report_generator.py

from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
from reportlab.lib.styles import getSampleStyleSheet
from datetime import datetime


from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Image
from reportlab.lib.styles import getSampleStyleSheet
from datetime import datetime
import os
from PIL import Image as PILImage


def generate_report(label, confidence, image, heatmap):
    try:
        if not label or image is None:
            return None

        # =========================
        # CREATE REPORTS DIRECTORY
        # =========================
        reports_dir = "reports"
        os.makedirs(reports_dir, exist_ok=True)  # auto-create if not exists

        # =========================
        # FILE PATH INSIDE FOLDER
        # =========================
        file_name = f"Deepfake_Detection_Report_{datetime.now().strftime('%Y%m%d_%H%M%S')}.pdf"
        file_path = os.path.join(reports_dir, file_name)

        doc = SimpleDocTemplate(file_path)
        styles = getSampleStyleSheet()
        content = []

        # TITLE
        content.append(Paragraph("Deepfake Detection Report", styles['Title']))
        content.append(Spacer(1, 12))

        # TIMESTAMP
        content.append(Paragraph(
            f"Generated on: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}",
            styles['Normal']
        ))
        content.append(Spacer(1, 12))

        # RESULTS
        content.append(Paragraph(f"<b>Prediction:</b> {label}", styles['Normal']))
        content.append(Spacer(1, 10))

        content.append(Paragraph(f"<b>Confidence:</b> {confidence}", styles['Normal']))
        content.append(Spacer(1, 15))

        # =========================
        # TEMP FILES (KEEP ROOT CLEAN)
        # =========================
        temp_dir = "temp"
        os.makedirs(temp_dir, exist_ok=True)

        image_path = os.path.join(temp_dir, "input.png")
        heatmap_path = os.path.join(temp_dir, "heatmap.png")

        # SAVE INPUT IMAGE
        if isinstance(image, PILImage.Image):
            image.save(image_path)

        if os.path.exists(image_path):
            content.append(Paragraph("<b>Input Image:</b>", styles['Normal']))
            content.append(Spacer(1, 10))
            content.append(Image(image_path, width=300, height=200))
            content.append(Spacer(1, 15))

        # HANDLE HEATMAP
        if heatmap is not None:
            try:
                if isinstance(heatmap, PILImage.Image):
                    heatmap.save(heatmap_path)
                else:
                    heatmap = PILImage.fromarray(heatmap)
                    heatmap.save(heatmap_path)

                if os.path.exists(heatmap_path):
                    content.append(Paragraph("<b>Explainability Heatmap:</b>", styles['Normal']))
                    content.append(Spacer(1, 10))
                    content.append(Image(heatmap_path, width=300, height=200))
                    content.append(Spacer(1, 15))

            except Exception as e:
                print("Heatmap error:", e)

        # INTERPRETATION
        interpretation = (
            "The uploaded image is likely AI-generated (deepfake)."
            if label == "Fake"
            else "The uploaded image is likely authentic."
        )

        content.append(Paragraph(f"<b>Interpretation:</b> {interpretation}", styles['Normal']))

        # BUILD PDF
        doc.build(content)

        # CLEANUP TEMP FILES
        for f in [image_path, heatmap_path]:
            if os.path.exists(f):
                os.remove(f)

        return file_path

    except Exception as e:
        print("REPORT ERROR:", e)
        return None