from flask import Blueprint, request, jsonify, render_template

import sys

import os

import cv2  # Added import

from utils.segmentation import segment_lung

from utils.classification import classify_disease

from utils.report_generator import generate_report

# Ensure directories exist

os.makedirs('app/static/uploaded_images', exist_ok=True)

os.makedirs('app/static/output_images', exist_ok=True)

main = Blueprint('main', __name__)

@main.route('/', methods=['GET'])

def index():

    return render_template('index.html')

@main.route('/analyze', methods=['POST'])

def analyze():

    try:

        file = request.files['xray']

        name = request.form['name']

        age = request.form['age']

        gender = request.form['gender']

        # Create paths using os.path.join for cross-platform compatibility

        upload_dir = 'app/static/uploaded_images'

        output_dir = 'app/static/output_images'

        xray_path = os.path.join(upload_dir, file.filename)

        mask_path = os.path.join(output_dir, f'mask_{file.filename}')

        report_path = os.path.join(output_dir, f'report_{os.path.splitext(file.filename)[0]}.pdf')

        file.save(xray_path)

        # Segment the lung

        mask = segment_lung(xray_path)

        cv2.imwrite(mask_path, mask)

        # Classify disease

        disease, confidence, severity = classify_disease(xray_path)

        # Generate report

        generate_report(name, age, gender, xray_path, mask_path, disease, severity, report_path)

        return jsonify({

            "success": True,

            "disease": disease,

            "severity": severity,

            "confidence": f"{confidence:.2f}",

            "segmented_image": f'mask_{file.filename}',

            "pdf_report": f'report_{os.path.splitext(file.filename)[0]}.pdf'

        })

    except Exception as e:

        return jsonify({

            "success": False,

            "error": str(e)

        }), 500