qiurui
cbfe4a23dc
- Pipeline: analyze(), redact(), analyze_image() methods - API: /analyze, /redact, /analyze/frame, /analyze/frame/base64 endpoints - Detectors: regex, NER, face (RKNN NPU) - Privacy frame route added for KVM-Privacy Hub integration
47 lines
1.5 KiB
Python
47 lines
1.5 KiB
Python
# tests/test_models.py
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from info_privacy.models import TextBlock, Entity, DetectionReport, EntityType
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def test_entity_type_enum():
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assert EntityType.ID_CARD.value == "id_card"
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assert EntityType.FACE.value == "face"
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def test_text_block_creation():
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block = TextBlock(
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text="张三，身份证：110101199001011234",
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bbox=[10, 20, 200, 40],
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page=1,
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layer="text",
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)
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assert block.layer == "text"
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def test_entity_creation():
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entity = Entity(
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id="e1",
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type=EntityType.ID_CARD,
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value="110101199001011234",
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page=1,
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bbox=[10, 20, 200, 40],
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layer="text",
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security_level="high",
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)
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assert entity.type == EntityType.ID_CARD
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def test_detection_report_summary():
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from info_privacy.models import Classification
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report = DetectionReport(
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doc_id="test-uuid",
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classification=Classification.NORMAL,
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blocked=False,
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block_reason=None,
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warning=None,
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doc_meta={"format": "pdf", "has_text_layer": True, "redact_strategy": "text_replace"},
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entities=[
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Entity(id="e1", type=EntityType.ID_CARD, value="x",
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page=1, bbox=[0,0,1,1], layer="text", security_level="high"),
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Entity(id="e2", type=EntityType.PHONE, value="y",
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page=1, bbox=[0,0,1,1], layer="text", security_level="high"),
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],
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)
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assert report.summary["id_card"] == 1
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assert report.summary["phone"] == 1
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