"""video_2 진단: 왜 0 프레임인지 각 단계별 확인"""
import sys
sys.stdout.reconfigure(encoding="utf-8", errors="replace")

import cv2
import numpy as np
from pathlib import Path
import importlib.util

spec = importlib.util.spec_from_file_location("p", "youtube_tab_to_pdf.py")
p = importlib.util.module_from_spec(spec)
spec.loader.exec_module(p)

mp4 = Path("output") / "サカナクション／新宝島(エレキギターTAB) 難易度★★★ sakanaction shintakarajima.mp4"
cap = cv2.VideoCapture(str(mp4))
total = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
fps = cap.get(cv2.CAP_PROP_FPS)

# 10개 프레임 샘플
indices = np.linspace(total * 0.1, total * 0.8, 10, dtype=int)
for idx in indices:
    cap.set(cv2.CAP_PROP_POS_FRAMES, idx)
    ret, frame = cap.read()
    if not ret:
        continue

    h, w = frame.shape[:2]
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # 행별 밝기
    margin_x = int(w * 0.1)
    row_br = np.mean(gray[:, margin_x:w-margin_x], axis=1)

    strip = p._find_white_tab_strip(frame)
    has_tab = False
    if strip:
        top, bottom = strip
        crop = frame[top:bottom, :]
        has_tab = p._has_tab_content(crop)

    print(f"Frame {idx:5d}: strip={strip}, has_tab={has_tab}, "
          f"top_br={np.mean(row_br[:h//3]):.0f}, "
          f"mid_br={np.mean(row_br[h//3:2*h//3]):.0f}, "
          f"bot_br={np.mean(row_br[2*h//3:]):.0f}")

    # strip이 있지만 has_tab=False인 경우 상세 진단
    if strip and not has_tab:
        top, bottom = strip
        crop = frame[top:bottom, :]
        g = cv2.cvtColor(crop, cv2.COLOR_BGR2GRAY)
        ch, cw = g.shape
        _, binary = cv2.threshold(g, 180, 255, cv2.THRESH_BINARY_INV)
        horiz_k = cv2.getStructuringElement(cv2.MORPH_RECT, (max(cw//3, 30), 1))
        horiz = cv2.morphologyEx(binary, cv2.MORPH_OPEN, horiz_k)
        lines = cv2.HoughLinesP(horiz, 1, np.pi/180, threshold=40,
                                minLineLength=cw//4, maxLineGap=20)
        nlines = 0 if lines is None else len(lines)
        ys = []
        if lines is not None:
            for l in lines:
                x1,y1,x2,y2 = l[0]
                if abs(y2-y1) < max(5, abs(x2-x1)*0.05):
                    ys.append((y1+y2)/2)
        ys.sort()
        clusters = []
        for y in ys:
            if not clusters or y - clusters[-1] > ch * 0.02:
                clusters.append(y)
        print(f"  → 크롭크기: {cw}x{ch}, 라인수: {nlines}, "
              f"수평ys: {len(ys)}, 클러스터: {len(clusters)}")

        # 디버그: 크롭 저장
        cv2.imwrite(f"output/raw_dump/v2_diag_{idx}.png", crop)

cap.release()