core/exporter.py

"""
Export Utilities

Fungsi-fungsi untuk export hasil counting ke CSV
dan membuat DataFrame summary untuk ditampilkan di Streamlit.
"""

import pandas as pd
from pathlib import Path
from datetime import datetime


def export_counts_to_csv(counts_data, output_path="outputs/counting_results.csv"):
    """
    Export data counting ke file CSV.
    
    Args:
        counts_data: dict dengan format:
            {
                "total": int,
                "per_class": {
                    "Car": int,
                    "Motorcycle": int,
                    "Bus": int,
                    "Truck": int
                }
            }
        output_path: path untuk menyimpan CSV
    
    Returns:
        str: path file yang dibuat
    """
    output_path = Path(output_path)
    output_path.parent.mkdir(parents=True, exist_ok=True)

    rows = []

    # baris per kelas (ambil dari data, tidak hardcode)
    per_class = counts_data.get("per_class", {})

    for cls_name, count in sorted(per_class.items()):
        rows.append({
            "Kelas": cls_name,
            "Jumlah": count
        })

    # baris total
    rows.append({
        "Kelas": "TOTAL",
        "Jumlah": counts_data.get("total", 0)
    })

    df = pd.DataFrame(rows)

    # tambahkan metadata
    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")

    # save ke CSV
    df.to_csv(output_path, index=False)

    # append timestamp ke file
    with open(output_path, "a") as f:
        f.write(f"\n# Timestamp: {timestamp}\n")

    return str(output_path)


def create_summary_dataframe(counts_data):
    """
    Buat DataFrame summary untuk ditampilkan di UI Streamlit.
    
    Args:
        counts_data: dict hasil dari counter.get_counts()
        
    Returns:
        pandas DataFrame
    """
    per_class = counts_data.get("per_class", {})

    rows = []
    for cls_name, count in sorted(per_class.items()):
        rows.append({
            "Kelas Kendaraan": cls_name,
            "Jumlah Terdeteksi": count
        })

    df = pd.DataFrame(rows)
    return df


def export_detailed_log(frame_logs, output_path="outputs/detailed_log.csv"):
    """
    Export log detail per-frame ke CSV.
    Berguna untuk analisis lebih lanjut.
    
    Args:
        frame_logs: list of dict, setiap dict berisi info per frame:
            {
                "frame_number": int,
                "num_detections": int,
                "num_tracked": int,
                "cumulative_count": int,
                "fps": float
            }
        output_path: path output
        
    Returns:
        str: path file
    """
    output_path = Path(output_path)
    output_path.parent.mkdir(parents=True, exist_ok=True)

    df = pd.DataFrame(frame_logs)
    df.to_csv(output_path, index=False)

    return str(output_path)