杨豪
d15b3c5b43
- src/: 最终交付物（solve.py base64 API、method_l_shape.py 核心算法、verify_result.py 验证工具） - docs/: 方案文档与实验演进记录 - try/: 历史实验脚本（A~K 方法） - 10/10 样本求解成功，3 个独立真值锚点偏差 <=4px
117 lines
3.9 KiB
Python
117 lines
3.9 KiB
Python
"""分歧裁决：对争议候选位置做细粒度尺度扫描 + 分通道 NCC。
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用法：.venv/bin/python try/adjudicate.py
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对 41ac 的 A2/C 两候选、444d 的共识候选、以及基线对 4db9/d7a7 做细化评估，
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输出每候选的最优尺度、NCC 与分通道 NCC，判断真目标。
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"""
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from pathlib import Path
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import sys
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import cv2
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import numpy as np
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sys.path.insert(0, str(Path(__file__).resolve().parent))
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from method_c_rotation import load_mark, template_at, patch_ncc # noqa: E402
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ROOT = Path(__file__).resolve().parent.parent
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CAP = ROOT / "captchas"
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CASES = {
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# 12位前缀: [(标签, 中心, 初始尺度), ...]
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"41ac8781f7e9": [
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("C ", (218.0, 223.0), 0.40),
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("A2 ", (110.0, 216.0), 0.50),
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("A2#2", (363.0, 214.5), 0.50),
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("A2#3", (270.0, 223.5), 0.50),
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],
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"444d0ea7c8bb": [("共识", (232.5, 202.5), 1.10)],
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"4db94793ec6d": [("基线", (351.0, 197.0), 1.05)],
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"d7a7f80c4554": [("基线", (222.8, 201.4), 0.95)],
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}
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SCALES_FINE = np.arange(-0.12, 0.121, 0.02)
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def find_files(prefix):
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"""按 12 位前缀 glob 完整文件名。"""
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bigs = [p for p in CAP.glob(f"{prefix}*.jpeg") if "-mark" not in p.stem]
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if not bigs:
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return None, None
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return bigs[0], CAP / f"{bigs[0].stem}-mark.png"
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def channel_ncc(big_f, center, tpl, mask):
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"""分通道 NCC（模板与 patch 中心对齐）。失败返回 None。"""
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try:
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h, w = tpl.shape[:2]
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x0 = int(round(center[0] - w / 2.0))
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y0 = int(round(center[1] - h / 2.0))
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if x0 < 0 or y0 < 0 or x0 + w > big_f.shape[1] or y0 + h > big_f.shape[0]:
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return None
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patch = big_f[y0:y0 + h, x0:x0 + w]
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vals = []
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for c in range(3):
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res = cv2.matchTemplate(patch[..., c:c + 1].copy(), tpl[..., c:c + 1].copy(),
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cv2.TM_CCOEFF_NORMED, mask=mask[..., None].copy())
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v = float(np.nan_to_num(res[0, 0], nan=-1.0))
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vals.append(v)
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return vals
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except cv2.error as e:
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print(f" 分通道失败: {e}")
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return None
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def refine(big_f, bgr, alpha, center, scale0):
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"""细粒度尺度扫描，返回 (best_ncc, best_scale, 分通道NCC)。"""
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try:
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best_ncc = -1.0
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best_scale = scale0
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best_ch = None
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for ds in SCALES_FINE:
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s = float(scale0 + ds)
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tpl, mask, _, _ = template_at(bgr, alpha, s, 0.0)
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if tpl is None:
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continue
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ncc = patch_ncc(big_f, center[0], center[1], tpl, mask)
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if ncc > best_ncc:
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ch = channel_ncc(big_f, center, tpl, mask)
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best_ncc = ncc
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best_scale = s
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best_ch = ch
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return best_ncc, best_scale, best_ch
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except Exception as e:
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print(f" 细化失败: {e}")
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return (-1.0, scale0, None)
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def process_case(prefix, cands):
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try:
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big_path, mark_path = find_files(prefix)
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if big_path is None:
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print(f"{prefix} 样本缺失")
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return
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big = cv2.imread(str(big_path), cv2.IMREAD_COLOR)
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if big is None:
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print(f"{prefix} 大图读取失败")
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return
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big_f = big.astype(np.float32)
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bgr, alpha = load_mark(mark_path)
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if bgr is None or alpha is None:
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print(f"{prefix} mark 读取失败")
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return
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print(f"== {prefix}")
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for label, center, scale0 in cands:
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ncc, s, ch = refine(big_f, bgr, alpha, center, scale0)
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chs = f"BGR={ch[0]:.2f}/{ch[1]:.2f}/{ch[2]:.2f}" if ch else "N/A"
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print(f" {label} center=({center[0]:.0f},{center[1]:.0f}) "
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f"scale*={s:.2f} ncc={ncc:.3f} {chs}")
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except Exception as e:
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print(f"{prefix} 处理失败: {e}")
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def main():
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for prefix, cands in CASES.items():
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process_case(prefix, cands)
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if __name__ == "__main__":
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main()
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