Delete app.py

app.py

@@ -1,148 +0,0 @@
-import os
-import gradio as gr
-import tensorflow as tf
-import numpy as np
-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
-import smtplib
-from email.message import EmailMessage
-
-# Load the trained model
-model = tf.keras.models.load_model("my_keras_model.h5")
-
-# Read HTML content from `re.html`
-with open("templates/re.html", "r", encoding="utf-8") as file:
-    html_content = file.read()
-
-# Create reports directory
-REPORTS_DIR = "reports"
-os.makedirs(REPORTS_DIR, exist_ok=True)
-
-# Email configuration from environment variables
-SENDER_EMAIL = os.getenv("SENDER_EMAIL", "[email protected]")
-SENDER_PASSWORD = os.getenv("SENDER_PASSWORD", "1w3r5y7i9pW$")
-
-# Function to send email with PDF attachment
-def send_email_with_attachment(to_email, file_path, patient_name):
-    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!")
-
-    with open(file_path, "rb") as f:
-        file_data = f.read()
-        msg.add_attachment(file_data, maintype="application", subtype="pdf", filename="report.pdf")
-
-    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 generate 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 for report
-    img = Image.open(xray).resize((300, 300))
-    img_path = os.path.join(REPORTS_DIR, "xray.png")
-    img.save(img_path)
-
-    # Generate PDF report
-    report_path = os.path.join(REPORTS_DIR, "report.pdf")
-    c = canvas.Canvas(report_path, pagesize=letter)
-    c.setFont("Helvetica-Bold", 16)
-    c.drawString(200, 770, "Bone Fracture Detection Report")
-
-    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 and align tables
-    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
-
-    patient_table = format_table(patient_data)
-    patient_table.wrapOn(c, 480, 500)
-    patient_table.drawOn(c, 50, 620)
-
-    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'}")
-
-    c.save()
-
-    # Send report via email
-    send_email_with_attachment(email, report_path, name)
-    
-    return report_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")
-        email = gr.Textbox(label="Patient Email")
-
-    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")
-
-    submit_button.click(
-        generate_report,
-        inputs=[name, age, gender, weight, height, allergies, cause, xray, email],
-        outputs=[output_file],
-    )
-
-if __name__ == "__main__":
-    app.launch()