exception as e:
-        return f"Error sending email: {str(e)}"
-
-# Generate 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
-
-    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"
-
-    # Save X-ray image
-    img = Image.open(xray).resize((300, 300))
-    img_path = f"{name}_xray.png"
-    img.save(img_path)
-
-    # PDF Report
-    report_path = f"{name}_fracture_report.pdf"
-    c = canvas.Canvas(report_path, pagesize=letter)
-
-    # Header
-    c.setFont("Helvetica-Bold", 16)
-    c.drawCentredString(300, 770, "XYZ Hospital, New Delhi")
-    c.setFont("Helvetica", 12)
-    c.drawCentredString(300, 750, "123 Health Street, New Delhi, India")
-    c.line(50, 740, 550, 740)
-
-    # Patient Details
-    c.setFont("Helvetica-Bold", 14)
-    c.drawString(50, 710, "Patient Information:")
-    c.setFont("Helvetica", 12)
-    details = [
-        f"Name: {name}",
-        f"Age: {age}",
-        f"Gender: {gender}",
-        f"Weight: {weight} kg",
-        f"Height: {height} cm",
-        f"Allergies: {allergies if allergies else 'None'}",
-        f"Cause of Injury: {cause if cause else 'Not Provided'}"
-    ]
-    y = 690
-    for detail in details:
-        c.drawString(50, y, detail)
-        y -= 20
-
-    # Diagnosis
-    c.setFont("Helvetica-Bold", 14)
-    c.drawString(50, y, "Diagnosis:")
-    c.setFont("Helvetica", 12)
-    y -= 20
-    c.drawString(50, y, f"Fractured: {'Yes' if diagnosed_class == 'Fractured' else 'No'}")
-    y -= 20
-    c.drawString(50, y, f"Injury Severity: {severity}")
-
-    # X-ray Image
-    c.drawInlineImage(img_path, 150, y - 260, width=300, height=300)
-    y -= 280
-
-    # Treatment & Recommendations
-    c.setFont("Helvetica-Bold", 14)
-    c.drawString(50, y, "Recommended Treatment:")
-    c.setFont("Helvetica", 12)
-    y -= 20
-    recommendations = {
-        "Mild": "Rest, pain relievers, and follow-up X-ray.",
-        "Moderate": "Plaster cast, minor surgery if needed.",
-        "Severe": "Major surgery, metal implants, and physiotherapy."
-    }
-    treatment_text = recommendations[severity]
-    for line in simpleSplit(treatment_text, "Helvetica", 12, 480):
-        c.drawString(50, y, line)
-        y -= 20
-
-    # Estimated Cost
-    c.setFont("Helvetica-Bold", 14)
-    c.drawString(50, y, "Estimated Treatment Cost:")
-    c.setFont("Helvetica", 12)
-    y -= 20
-    cost_gov = f"Government Hospital: ₹{2000 if severity == 'Mild' else 8000 if severity == 'Moderate' else 20000} - ₹{5000 if severity == 'Mild' else 15000 if severity == 'Moderate' else 50000}"
-    cost_priv = f"Private Hospital: ₹{10000 if severity == 'Mild' else 30000 if severity == 'Moderate' else 100000}+"
-    for line in simpleSplit(cost_gov, "Helvetica", 12, 480):
-        c.drawString(50, y, line)
-        y -= 20
-    for line in simpleSplit(cost_priv, "Helvetica", 12, 480):
-        c.drawString(50, y, line)
-        y -= 20
-
-    c.save()
-
-    # Send email with report
-    email_status = send_email(email, name, report_path)
-
-    return report_path, email_status
+        print(f"Error sending email: {e}")
 
 # Gradio Interface
 with gr.Blocks() as app:
-    gr.Markdown("# Bone Fracture Detection System\n### AI-powered diagnosis and treatment recommendations")
-
-    with gr.Row():
-        name = gr.Textbox(label="Patient Name", max_chars=50)
-        age = gr.Number(label="Age")
-
-    with gr.Row():
-        gender = gr.Radio(["Male", "Female", "Other"], label="Gender")
-        email = gr.Textbox(label="Patient Email")
-
-    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 (Max 100 words)", max_chars=500)
-
-    with gr.Row():
-        xray = gr.Image(type="filepath", label="Upload X-ray Image")
-
-    submit_button = gr.Button("Generate Report")
-    output_file = gr.File(label="Download Report")
-    email_status = gr.Textbox(label="Email Status", interactive=False)
-
-    submit_button.click(
-        generate_report,
-        inputs=[name, age, gender, weight, height, allergies, cause, xray, email],
-        outputs=[output_file, email_status]
-    )
-
-if __name__ == "__main__":
-    app.launch()
+    gr.Markdown("# Bone Fracture Detection & Diagnosis")
+    gr.Markdown("Upload an X-ray, enter patient details, and get a report with treatment suggestions.")
+    
+    name = gr.Textbox(label="Patient Name", max_length=50)
+    age = gr.Number(label="Age")
+    gender = gr.Dropdown(label="Gender", choices=["Male", "Female", "Other"])
+    weight = gr.Number(label="Weight (kg)")
+    height = gr.Number(label="Height (cm)")
+    allergies = gr.Textbox(label="Allergies", max_length=100)
+    injury_cause = gr.Textbox(label="Cause of Injury", max_length=500)
+    address = gr.Textbox(label="Address", max_length=150)
+    parent_name = gr.Textbox(label="Parent/Guardian Name", max_length=50)
+    email = gr.Textbox(label="Patient Email", type="email")
+    xray = gr.Image(label="Upload X-ray", type="pil")
+
+    submit = gr.Button("Generate Report")
+    output = gr.File()
+
+    submit.click(generate_report, [name, age, gender, weight, height, allergies, injury_cause, address, parent_name, email, xray], output)
+
+app.launch()