yml2213
6a8b3b3ce4
做了什么:
- solvers/slider.py: 新增 SliderChallenge（把课题 JSON 解析成解题参数）+ piece_from_sprite
（按 sprite_pos/size_2d 裁拼图块）+ track_limit 解析 / clamp_x / answer（按 data_type 组答案）
- telemetry/values.py: 新增 drag_trajectory_points（拖动轨迹：按下->横移->松手，
首点绝对、其余增量、尾点固定 [1,1,12]）；_sample_dt 抽成模块级供两条轨迹复用
- telemetry/{values,crypto}.py: generate_collect / generate_telemetry 接受 trajectory=
- protocol/client.py: 新增滑块分支（拉底图 + 精灵图 -> 裁块 -> ZNCC -> 组答案 -> 拖动轨迹），
accept_kinds 默认扩为 文字点选 + 图标点选 + 滑块
- scripts/verify/send_test.py: 加 --kind text|slider|icon|any
关键结论（账本 #60~#63）:
- 滑块答案是 DynAnswerType_POS，但坐标用**背景图原始像素**（不是页面显示像素）：
所以解题用 scale=1.0 直接提交 target_x_image；elem_id / data_type 均取自 move_cfg
- 拼图块可从课题配置直接裁，与旧 DOM 换算结果**逐像素相同**（测试已加交叉断言）
- **ddddocr 的滑块距离识别不可用**：fixture 偏 59px、实时偏 60px。判定手段是把拼图块
alpha 轮廓叠到背景上目视 —— 本项目 ZNCC 与缺口描边严丝合缝，ddddocr 整体右偏
- 低置信度（margin=0.024 < 0.08）那次被正确拒答并换题，换题后立刻成功，安全网有效
怎么验证:
- .venv/bin/python -m tcaptcha.tests.test_slider_solver 全绿（新增 [6]/[7] 两组断言）
- .venv/bin/python -m tcaptcha.selftest 全绿
- .venv/bin/python scripts/verify/send_test.py --kind slider 3/3 errorCode=0
- 文字点选回归不受影响：--kind text 仍为 errorCode=0
169 lines
7.5 KiB
Python
169 lines
7.5 KiB
Python
# -*- coding: utf-8 -*-
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"""
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滑块拼图求解器 回归测试 (AGENTS.md §5.9)
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固化的性质 (样本取自 1ms.run aid=195672344 真机页面 2026-10-11 的滑块验证码):
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1. `sprite_region` 能把 CSS 的 background-position/size 正确换算成精灵图像素区域;
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2. ZNCC 峰值落在**真缺口**上, 而不是干扰缺口, 也不是拼图块当前位置;
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3. 通过 y 方向小抖动吸收取整误差, 结果稳定;
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4. `ok` 的判定 (分数 + 与次峰间距) 在该样本上成立。
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样本: tcaptcha/tests/fixtures/1ms_slider_1_{bg.jpg,sprite.png}
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bg = 页面 `img_index=1` 的背景图 (672x390, 含真缺口 + 干扰缺口)
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sprite = 页面 `img_index=0` 的精灵图 (682x620, 含拖动柄 + 拼图块)
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DOM 实测口径 (drag_ele.html iframe 内):
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slideBg rect=(10, 68.78) 显示 340 x 242.857 -> scale = 340/672 = 0.50595238
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拼图块元素 rect=(35.2976, 133.53) 显示 60.7143 x 60.7143
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background-position: -70.8333px -247.917px
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background-size: 345.06px 313.69px
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=> 拼图块裁剪图在背景图坐标系里的左上角 = (50.0, 127.97)
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运行:
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.venv/bin/python -m tcaptcha.tests.test_slider_solver
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"""
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from __future__ import annotations
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import sys
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from pathlib import Path
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import cv2
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import numpy as np
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ROOT = Path(__file__).resolve().parents[2]
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if str(ROOT) not in sys.path:
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sys.path.insert(0, str(ROOT))
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from tcaptcha.solvers.slider import ( # noqa: E402
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SliderChallenge, SliderSolver, piece_mask, piece_from_sprite, sprite_region,
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)
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from tcaptcha.telemetry.values import drag_trajectory_points # noqa: E402
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FIX = ROOT / "tcaptcha" / "tests" / "fixtures"
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# 真机课题配置快照（aid=195672344 下滑块 2401/2402 的 dyn_show_info，
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# 只把两个很长的 image/sess 参数截短，字段结构一字未改）
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REAL_SLIDER_CHALLENGE = {
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"lang": "zh-cn",
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"instruction": "拖动下方滑块完成拼图",
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"bg_elem_cfg": {"sprite_pos": [0, 0], "size_2d": [672, 480],
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"img_url": "/cap_union_new_getcapbysig?img_index=1&image=XX&sess=YY"},
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"sprite_url": "/cap_union_new_getcapbysig?img_index=0&image=XX&sess=YY",
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"fg_elem_list": [
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{"id": 3, "sprite_pos": [0, 422], "size_2d": [672, 32], "init_pos": [0, 422]},
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{"id": 1, "sprite_pos": [140, 490], "size_2d": [120, 120], "init_pos": [50, 128],
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"move_cfg": {"track_limit": "x>=50&&x<=552", "move_factor": [1, 0],
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"data_type": ["DynAnswerType_POS"]}},
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],
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}
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# 真机 DOM 口径
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BG_POS = (-70.8333, -247.917)
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BG_SIZE = (345.06, 313.69)
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ELEM_SIZE = (60.7143, 60.7143)
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SLIDE_W = 340.0
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BG_NATURAL_W = 672.0
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SCALE = SLIDE_W / BG_NATURAL_W # 0.50595238
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PIECE_X_IMAGE = 50.0
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PIECE_Y_IMAGE = 128.0
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EXPECTED_DX_IMAGE = 293.0 # 真缺口 x - 拼图块 x
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EXPECTED_DECOY_X = 489 # 干扰缺口在背景图坐标里的 x
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_fails: list = []
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def check(name: str, cond: bool, detail: str = "") -> None:
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print(f" [{'PASS' if cond else 'FAIL'}] {name}" + (f" {detail}" if detail else ""))
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if not cond:
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_fails.append(name)
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def test_challenge_config() -> None:
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"""课题配置 -> 解题参数 -> 提交答案（滑块端到端里最容易出错的一环）。"""
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print("\n[6] 课题配置解析 (SliderChallenge)")
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sc = SliderChallenge.from_challenge(REAL_SLIDER_CHALLENGE)
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check("sprite_rect == (140,490,120,120)", sc.sprite_rect == (140, 490, 120, 120),
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str(sc.sprite_rect))
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check("init_pos == (50,128)", sc.init_pos == (50.0, 128.0), str(sc.init_pos))
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check("elem_id == 1（拼图块，不是滑轨的 3）", sc.elem_id == 1, str(sc.elem_id))
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check("data_type == DynAnswerType_POS", sc.data_type == "DynAnswerType_POS", sc.data_type)
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check("track_limit == (50,552)", sc.track_limit == (50.0, 552.0), str(sc.track_limit))
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check("bg_size == (672,480)", sc.bg_size == (672, 480), str(sc.bg_size))
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check("clamp_x 把越界值夹回轨道", sc.clamp_x(600) == 552.0 and sc.clamp_x(10) == 50.0,
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f"{sc.clamp_x(600)} / {sc.clamp_x(10)}")
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ans = sc.answer(343.0, 128.4)
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check("answer 结构 == [{elem_id,type,data}]",
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ans == [{"elem_id": 1, "type": "DynAnswerType_POS", "data": "343,128"}], str(ans))
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print("\n[7] 拖动轨迹 (drag_trajectory_points)")
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traj = drag_trajectory_points(sc.init_pos, (343.0, 128.0), img_w=sc.bg_size[0])
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check("首点是绝对坐标", len(traj[0]) == 3 and traj[0][0] > 20, str(traj[0]))
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check("尾点固定 [1,1,12]", traj[-1] == [1, 1, 12], str(traj[-1]))
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net = sum(p[0] for p in traj[1:-1])
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expect = (343.0 - 50.0) * (320.0 / 672.0)
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check("净横向位移 ≈ dx*scale", abs(net - expect) <= 6, f"{net} vs {expect:.1f}")
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check("点数在合理范围", 20 <= len(traj) <= 50, str(len(traj)))
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def main() -> int:
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bg = cv2.imread(str(FIX / "1ms_slider_1_bg.jpg"))
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sprite = cv2.imread(str(FIX / "1ms_slider_1_sprite.png"), cv2.IMREAD_UNCHANGED)
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if bg is None or sprite is None:
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print("缺少 fixture, 请确认 tcaptcha/tests/fixtures/1ms_slider_1_* 存在")
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return 1
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print(f"bg={bg.shape} sprite={sprite.shape}")
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print("\n[1] 精灵图区域换算")
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x, y, w, h = sprite_region(BG_POS, BG_SIZE, ELEM_SIZE, sprite.shape[:2])
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check("sprite_region == (140, 490, 120, 120)", (x, y, w, h) == (140, 490, 120, 120), f"got={(x, y, w, h)}")
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crop = sprite[y:y + h, x:x + w]
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# 交叉核对：课题配置里直接给的 sprite 矩形，应当与 DOM 换算结果完全一致
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crop_cfg = piece_from_sprite(sprite, (140, 490, 120, 120))
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check("配置矩形裁出的块 == DOM 换算裁出的块", np.array_equal(crop, crop_cfg))
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mask = piece_mask(crop)
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check("拼图块掩膜非空且不过分满", 500 < int(mask.sum()) < w * h * 0.9,
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f"mask={int(mask.sum())}/{w * h}")
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print("\n[2] 缺口定位 (ZNCC)")
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res = SliderSolver().solve(bg, crop, piece_x_image=PIECE_X_IMAGE, scale=SCALE,
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piece_y_image=PIECE_Y_IMAGE)
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print(f" {res.describe()}")
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check("ok", res.ok)
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check("分数 >= 0.65", res.score >= 0.65, f"score={res.score:.3f}")
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check("与次峰间距 >= 0.15", res.margin >= 0.15, f"margin={res.margin:.3f}")
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check("落在真缺口 (误差 <= 4 背景像素)", abs(res.target_x_image - (PIECE_X_IMAGE + EXPECTED_DX_IMAGE)) <= 4,
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f"target_x={res.target_x_image}")
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print("\n[3] 干扰缺口没有被选中")
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decoy = [x0 for x0, _ in res.candidates if abs(x0 - EXPECTED_DECOY_X) <= 6]
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check("次峰就是干扰缺口", bool(decoy), f"candidates={res.candidates}")
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check("真缺口分数严格高于干扰缺口", res.score > res.runner_up + 0.1,
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f"{res.score:.3f} vs {res.runner_up:.3f}")
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print("\n[4] 显示坐标换算")
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check("dx_display == dx_image * scale",
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abs(res.dx_display - res.dx_image * SCALE) < 1e-6,
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f"{res.dx_display:.2f} == {res.dx_image:.2f} * {SCALE:.6f}")
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check("dx_display 落在 [140, 160]", 140 <= res.dx_display <= 160, f"{res.dx_display:.2f}")
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print("\n[5] 拼图块当前位置不是答案 (那里没有洞)")
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near_piece = [s for x0, s in res.candidates if abs(x0 - PIECE_X_IMAGE) <= 8]
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check("拼图块自身位置的分数很低", all(s < 0.3 for s in near_piece),
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f"{near_piece}")
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test_challenge_config()
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print(f"\n{'=' * 62}")
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if _fails:
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print(f"❌ slider_solver 测试失败: {_fails}")
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return 1
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print("✅ slider_solver 测试全部通过")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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