Update app.py

app.py

@@ -3,6 +3,7 @@ os.environ['MPLCONFIGDIR'] = '/tmp/matplotlib'
 from flask import Flask, render_template, request, redirect, url_for, session, send_file, jsonify
 from flask_sqlalchemy import SQLAlchemy
 from flask_migrate import Migrate
+import threading 
 import tensorflow as tf
 import numpy as np
 from PIL import Image
@@ -151,6 +152,25 @@ def preprocess_image(image_bytes):
     image_array = tf.keras.utils.img_to_array(image)
     return np.expand_dims(image_array, axis=0) / 255.0
 
+# NEW: Function to send email in a background thread
+def send_email_async(app_context, report_data):
+    with app_context:
+        try:
+            pdf_path = f"/tmp/report_{report_data['scan_id']}.pdf"
+            generate_pdf(report_data, pdf_path)
+            
+            msg = Message('Your SnapSkin Diagnostic Report', sender=app.config['MAIL_USERNAME'], recipients=[report_data['email']])
+            msg.body = f"Dear {report_data['name']},\n\nPlease find your diagnostic report attached."
+            
+            with app.open_resource(pdf_path) as fp:
+                msg.attach(f"SnapSkin_Report_{report_data['scan_id']}.pdf", "application/pdf", fp.read())
+            
+            mail.send(msg)
+            os.remove(pdf_path)
+            logger.info(f"Report sent successfully to {report_data['email']}")
+        except Exception as e:
+            logger.error(f"Failed to send email in background: {e}")
+
 def generate_pdf(report, filepath):
     c = canvas.Canvas(filepath, pagesize=A4)
     width, height = A4
@@ -236,6 +256,7 @@ def form():
 def training_plot():
     return send_file(PLOT_PATH, mimetype="image/png") if os.path.exists(PLOT_PATH) else ("", 404)
 
+
 @app.route("/uploads/<filename>")
 def uploaded_file(filename):
     upload_folder = "/tmp/uploads"
@@ -244,23 +265,18 @@ def uploaded_file(filename):
 @app.route("/predict", methods=["POST"])
 def predict():
     try:
-        if model_load_error or not model:
-            raise ValueError(f"Model not loaded: {model_load_error}")
-        if "image" not in request.files or not request.files["image"].filename:
-            raise ValueError("No image uploaded.")
-        
         image_file = request.files["image"]
         image_bytes = image_file.read()
         
-        # Preprocess and Predict
+        # --- Prediction Logic ---
         img_array = preprocess_image(image_bytes)
         prediction = model.predict(img_array)[0]
         predicted_index = int(np.argmax(prediction))
         confidence = float(prediction[predicted_index])
         label = label_map.get(predicted_index, "Unknown") if confidence >= CONFIDENCE_THRESHOLD else "Low confidence"
-        msg = "This image is not confidently recognized. Please upload a clearer image." if confidence < CONFIDENCE_THRESHOLD else ""
+        msg = "This image is not confidently recognized." if confidence < CONFIDENCE_THRESHOLD else ""
 
-        # Database operations
+        # --- Database Operations ---
         email = request.form.get("email")
         user = User.query.filter_by(email=email).first()
         if not user:
@@ -268,6 +284,7 @@ def predict():
             db.session.add(user)
             db.session.commit()
             
+        # --- Save image to /tmp to fix permission error ---
         timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
         image_filename = f"scan_{user.id}_{timestamp}.jpg"
         upload_folder = "/tmp/uploads"
@@ -276,6 +293,7 @@ def predict():
         with open(image_path, "wb") as f:
             f.write(image_bytes)
 
+        # --- Save Scan to DB ---
         scan = Scan(
             user_id=user.id, patient_name=request.form.get("name"),
             patient_gender=request.form.get("gender"), patient_age=int(request.form.get("age")),
@@ -284,44 +302,25 @@ def predict():
         db.session.add(scan)
         db.session.commit()
 
-        # Prepare report for session and email
+        # --- Prepare Report ---
         report = {
             "name": request.form.get("name"), "email": email, "gender": request.form.get("gender"),
             "age": request.form.get("age"), "prediction": label, "confidence": f"{confidence * 100:.2f}%",
-            "message": msg, "scan_id": scan.id
+            "message": msg, "scan_id": scan.id,
+            "email_status": "Your report will be sent to your email shortly." # Neutral message
         }
 
-        # Email sending logic
-        try:
-            if not app.config['MAIL_USERNAME'] or not app.config['MAIL_PASSWORD']:
-                raise ValueError("Mail server credentials are not configured.")
-            
-            pdf_path = f"/tmp/report_{scan.id}.pdf"
-            generate_pdf(report, pdf_path)
-            
-            email_msg = Message('Your SnapSkin Diagnostic Report', sender=app.config['MAIL_USERNAME'], recipients=[email])
-            email_msg.body = f"Dear {report['name']},\n\nPlease find your diagnostic report attached.\n\nThank you for using SnapSkin."
-            with app.open_resource(pdf_path) as fp:
-                email_msg.attach(f"SnapSkin_Report_{scan.id}.pdf", "application/pdf", fp.read())
-            mail.send(email_msg)
-            
-            os.remove(pdf_path)
-            report["email_status"] = "Success! The report has been sent to your email."
-            logger.info(f"Report sent to {email} for scan ID {scan.id}")
-            
-        except Exception as e:
-            logger.error(f"Failed to send email for scan ID {scan.id}: {e}")
-            report["email_status"] = "Failed to send the report to your email. You can download it directly."
+        # --- Send email in background to prevent loading freeze ---
+        thread = threading.Thread(target=send_email_async, args=(app.app_context(), report))
+        thread.start()
 
         session["report"] = report
         return redirect(url_for("result"))
 
     except Exception as e:
         logger.error(f"Prediction error: {e}")
-        return render_template(FORM_TEMPLATE, history_plot="/training_plot.png", result={
-            "prediction": "Error", "confidence": "N/A",
-            "message": f"An error occurred during prediction: {e}",
-            "email_status": "N/A"
+        return render_template("form.html", result={
+            "prediction": "Error", "message": f"An error occurred: {e}"
         })
 
 @app.route("/result")
@@ -329,8 +328,6 @@ def result():
     report = session.get("report")
     if not report:
         return redirect(url_for("form"))
-    # Change this line to render your result.html page
-    # The **report unpacks the dictionary into template variables
     return render_template("result.html", **report)
     
 @app.route("/download-report")