feat: Phase 1 - Système d'évaluation de la qualité

- Sélection et copie de 27 documents représentatifs (10 simples, 12 moyens, 5 complexes)
- Outil d'annotation CLI complet (tools/annotation_tool.py)
- Guide d'annotation détaillé (docs/annotation_guide.md)
- Évaluateur de qualité (evaluation/quality_evaluator.py)
  * Calcul Précision, Rappel, F1-Score
  * Identification faux positifs/négatifs
  * Métriques par type de PII
  * Export JSON et rapports texte
- Scanner de fuite (evaluation/leak_scanner.py)
  * Détection PII résiduels (CRITIQUE)
  * Détection nouveaux PII (HAUTE)
  * Scan métadonnées PDF (MOYENNE)
- Benchmark de performance (evaluation/benchmark.py)
  * Mesure temps de traitement
  * Mesure CPU/RAM
  * Export JSON/CSV
- Tests unitaires complets pour tous les composants
- Documentation complète du module d'évaluation

Tâches complétées:
- 1.1.1 Sélection de 27 documents (au lieu de 30)
- 1.1.2 Outil d'annotation CLI
- 1.2.1 Évaluateur de qualité
- 1.2.2 Scanner de fuite
- 1.2.3 Benchmark de performance

Prochaines étapes:
- 1.1.3 Annotation des 27 documents (manuel)
- 1.1.4 Enrichissement stopwords médicaux
- 1.3 Mesure de la baseline

tests/ground_truth/pdfs/mapping.json

@@ -0,0 +1,299 @@
+[
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+    "folder": "148_23018396",
+    "original_filename": "BACTERIO 23018396.pdf",
+    "type": "unknown",
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+  {
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+    "dest_filename": "002_simple_unknown_bacterio_476_23159413.pdf",
+    "original_path": "/home/dom/Téléchargements/II-1 Ctrl_T2A_2025_CHCB_DocJustificatifs (1)/476_23159413/bacterio 476_23159413.pdf",
+    "folder": "476_23159413",
+    "original_filename": "bacterio 476_23159413.pdf",
+    "type": "unknown",
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+    "original_path": "/home/dom/Téléchargements/II-1 Ctrl_T2A_2025_CHCB_DocJustificatifs (1)/210_23155084/CRO 23155084.pdf",
+    "folder": "210_23155084",
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+    "folder": "363_23085243",
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+    "folder": "222_23139653",
+    "original_filename": "CONSULTATION ANESTHESISTE 23139653.pdf",
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+    "folder": "anonymise",
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+    "folder": "1_23042753",
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+    "folder": "153_23102610",
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tests/ground_truth/selected_documents.json

@@ -0,0 +1,245 @@
+[
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+    "folder": "148_23018396",
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+]

tests/unit/test_benchmark.py

@@ -0,0 +1,79 @@
+#!/usr/bin/env python3
+"""
+Tests unitaires pour le benchmark.
+"""
+import pytest
+from pathlib import Path
+from evaluation.benchmark import Benchmark, BenchmarkResult
+
+
+class TestBenchmark:
+    """Tests pour Benchmark."""
+    
+    def test_get_system_info(self):
+        """Test de récupération des informations système."""
+        benchmark = Benchmark(Path("tests/ground_truth"))
+        
+        system_info = benchmark.get_system_info()
+        
+        assert "os" in system_info
+        assert "cpu" in system_info
+        assert "ram_gb" in system_info
+        assert "python_version" in system_info
+        assert system_info["ram_gb"] > 0
+    
+    def test_calculate_summary(self):
+        """Test de calcul du résumé."""
+        benchmark = Benchmark(Path("tests/ground_truth"))
+        
+        results = [
+            BenchmarkResult(
+                pdf_path="test1.pdf",
+                processing_time_s=10.0,
+                cpu_usage_percent=50.0,
+                ram_usage_mb=100.0,
+                pii_detected=10
+            ),
+            BenchmarkResult(
+                pdf_path="test2.pdf",
+                processing_time_s=20.0,
+                cpu_usage_percent=60.0,
+                ram_usage_mb=200.0,
+                pii_detected=20
+            )
+        ]
+        
+        summary = benchmark.calculate_summary(results)
+        
+        assert summary["documents_count"] == 2
+        assert summary["avg_time_per_doc"] == 15.0
+        assert summary["min_time"] == 10.0
+        assert summary["max_time"] == 20.0
+        assert summary["avg_cpu_percent"] == 55.0
+        assert summary["avg_ram_mb"] == 150.0
+        assert summary["total_pii_detected"] == 30
+        assert summary["avg_pii_per_doc"] == 15.0
+    
+    def test_benchmark_result_to_dict(self):
+        """Test de conversion en dictionnaire."""
+        result = BenchmarkResult(
+            pdf_path="test.pdf",
+            processing_time_s=12.345,
+            time_per_page_s=4.115,
+            cpu_usage_percent=67.89,
+            ram_usage_mb=123.45,
+            pii_detected=15
+        )
+        
+        data = result.to_dict()
+        
+        assert data["pdf_path"] == "test.pdf"
+        assert data["processing_time_s"] == 12.35  # Arrondi à 2 décimales
+        assert data["time_per_page_s"] == 4.12
+        assert data["cpu_usage_percent"] == 67.89
+        assert data["ram_usage_mb"] == 123.45
+        assert data["pii_detected"] == 15
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])

tests/unit/test_leak_scanner.py

@@ -0,0 +1,110 @@
+#!/usr/bin/env python3
+"""
+Tests unitaires pour le scanner de fuite.
+"""
+import pytest
+from pathlib import Path
+from evaluation.leak_scanner import LeakScanner, LeakReport
+
+
+class TestLeakScanner:
+    """Tests pour LeakScanner."""
+    
+    def test_scan_text_no_leak(self):
+        """Test sans fuite."""
+        scanner = LeakScanner()
+        
+        text = "Le patient a été examiné par le Dr. [NOM] le [DATE]."
+        original_pii = [
+            {"kind": "NOM", "original": "DUPONT"},
+            {"kind": "DATE", "original": "15/01/2024"}
+        ]
+        
+        leaks = scanner.scan_text(text, original_pii)
+        
+        assert len(leaks) == 0
+    
+    def test_scan_text_original_pii_present(self):
+        """Test avec PII original présent."""
+        scanner = LeakScanner()
+        
+        text = "Le patient DUPONT a été examiné le 15/01/2024."
+        original_pii = [
+            {"kind": "NOM", "original": "DUPONT"},
+            {"kind": "DATE", "original": "15/01/2024"}
+        ]
+        
+        leaks = scanner.scan_text(text, original_pii)
+        
+        assert len(leaks) == 2
+        assert all(leak["severity"] == "CRITIQUE" for leak in leaks)
+        assert all(leak["type"] == "original_pii_present" for leak in leaks)
+    
+    def test_scan_text_new_pii_detected(self):
+        """Test avec nouveau PII détecté."""
+        scanner = LeakScanner()
+        
+        text = "Contact: jean.dupont@example.com ou 01 23 45 67 89"
+        original_pii = []
+        
+        leaks = scanner.scan_text(text, original_pii)
+        
+        # Devrait détecter l'email et le téléphone
+        assert len(leaks) >= 2
+        
+        email_leak = next((l for l in leaks if l["pii_type"] == "EMAIL"), None)
+        assert email_leak is not None
+        assert email_leak["severity"] == "HAUTE"
+        
+        tel_leak = next((l for l in leaks if l["pii_type"] == "TEL"), None)
+        assert tel_leak is not None
+        assert tel_leak["severity"] == "HAUTE"
+    
+    def test_leak_report_is_safe(self):
+        """Test de rapport sûr."""
+        report = LeakReport(
+            is_safe=True,
+            leak_count=0,
+            leaks=[],
+            severity_counts={}
+        )
+        
+        assert report.is_safe
+        assert report.leak_count == 0
+    
+    def test_leak_report_not_safe(self):
+        """Test de rapport non sûr."""
+        report = LeakReport(
+            is_safe=False,
+            leak_count=2,
+            leaks=[
+                {"severity": "CRITIQUE", "type": "original_pii_present"},
+                {"severity": "HAUTE", "type": "new_pii_detected"}
+            ],
+            severity_counts={"CRITIQUE": 1, "HAUTE": 1}
+        )
+        
+        assert not report.is_safe
+        assert report.leak_count == 2
+        assert report.severity_counts["CRITIQUE"] == 1
+        assert report.severity_counts["HAUTE"] == 1
+    
+    def test_leak_report_to_dict(self):
+        """Test de conversion en dictionnaire."""
+        report = LeakReport(
+            is_safe=False,
+            leak_count=1,
+            leaks=[{"severity": "CRITIQUE"}],
+            severity_counts={"CRITIQUE": 1}
+        )
+        
+        data = report.to_dict()
+        
+        assert data["is_safe"] is False
+        assert data["leak_count"] == 1
+        assert len(data["leaks"]) == 1
+        assert data["severity_counts"]["CRITIQUE"] == 1
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])

tests/unit/test_quality_evaluator.py

@@ -0,0 +1,145 @@
+#!/usr/bin/env python3
+"""
+Tests unitaires pour l'évaluateur de qualité.
+"""
+import pytest
+from pathlib import Path
+from evaluation.quality_evaluator import QualityEvaluator, EvaluationResult
+
+
+class TestQualityEvaluator:
+    """Tests pour QualityEvaluator."""
+    
+    def test_normalize_text(self):
+        """Test de normalisation de texte."""
+        evaluator = QualityEvaluator(Path("tests/ground_truth"))
+        
+        assert evaluator.normalize_text("DUPONT") == "dupont"
+        assert evaluator.normalize_text("  DUPONT  ") == "dupont"
+        assert evaluator.normalize_text("DUPONT\n\nMARTIN") == "dupont martin"
+        assert evaluator.normalize_text("Jean-Pierre") == "jean-pierre"
+    
+    def test_types_match(self):
+        """Test de correspondance des types."""
+        evaluator = QualityEvaluator(Path("tests/ground_truth"))
+        
+        # Correspondance directe
+        assert evaluator.types_match("NOM", "NOM")
+        assert evaluator.types_match("NOM", "NOM_GLOBAL")
+        assert evaluator.types_match("TEL", "TEL_GLOBAL")
+        
+        # Correspondance croisée
+        assert evaluator.types_match("NOM", "PRENOM")
+        assert evaluator.types_match("PRENOM", "NOM")
+        
+        # Non correspondance
+        assert not evaluator.types_match("NOM", "TEL")
+        assert not evaluator.types_match("EMAIL", "ADRESSE")
+    
+    def test_calculate_metrics(self):
+        """Test de calcul des métriques."""
+        evaluator = QualityEvaluator(Path("tests/ground_truth"))
+        
+        # Cas parfait
+        precision, recall, f1 = evaluator.calculate_metrics(10, 0, 0)
+        assert precision == 1.0
+        assert recall == 1.0
+        assert f1 == 1.0
+        
+        # Cas avec erreurs
+        precision, recall, f1 = evaluator.calculate_metrics(8, 2, 2)
+        assert precision == 0.8  # 8 / (8 + 2)
+        assert recall == 0.8     # 8 / (8 + 2)
+        assert f1 == 0.8
+        
+        # Cas zéro
+        precision, recall, f1 = evaluator.calculate_metrics(0, 0, 0)
+        assert precision == 0.0
+        assert recall == 0.0
+        assert f1 == 0.0
+    
+    def test_compare_simple(self):
+        """Test de comparaison simple."""
+        evaluator = QualityEvaluator(Path("tests/ground_truth"))
+        
+        annotations = [
+            {"page": 0, "type": "NOM", "text": "DUPONT", "context": "Dr. DUPONT"},
+            {"page": 0, "type": "TEL", "text": "01 23 45 67 89", "context": "Tel: 01 23 45 67 89"}
+        ]
+        
+        detections = [
+            {"page": 0, "kind": "NOM", "original": "DUPONT"},
+            {"page": 0, "kind": "TEL", "original": "01 23 45 67 89"}
+        ]
+        
+        tp, fn, fp = evaluator.compare(annotations, detections)
+        
+        assert len(tp) == 2
+        assert len(fn) == 0
+        assert len(fp) == 0
+    
+    def test_compare_with_false_negative(self):
+        """Test avec faux négatif."""
+        evaluator = QualityEvaluator(Path("tests/ground_truth"))
+        
+        annotations = [
+            {"page": 0, "type": "NOM", "text": "DUPONT", "context": "Dr. DUPONT"},
+            {"page": 0, "type": "TEL", "text": "01 23 45 67 89", "context": "Tel: 01 23 45 67 89"}
+        ]
+        
+        detections = [
+            {"page": 0, "kind": "NOM", "original": "DUPONT"}
+            # TEL manquant
+        ]
+        
+        tp, fn, fp = evaluator.compare(annotations, detections)
+        
+        assert len(tp) == 1
+        assert len(fn) == 1
+        assert len(fp) == 0
+        assert fn[0]["type"] == "TEL"
+        assert fn[0]["reason"] == "not_detected"
+    
+    def test_compare_with_false_positive(self):
+        """Test avec faux positif."""
+        evaluator = QualityEvaluator(Path("tests/ground_truth"))
+        
+        annotations = [
+            {"page": 0, "type": "NOM", "text": "DUPONT", "context": "Dr. DUPONT"}
+        ]
+        
+        detections = [
+            {"page": 0, "kind": "NOM", "original": "DUPONT"},
+            {"page": 0, "kind": "NOM", "original": "MARTIN"}  # Faux positif
+        ]
+        
+        tp, fn, fp = evaluator.compare(annotations, detections)
+        
+        assert len(tp) == 1
+        assert len(fn) == 0
+        assert len(fp) == 1
+        assert fp[0]["text"] == "MARTIN"
+    
+    def test_evaluation_result_to_dict(self):
+        """Test de conversion en dictionnaire."""
+        result = EvaluationResult(
+            pdf_path="test.pdf",
+            true_positives=10,
+            false_positives=2,
+            false_negatives=1,
+            precision=0.8333,
+            recall=0.9091,
+            f1_score=0.8696
+        )
+        
+        data = result.to_dict()
+        
+        assert data["pdf_path"] == "test.pdf"
+        assert data["true_positives"] == 10
+        assert data["precision"] == 0.8333
+        assert data["recall"] == 0.9091
+        assert data["f1_score"] == 0.8696
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])