import cv2
import os
import numpy as np

import sys
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..'))

from utils.lbp_features import FACE_SIZE

face_cascade = cv2.CascadeClassifier(
    cv2.data.haarcascades + 'haarcascade_frontalface_default.xml'
)


def crop_wajah(gray):
    """Crop wajah persis seperti notebook ablasi jalur 2."""
    wajah = face_cascade.detectMultiScale(gray, 1.1, 5, minSize=(50, 50))
    if len(wajah) == 0:
        return None, None

    (x, y, w, h) = max(wajah, key=lambda r: r[2] * r[3])
    sisi = max(w, h)
    cx, cy = x + w // 2, y + h // 2
    half = sisi // 2
    y1 = max(0, cy - half)
    y2 = min(gray.shape[0], cy + half)
    x1 = max(0, cx - half)
    x2 = min(gray.shape[1], cx + half)

    face_crop_gray = cv2.resize(gray[y1:y2, x1:x2], FACE_SIZE)
    face_crop_color = None
    return face_crop_gray, (x1, y1, x2, y2)


def extract_frames(video_path, output_dir, target_frames=200):
    """
    Ekstraksi frame sesuai ablasi jalur 2:
    1. Baca SEMUA frame
    2. Crop SEMUA frame (Haar Cascade)
    3. Sampling merata (np.linspace) dari yang berhasil crop
    """
    if not os.path.exists(video_path):
        raise Exception(f"Video tidak ditemukan: {video_path}")

    if not os.path.exists(output_dir):
        os.makedirs(output_dir)
    else:
        for f in os.listdir(output_dir):
            if (f.startswith("frame_") or f.startswith("raw_frame_")) and f.endswith(".jpg"):
                os.remove(os.path.join(output_dir, f))

    cap = cv2.VideoCapture(video_path)
    if not cap.isOpened():
        raise Exception("Gagal membuka file video.")

    total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
    fps = cap.get(cv2.CAP_PROP_FPS)

    if total_frames <= 0:
        raise Exception("Video tidak valid (0 frame).")

    semua_crop = []
    skipped_no_face = 0
    frame_idx = 0

    while True:
        ret, frame = cap.read()
        if not ret:
            break

        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        face_gray, bbox = crop_wajah(gray)

        if face_gray is None:
            skipped_no_face += 1
            frame_idx += 1
            continue

        (x1, y1, x2, y2) = bbox
        face_color = frame[y1:y2, x1:x2]

        semua_crop.append({
            'frame_idx': frame_idx,
            'face_gray': face_gray,
            'face_color': face_color,
        })

        frame_idx += 1

    cap.release()

    total_crop = len(semua_crop)

    if total_crop == 0:
        raise Exception(
            "Tidak ada frame wajah yang berhasil diekstrak. "
            "Pastikan wajah terlihat jelas di video."
        )

    if total_crop <= target_frames:
        hasil = semua_crop
    else:
        indices = np.linspace(0, total_crop - 1, target_frames, dtype=int)
        hasil = [semua_crop[i] for i in indices]

    saved_count = 0
    for cand in hasil:
        filename = f"frame_{saved_count:03d}.jpg"
        filename_raw = f"raw_frame_{saved_count:03d}.jpg"
        cv2.imwrite(
            os.path.join(output_dir, filename),
            cand['face_gray'],
            [int(cv2.IMWRITE_JPEG_QUALITY), 95]
        )
        cv2.imwrite(os.path.join(output_dir, filename_raw), cand['face_color'])
        saved_count += 1

    interval = total_crop / saved_count if saved_count > 0 else 0

    return {
        "total_video_frames": total_frames,
        "video_fps": round(fps, 1),
        "total_crop_detected": total_crop,
        "total_extracted": saved_count,
        "target_frames": target_frames,
        "skipped_no_face": skipped_no_face,
        "sampling_interval": round(interval, 1),
        "output_dir": output_dir
    }