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1a12965 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 | """Post-generation validation of exported metadata.
Checks that every sample's metadata is internally consistent and safe for
downstream ML consumption: the signature was actually detected, its polygon
is a valid non-degenerate geometry, every declared bounding box is
well-formed and lies on the page, no NaN/Inf values leaked into the JSON,
metadata is schema-complete, and the difficulty score is exactly
reproducible from its own recorded components and weights.
"""
from __future__ import annotations
import math
from dataclasses import dataclass, field
from typing import Any
from shapely.geometry import Polygon
from src.config.schema import DifficultyWeights, ValidationConfig
from src.utils.logging_utils import get_logger
from src.verification.case_types import CASE_TABLE
logger = get_logger(__name__)
REQUIRED_TOP_LEVEL_KEYS = (
"document_id", "template", "page", "page_size", "signer", "signature_source",
"placement", "rendering", "difficulty", "quality", "verification", "augmentation", "geometry", "metrics",
)
# Case types whose ground truth is an intentionally blank target box -- a
# real signature is not expected to be detected there.
_BLANK_CASE_TYPES = frozenset({"2a", "5a"})
@dataclass
class ValidationIssue:
field: str
message: str
severity: str # "error" | "warning"
@dataclass
class ValidationReport:
sample_id: str
passed: bool
issues: list[ValidationIssue] = field(default_factory=list)
@property
def errors(self) -> list[ValidationIssue]:
return [i for i in self.issues if i.severity == "error"]
@property
def warnings(self) -> list[ValidationIssue]:
return [i for i in self.issues if i.severity == "warning"]
class ValidationEngine:
"""Validates one sample's exported metadata for correctness and completeness.
Example:
>>> engine = ValidationEngine(cfg.validation, cfg.difficulty)
>>> report = engine.validate(metadata)
>>> assert report.passed
"""
def __init__(self, config: ValidationConfig, difficulty_weights: DifficultyWeights) -> None:
self.config = config
self.weights = difficulty_weights
def validate(self, metadata: dict[str, Any]) -> ValidationReport:
"""Run every validation check against one sample's metadata dict."""
sample_id = str(metadata.get("document_id", "unknown"))
issues: list[ValidationIssue] = []
issues += self._check_completeness(metadata)
issues += self._check_no_nan(metadata)
issues += self._check_signature_exists(metadata)
issues += self._check_polygon_valid(metadata)
issues += self._check_boxes(metadata)
issues += self._check_difficulty_reproducible(metadata)
issues += self._check_verification_consistency(metadata)
has_errors = any(i.severity == "error" for i in issues)
has_warnings = any(i.severity == "warning" for i in issues)
passed = not has_errors and not (self.config.strict and has_warnings)
return ValidationReport(sample_id=sample_id, passed=passed, issues=issues)
def _check_completeness(self, metadata: dict[str, Any]) -> list[ValidationIssue]:
issues = []
for key in REQUIRED_TOP_LEVEL_KEYS:
if key not in metadata:
issues.append(ValidationIssue(key, f"Missing required top-level key '{key}'", "error"))
signer = metadata.get("signer", {})
for key in ("name", "role"):
if not signer.get(key):
issues.append(ValidationIssue(f"signer.{key}", f"Missing signer.{key}", "error"))
return issues
def _check_no_nan(self, metadata: dict[str, Any], path: str = "") -> list[ValidationIssue]:
issues: list[ValidationIssue] = []
# geometry.centroid_px / distance_from_box_center_px are deliberate
# NaN sentinels (see GeometryAnalyzer._empty_result) when nothing was
# detected -- not a data-quality bug, so they're excluded from the walk.
skip_paths: set = set()
if not metadata.get("geometry", {}).get("detected", True):
skip_paths = {"geometry.centroid_px[0]", "geometry.centroid_px[1]", "geometry.distance_from_box_center_px"}
def walk(value: Any, cur_path: str) -> None:
if cur_path in skip_paths:
return
if isinstance(value, dict):
for k, v in value.items():
walk(v, f"{cur_path}.{k}" if cur_path else str(k))
elif isinstance(value, (list, tuple)):
for i, v in enumerate(value):
walk(v, f"{cur_path}[{i}]")
elif isinstance(value, float):
if math.isnan(value) or math.isinf(value):
issues.append(ValidationIssue(cur_path, f"Non-finite value ({value}) at {cur_path}", "error"))
walk(metadata, path)
return issues
@staticmethod
def _expects_blank_target(metadata: dict[str, Any]) -> bool:
verification = metadata.get("verification") or {}
return verification.get("case_type") in _BLANK_CASE_TYPES
def _check_signature_exists(self, metadata: dict[str, Any]) -> list[ValidationIssue]:
geometry = metadata.get("geometry", {})
if self._expects_blank_target(metadata):
return []
if not geometry.get("detected", False):
return [ValidationIssue("geometry.detected", "Signature was not detected in the rendered document", "error")]
if geometry.get("ink_pixels", 0) <= 0:
return [ValidationIssue("geometry.ink_pixels", "Signature detected but has zero ink pixels", "error")]
return []
def _check_polygon_valid(self, metadata: dict[str, Any]) -> list[ValidationIssue]:
issues: list[ValidationIssue] = []
if not metadata.get("geometry", {}).get("detected", False) and self._expects_blank_target(metadata):
return []
poly_pts = metadata.get("geometry", {}).get("signature_polygon_px", [])
if len(poly_pts) < 3:
issues.append(ValidationIssue("geometry.signature_polygon_px", "Polygon has fewer than 3 points", "error"))
return issues
try:
poly = Polygon(poly_pts)
if not poly.is_valid:
issues.append(ValidationIssue("geometry.signature_polygon_px", "Polygon geometry is invalid", "error"))
elif poly.area <= 0:
issues.append(ValidationIssue("geometry.signature_polygon_px", "Polygon has zero area", "error"))
except Exception as exc: # pragma: no cover - defensive
issues.append(ValidationIssue("geometry.signature_polygon_px", f"Polygon construction failed: {exc}", "error"))
return issues
def _check_boxes(self, metadata: dict[str, Any]) -> list[ValidationIssue]:
issues: list[ValidationIssue] = []
geometry = metadata.get("geometry", {})
page_w, page_h = metadata.get("page_size", [None, None])
eps = self.config.max_coordinate_epsilon
for field_name in ("target_box", "actual_box", "signature_bbox_px", "box_px"):
box = geometry.get(field_name)
if not box or len(box) != 4:
issues.append(ValidationIssue(f"geometry.{field_name}", "Box missing or malformed", "error"))
continue
x1, y1, x2, y2 = box
if x2 <= x1 or y2 <= y1:
issues.append(ValidationIssue(f"geometry.{field_name}", f"Box has non-positive extent: {box}", "error"))
if page_w is not None and page_h is not None:
if x1 < -eps or y1 < -eps or x2 > page_w + eps or y2 > page_h + eps:
issues.append(ValidationIssue(
f"geometry.{field_name}",
f"Box {box} lies outside page bounds (0,0,{page_w},{page_h})",
"warning",
))
return issues
def _check_difficulty_reproducible(self, metadata: dict[str, Any]) -> list[ValidationIssue]:
difficulty = metadata.get("difficulty", {})
required = ("misplacement", "whitespace", "faintness", "smallness", "low_texture", "score", "tier")
if not all(k in difficulty for k in required):
return [ValidationIssue("difficulty", "Difficulty block incomplete", "error")]
w = self.weights
recomputed = (
w.misplacement * difficulty["misplacement"]
+ w.whitespace * difficulty["whitespace"]
+ w.faintness * difficulty["faintness"]
+ w.smallness * difficulty["smallness"]
+ w.low_texture * difficulty["low_texture"]
)
if abs(recomputed - difficulty["score"]) > 1e-3:
return [ValidationIssue(
"difficulty.score",
f"Score {difficulty['score']} does not match recomputed weighted sum {recomputed:.4f}",
"error",
)]
if recomputed < w.easy_threshold:
expected_tier = "easy"
elif recomputed < w.hard_threshold:
expected_tier = "medium"
else:
expected_tier = "hard"
if expected_tier != difficulty["tier"]:
return [ValidationIssue(
"difficulty.tier", f"Tier '{difficulty['tier']}' does not match expected '{expected_tier}'", "error",
)]
return []
def _check_verification_consistency(self, metadata: dict[str, Any]) -> list[ValidationIssue]:
verification = metadata.get("verification") or {}
case_type = verification.get("case_type")
if case_type is None:
return []
spec = CASE_TABLE.get(case_type)
if spec is None:
return [ValidationIssue("verification.case_type", f"Unknown case_type '{case_type}'", "error")]
issues: list[ValidationIssue] = []
if verification.get("verdict") != spec.verdict:
issues.append(ValidationIssue(
"verification.verdict",
f"verdict '{verification.get('verdict')}' does not match case_type '{case_type}' expected '{spec.verdict}'",
"error",
))
if verification.get("reject_code") != spec.reject_code:
issues.append(ValidationIssue(
"verification.reject_code",
f"reject_code '{verification.get('reject_code')}' does not match case_type '{case_type}' expected '{spec.reject_code}'",
"error",
))
return issues
@dataclass
class ValidationSummary:
"""Aggregate statistics over a batch of per-sample validation reports."""
total: int
passed: int
failed: int
total_errors: int
total_warnings: int
failed_sample_ids: list[str]
def as_dict(self) -> dict[str, Any]:
return {
"total": self.total,
"passed": self.passed,
"failed": self.failed,
"pass_rate": round(self.passed / self.total, 4) if self.total else 0.0,
"total_errors": self.total_errors,
"total_warnings": self.total_warnings,
"failed_sample_ids": self.failed_sample_ids,
}
def summarize(reports: list[ValidationReport]) -> ValidationSummary:
"""Aggregate a list of per-sample validation reports into a batch summary."""
passed = sum(1 for r in reports if r.passed)
return ValidationSummary(
total=len(reports),
passed=passed,
failed=len(reports) - passed,
total_errors=sum(len(r.errors) for r in reports),
total_warnings=sum(len(r.warnings) for r in reports),
failed_sample_ids=[r.sample_id for r in reports if not r.passed],
)
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