# -*- coding: utf-8 -*-
# 调试：trim_label 单格验证（r0c0 / r3c0 / r2c8）
import os
import sys

import cv2
import numpy as np

sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'tools'))
import tool_crop_mall_logos as M  # noqa: E402

HERE = os.path.dirname(os.path.abspath(__file__))
img = M.imread_u(M.DEFAULT_SRC)
warped = M.warp_board(img, M.detect_board_quad(img))
blocks = M.detect_confident_blocks(warped)
g = M.fit_grid(blocks)
print('row_top', [round(v) for v in g['row_top']])
print('col_center', [round(v) for v in g['col_center']])

for (ri, ci) in [(4, 1), (3, 8), (0, 0), (2, 8), (3, 6), (6, 10), (5, 0), (6, 0)]:
    b = g['grid'].get((ri, ci))
    if b is not None:
        x0, y0, x1, y1 = b['x'] - 2, b['y'] - 2, b['x'] + b['w'] + 2, b['y'] + b['h'] + 2
        kind = 'detect'
    else:
        cx = g['col_center'][ci]
        x0, x1 = int(cx - g['pw'] / 2 - 2), int(cx + g['pw'] / 2 + 2)
        y0, y1 = int(g['row_top'][ri] - 2), int(g['row_top'][ri] + g['ph'] + 2)
        kind = 'fallback'
    crop = warped[y0:y1, x0:x1]
    gray = cv2.cvtColor(crop, cv2.COLOR_BGR2GRAY)
    h = gray.shape[0]
    print('--- r%dc%d %s bbox h=%d' % (ri, ci, kind, h))
    for y in range(h - 1, max(0, h - 90), -6):
        row = gray[y]
        print('   y=%3d dark=%.3f mean=%.0f' % (y, float(np.mean(row < 160)), float(np.mean(row))))
    t = M.trim_label(crop)
    print('   trim: %d -> %d' % (crop.shape[0], t.shape[0]))
    if (ri, ci) in [(6, 10), (6, 0)]:
        import numpy as _np
        gg = cv2.cvtColor(crop, cv2.COLOR_BGR2GRAY).astype(_np.float32)
        dk = (gg < 160).mean(axis=1)
        mn = gg.mean(axis=1)
        ww = gg.shape[1]
        a0, a1 = int(ww * 0.2), int(ww * 0.8)
        dc = (gg[:, a0:a1] < 160).mean(axis=1)
        do = ((gg[:, :a0] < 160).sum(axis=1) + (gg[:, a1:] < 160).sum(axis=1)) / float(ww - (a1 - a0))
        rt = (dc + 0.004) / (do + 0.004)
        it = (dk >= 0.04) & (mn <= 220) & (rt > 2.5)
        ig = (dk < 0.12) & (mn >= 165) & (~it)
        for y in range(crop.shape[0] - 1, int(crop.shape[0] * 0.4), -4):
            print('   y=%3d dark=%.3f mean=%3.0f ratio=%5.2f text=%d gap=%d' % (y, dk[y], mn[y], rt[y], it[y], ig[y]))
    M.imwrite_u(os.path.join(HERE, 'trim_r%dc%d.jpg' % (ri, ci)), t)