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f6c8252 979f3c3 f6c8252 | 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 | """Tests Sprint 54 β Layout F1 par type de rΓ©gion.
Couvre :
1. ``Region`` validation (bbox invalide β ValueError, area calculΓ©e).
2. ``_iou_bbox`` mathΓ©matique (identitΓ©, disjoint, partiel).
3. **Cas standards** :
- Layout parfait β F1 = 1
- Mauvais type sur la mΓͺme bbox β 0 TP pour ce type
- Hallucination (rΓ©gion inventΓ©e) β FP
- RΓ©gion ratΓ©e (manquante) β FN
- IoU sous le seuil β pas d'appariement
4. **Multi-type** : breakdown per_type cohΓ©rent avec les comptages
globaux.
5. **Alignement greedy** : 2 hypothΓ¨ses pour 1 GT β la meilleure
gagne, l'autre devient FP.
6. **Cas dΓ©gΓ©nΓ©rΓ©s** : listes vides, None, IoU custom.
7. ``layout_f1`` raccourci Γ©quivalent Γ ``compute_layout_metrics["f1"]``.
"""
from __future__ import annotations
import pytest
from picarones.measurements.layout import (
Region,
_iou_bbox,
compute_layout_metrics,
layout_f1,
)
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# 1. Region validation
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
class TestRegionDataclass:
def test_valid_construction(self) -> None:
r = Region("r1", "TextRegion", (0, 0, 100, 200))
assert r.id == "r1"
assert r.area == 20_000
def test_invalid_bbox_raises(self) -> None:
with pytest.raises(ValueError, match="bbox invalide"):
Region("r1", "TextRegion", (0, 0, 0, 100))
with pytest.raises(ValueError, match="bbox invalide"):
Region("r1", "TextRegion", (0, 0, 100, -5))
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# 2. IoU bbox
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
class TestIouBbox:
def test_identical_bbox_iou_one(self) -> None:
a = Region("a", "X", (0, 0, 100, 100))
assert _iou_bbox(a, a) == pytest.approx(1.0)
def test_disjoint_bbox_iou_zero(self) -> None:
a = Region("a", "X", (0, 0, 100, 100))
b = Region("b", "X", (200, 200, 50, 50))
assert _iou_bbox(a, b) == 0.0
def test_partial_overlap(self) -> None:
# a = [0,0,100,100], b = [50,50,100,100]
# intersection : 50x50 = 2500
# union : 10000 + 10000 - 2500 = 17500
# iou = 2500/17500 β 0.143
a = Region("a", "X", (0, 0, 100, 100))
b = Region("b", "X", (50, 50, 100, 100))
assert _iou_bbox(a, b) == pytest.approx(2500 / 17500)
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# 3. Cas standards
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
class TestStandardCases:
def test_perfect_layout(self) -> None:
ref = [
Region("r1", "TextRegion", (0, 0, 100, 100)),
Region("r2", "MarginNote", (200, 0, 50, 100)),
]
m = compute_layout_metrics(ref, list(ref))
assert m["global"]["f1"] == pytest.approx(1.0)
assert m["true_positives"] == 2
assert m["false_positives"] == 0
assert m["false_negatives"] == 0
def test_wrong_type_breaks_match(self) -> None:
# MΓͺme bbox mais type diffΓ©rent β pas d'appariement
ref = [Region("r1", "TextRegion", (0, 0, 100, 100))]
hyp = [Region("r1", "MarginNote", (0, 0, 100, 100))]
m = compute_layout_metrics(ref, hyp)
assert m["true_positives"] == 0
assert m["false_negatives"] == 1
assert m["false_positives"] == 1
def test_hallucinated_region_is_fp(self) -> None:
ref = [Region("r1", "TextRegion", (0, 0, 100, 100))]
hyp = [
Region("r1", "TextRegion", (0, 0, 100, 100)),
Region("rX", "TextRegion", (500, 500, 50, 50)), # inventΓ©e
]
m = compute_layout_metrics(ref, hyp)
assert m["true_positives"] == 1
assert m["false_positives"] == 1
assert m["hallucinated_regions"][0]["id"] == "rX"
def test_missing_region_is_fn(self) -> None:
ref = [
Region("r1", "TextRegion", (0, 0, 100, 100)),
Region("r2", "TextRegion", (200, 0, 100, 100)),
]
hyp = [Region("r1", "TextRegion", (0, 0, 100, 100))]
m = compute_layout_metrics(ref, hyp)
assert m["true_positives"] == 1
assert m["false_negatives"] == 1
assert m["missed_regions"][0]["id"] == "r2"
def test_iou_below_threshold_no_match(self) -> None:
# Recouvrement IoU = 2500/17500 β 0.14 < 0.5
ref = [Region("r1", "TextRegion", (0, 0, 100, 100))]
hyp = [Region("r1", "TextRegion", (50, 50, 100, 100))]
m = compute_layout_metrics(ref, hyp, iou_threshold=0.5)
assert m["true_positives"] == 0
def test_iou_above_threshold_matches(self) -> None:
# Recouvrement IoU = 6400/13600 β 0.47, sous 0.5 mais sur 0.4
ref = [Region("r1", "TextRegion", (0, 0, 100, 100))]
hyp = [Region("r1", "TextRegion", (20, 20, 100, 100))]
m_strict = compute_layout_metrics(ref, hyp, iou_threshold=0.5)
m_loose = compute_layout_metrics(ref, hyp, iou_threshold=0.4)
assert m_strict["true_positives"] == 0
assert m_loose["true_positives"] == 1
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# 4. Multi-type breakdown
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
class TestPerTypeBreakdown:
def test_per_type_metrics(self) -> None:
ref = [
Region("r1", "TextRegion", (0, 0, 100, 100)),
Region("r2", "TextRegion", (200, 0, 100, 100)),
Region("r3", "MarginNote", (0, 200, 100, 50)),
Region("r4", "Header", (0, 300, 200, 30)),
]
hyp = [
Region("r1", "TextRegion", (0, 0, 100, 100)), # match
# r2 manquante β FN TextRegion
Region("r3", "MarginNote", (0, 200, 100, 50)), # match
Region("rX", "Footer", (0, 400, 200, 30)), # FP Footer
# r4 Header manquante β FN Header
]
m = compute_layout_metrics(ref, hyp)
per_type = m["per_type"]
# TextRegion : 1 TP + 1 FN β P=1, R=0.5, F1=2/3
assert per_type["TextRegion"]["true_positives" if False else "f1"] == pytest.approx(2 / 3)
# MarginNote : 1 TP, parfait
assert per_type["MarginNote"]["f1"] == pytest.approx(1.0)
# Header : 1 FN β P=0, R=0, F1=0
assert per_type["Header"]["f1"] == 0.0
# Footer : 1 FP β P=0, R=0
assert per_type["Footer"]["f1"] == 0.0
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# 5. Alignement greedy
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
class TestGreedyAlignment:
def test_best_iou_wins(self) -> None:
# GT : 1 région. Hypothèse : 2 régions, l'une parfaite,
# l'autre faiblement chevauchante. La meilleure gagne.
ref = [Region("r1", "TextRegion", (0, 0, 100, 100))]
hyp = [
Region("h_weak", "TextRegion", (60, 60, 100, 100)), # faible IoU
Region("h_strong", "TextRegion", (0, 0, 100, 100)), # parfait
]
m = compute_layout_metrics(ref, hyp, iou_threshold=0.1)
# Le strong gagne, le weak devient FP
assert m["true_positives"] == 1
assert m["false_positives"] == 1
assert m["hallucinated_regions"][0]["id"] == "h_weak"
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# 6. Cas dΓ©gΓ©nΓ©rΓ©s
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
class TestDegenerateCases:
def test_both_empty(self) -> None:
m = compute_layout_metrics([], [])
assert m["global"]["f1"] == 0.0
assert m["per_type"] == {}
def test_only_reference_empty(self) -> None:
m = compute_layout_metrics([], [Region("r1", "X", (0, 0, 10, 10))])
assert m["false_positives"] == 1
assert m["true_positives"] == 0
def test_only_hypothesis_empty(self) -> None:
m = compute_layout_metrics([Region("r1", "X", (0, 0, 10, 10))], [])
assert m["false_negatives"] == 1
assert m["true_positives"] == 0
def test_none_inputs(self) -> None:
m = compute_layout_metrics(None, None)
assert m["global"]["f1"] == 0.0
def test_dict_input_coerced(self) -> None:
# L'utilisateur peut passer des dicts au format {id, type, bbox}
ref = [{"id": "r1", "type": "TextRegion", "bbox": (0, 0, 100, 100)}]
hyp = [{"id": "r1", "type": "TextRegion", "bbox": (0, 0, 100, 100)}]
assert layout_f1(ref, hyp) == pytest.approx(1.0)
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# 7. Type matching case-insensitive
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
class TestTypeNormalization:
def test_type_case_insensitive(self) -> None:
ref = [Region("r1", "TextRegion", (0, 0, 100, 100))]
hyp = [Region("r1", "textregion", (0, 0, 100, 100))]
assert layout_f1(ref, hyp) == pytest.approx(1.0)
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# 8. Shortcut layout_f1
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
class TestShortcut:
def test_shortcut_matches_full_call(self) -> None:
ref = [
Region("r1", "TextRegion", (0, 0, 100, 100)),
Region("r2", "MarginNote", (200, 0, 50, 100)),
]
hyp = [
Region("r1", "TextRegion", (0, 0, 100, 100)),
# r2 manquante
]
full = compute_layout_metrics(ref, hyp)
assert layout_f1(ref, hyp) == pytest.approx(full["global"]["f1"])
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