yml2213
344eea2194
做了什么:
- 包改为分层: tcaptcha/{protocol,telemetry,solvers,ocr,adapters,models,tests}
* protocol/ client.py transport.py proxy.py
* telemetry/ crypto.py values.py key.py opcodes.py
disasm.py program.py layout.py modules.py
* solvers/ text_click.py icon_click.py icon_click_rotate.py slider.py
* ocr/ engines.py slicer.py
* adapters/ one_ms.py
- tools/ 里原本是**包运行时依赖**的 tdc_{disasm,program,layout,modules}.py 并入 telemetry/
（放在 tools/ 属于分层倒置），tools/ 只留 CLI: tdc_key_pure.py / tdc_profile.py / cdp_*.js
- crypto.py 529 -> 340 行: 切除「成功样本模板回填」与「Node 插桩兜底」两条老路；
generate_telemetry 只剩 python_values 一种模式，传别的会直接报错并说明原因
- 求解器改名分清: solver.py -> solvers/icon_click.py（client 实际在用的 YOLO+ResNet18 ONNX），
icon_click_solver.py -> solvers/icon_click_rotate.py（仅测试在用，留作对照）
- pyproject: 去掉 ultralytics/onnx（训练栈已删），补上真正在用的 onnxruntime
删除了什么:
- 雨云整条线 + dist/rainyun_qinglong（104M 旧快照）
- 模板回填: models/success_collect_template.b64、tdc_worker.js、analyze_collect_layout.py
- 「补环境」时代浏览器 JS: chrome_fetch/manual_captcha/probe_captcha/solve_in_browser/tdc_browser
- 旧 VM 探索工具 10 个(tdc_collectgen/tdc_slotmap/tdc_lift/tdc_vm_run/tdc_query/tdc_probe 等)
+ 8 个基于它们的旧 verify 脚本
- 训练/标注/评估: train_classifier/train_detector/prepare_yolo/web_labeler/collector/
siamese/evaluate/benchmark_verify
- tcaptcha/core_js/（60 个分析产物）、TOOLCHAIN_REPORT.md（整篇在描述已删工具）
- 3 个已无任何引用的 PyTorch 权重：icon_classifier.pt 43M / yolo_detector.pt 5.9M /
siamese_matcher.pt 1.6M —— 线上只跑 onnx，tcaptcha/ 117M -> 66M
为什么:
- 项目后面要专门承载「滑块 / 文字点选 / 图标点选」三种求解器；扁平包 + 运行时依赖混在
tools/ + 两条已废弃的 collect 生成路线，会让后续扩展持续踩坑
怎么验证:
- .venv/bin/python -m tcaptcha.selftest 全绿
- scripts/verify/verify_offline.py 逐槽全等 + 分段几何一致
- scripts/verify/verify_values.py 4 份真机明文 152/152 逐槽全等
- scripts/verify/send_test.py --mode python_values 1ms 签到页文字点选 errorCode=0
- 回滚点: tag backup/pre-refactor-20261012
81 lines
2.8 KiB
Python
81 lines
2.8 KiB
Python
# -*- coding: utf-8 -*-
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"""
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文字点选求解器回归测试 (真实线上样本)
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fixtures 里的 6 张图全部来自真实线上环境:
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* har_round1..4 —— 用户 `点选.har` 抓包中的 4 道题 (672x480 背景图)
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* live_probe —— 本次逆向期间实时抓取的一道题
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* live_hard_rare_char —— 含生僻字 "筹" 且整题带斜切变形, 用于验证 ddddocr+PP-OCRv4 集成
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运行:
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uv run python -m tcaptcha.tests.test_glyph_solver
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"""
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from __future__ import annotations
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import json
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import logging
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import sys
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from pathlib import Path
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FIXTURES = Path(__file__).resolve().parent / "fixtures"
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MANIFEST = FIXTURES / "manifest.json"
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ROOT = Path(__file__).resolve().parent.parent.parent
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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.text_click import TextClickSolver, parse_instruction # noqa: E402
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TOLERANCE = 22 # 像素容差 (汉字包围盒中心 vs 人工标注中心)
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def run(verbose: bool = False) -> int:
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logging.basicConfig(level=logging.WARNING)
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cases = json.loads(MANIFEST.read_text(encoding="utf-8"))
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solver = TextClickSolver()
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passed = 0
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failed = []
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for case in cases:
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img = (FIXTURES / case["image"]).read_bytes()
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result = solver.solve_ex(img, case["instruction"])
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ok_points = result.ok and all(
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abs(p[0] - e[0]) <= TOLERANCE and abs(p[1] - e[1]) <= TOLERANCE
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for p, e in zip(result.points, case["expected_points"])
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)
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if verbose:
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print(f" {case['image']:24s} {case['instruction']}")
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print(f" pred={result.points}")
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print(f" exp ={case['expected_points']} post={result.posterior:.4f} "
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f"{'OK' if ok_points else 'MISMATCH'}")
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if ok_points:
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passed += 1
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else:
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failed.append((case["image"], result.points, case["expected_points"]))
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total = len(cases)
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print(f"\n文字点选求解器回归: {passed}/{total} 通过")
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for image, pred, exp in failed:
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print(f" ✗ {image}: pred={pred} exp={exp}")
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return 0 if passed == total else 1
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def test_parse_instruction():
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"""提示语解析的边界用例 (图标点选/滑块的模板串不能解析出目标字)"""
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assert parse_instruction("请依次点击：虫 呈 般") == ["虫", "呈", "般"]
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assert parse_instruction("请依次点击：虫呈般") == ["虫", "呈", "般"]
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assert parse_instruction("请依次点击：") == [] # 图标点选
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assert parse_instruction("拖动下方滑块完成拼图") == [] # 滑块
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if __name__ == "__main__":
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import argparse
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ap = argparse.ArgumentParser()
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ap.add_argument("-v", "--verbose", action="store_true")
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args = ap.parse_args()
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test_parse_instruction()
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print("提示语解析边界用例: OK")
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sys.exit(run(verbose=args.verbose))
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