invoice-master-poc-v2/tests/table/test_structure_detector.py

"""
Tests for PP-StructureV3 Table Detection

TDD tests for TableDetector class. Tests are designed to run without
requiring the actual PP-StructureV3 library by using mock objects.
"""

import pytest
from dataclasses import dataclass
from typing import Any
from unittest.mock import MagicMock, patch
import numpy as np

from backend.table.structure_detector import (
    TableDetectionResult,
    TableDetector,
    TableDetectorConfig,
)


class TestTableDetectionResult:
    """Tests for TableDetectionResult dataclass."""

    def test_create_with_required_fields(self):
        """Test creating result with required fields."""
        result = TableDetectionResult(
            bbox=(10.0, 20.0, 300.0, 400.0),
            html="<table><tr><td>Test</td></tr></table>",
            confidence=0.95,
            table_type="wired",
        )

        assert result.bbox == (10.0, 20.0, 300.0, 400.0)
        assert result.html == "<table><tr><td>Test</td></tr></table>"
        assert result.confidence == 0.95
        assert result.table_type == "wired"
        assert result.cells == []

    def test_create_with_cells(self):
        """Test creating result with cell data."""
        cells = [
            {"text": "Header1", "row": 0, "col": 0},
            {"text": "Value1", "row": 1, "col": 0},
        ]
        result = TableDetectionResult(
            bbox=(0, 0, 100, 100),
            html="<table></table>",
            confidence=0.9,
            table_type="wireless",
            cells=cells,
        )

        assert len(result.cells) == 2
        assert result.cells[0]["text"] == "Header1"
        assert result.table_type == "wireless"

    def test_bbox_is_tuple_of_floats(self):
        """Test that bbox contains float values."""
        result = TableDetectionResult(
            bbox=(10, 20, 300, 400),  # int inputs
            html="",
            confidence=0.9,
            table_type="wired",
        )

        # Should work with int inputs (duck typing)
        assert len(result.bbox) == 4


class TestTableDetectorConfig:
    """Tests for TableDetectorConfig dataclass."""

    def test_default_values(self):
        """Test default configuration values."""
        config = TableDetectorConfig()

        assert config.device == "gpu:0"
        assert config.use_doc_orientation_classify is False
        assert config.use_doc_unwarping is False
        assert config.use_textline_orientation is False
        # SLANeXt models for better table recognition accuracy
        assert config.wired_table_model == "SLANeXt_wired"
        assert config.wireless_table_model == "SLANeXt_wireless"
        assert config.layout_model == "PP-DocLayout_plus-L"
        assert config.min_confidence == 0.5

    def test_custom_values(self):
        """Test custom configuration values."""
        config = TableDetectorConfig(
            device="cpu",
            min_confidence=0.7,
            wired_table_model="SLANet_plus",
        )

        assert config.device == "cpu"
        assert config.min_confidence == 0.7
        assert config.wired_table_model == "SLANet_plus"


class TestTableDetectorInitialization:
    """Tests for TableDetector initialization."""

    def test_init_with_default_config(self):
        """Test initialization with default config."""
        detector = TableDetector()

        assert detector.config is not None
        assert detector.config.device == "gpu:0"
        assert detector._initialized is False

    def test_init_with_custom_config(self):
        """Test initialization with custom config."""
        config = TableDetectorConfig(device="cpu", min_confidence=0.8)
        detector = TableDetector(config=config)

        assert detector.config.device == "cpu"
        assert detector.config.min_confidence == 0.8

    def test_init_with_mock_pipeline(self):
        """Test initialization with pre-initialized pipeline."""
        mock_pipeline = MagicMock()
        detector = TableDetector(pipeline=mock_pipeline)

        assert detector._initialized is True
        assert detector._pipeline is mock_pipeline


class TestTableDetectorDetection:
    """Tests for TableDetector.detect() method."""

    def create_mock_element(
        self,
        label: str = "table",
        bbox: tuple = (10, 20, 300, 400),
        html: str = "<table><tr><td>Test</td></tr></table>",
        score: float = 0.95,
    ) -> MagicMock:
        """Create a mock PP-StructureV3 element."""
        element = MagicMock()
        element.label = label
        element.bbox = bbox
        element.html = html
        element.score = score
        element.cells = []
        return element

    def create_mock_result(self, elements: list) -> MagicMock:
        """Create a mock PP-StructureV3 result (legacy API without 'get')."""
        # Use spec=[] to prevent MagicMock from having a 'get' method
        # This simulates the legacy API that uses layout_elements attribute
        result = MagicMock(spec=["layout_elements"])
        result.layout_elements = elements
        return result

    def test_detect_single_table(self):
        """Test detecting a single table in image."""
        # Setup mock pipeline
        mock_pipeline = MagicMock()
        element = self.create_mock_element()
        mock_result = self.create_mock_result([element])
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1
        assert results[0].bbox == (10.0, 20.0, 300.0, 400.0)
        assert results[0].confidence == 0.95
        assert results[0].table_type == "wired"
        mock_pipeline.predict.assert_called_once()

    def test_detect_multiple_tables(self):
        """Test detecting multiple tables in image."""
        mock_pipeline = MagicMock()
        element1 = self.create_mock_element(
            bbox=(10, 20, 300, 200),
            html="<table>1</table>",
        )
        element2 = self.create_mock_element(
            bbox=(10, 220, 300, 400),
            html="<table>2</table>",
        )
        mock_result = self.create_mock_result([element1, element2])
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((500, 400, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 2
        assert results[0].html == "<table>1</table>"
        assert results[1].html == "<table>2</table>"

    def test_detect_no_tables(self):
        """Test handling of image with no tables."""
        mock_pipeline = MagicMock()
        # Return result with non-table elements
        text_element = MagicMock()
        text_element.label = "text"
        mock_result = self.create_mock_result([text_element])
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 0

    def test_detect_filters_low_confidence(self):
        """Test that low confidence tables are filtered out."""
        mock_pipeline = MagicMock()
        low_conf_element = self.create_mock_element(score=0.3)
        high_conf_element = self.create_mock_element(score=0.9)
        mock_result = self.create_mock_result([low_conf_element, high_conf_element])
        mock_pipeline.predict.return_value = [mock_result]

        config = TableDetectorConfig(min_confidence=0.5)
        detector = TableDetector(config=config, pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1
        assert results[0].confidence == 0.9

    def test_detect_wireless_table(self):
        """Test detecting wireless (borderless) table."""
        mock_pipeline = MagicMock()
        element = self.create_mock_element(label="wireless_table")
        mock_result = self.create_mock_result([element])
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1
        assert results[0].table_type == "wireless"

    def test_detect_with_file_path(self):
        """Test detection with file path input."""
        mock_pipeline = MagicMock()
        element = self.create_mock_element()
        mock_result = self.create_mock_result([element])
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)

        # Should accept string path
        results = detector.detect("/path/to/image.png")

        mock_pipeline.predict.assert_called_with("/path/to/image.png")

    def test_detect_returns_empty_on_none_results(self):
        """Test handling of None results from pipeline."""
        mock_pipeline = MagicMock()
        mock_pipeline.predict.return_value = None

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert results == []


class TestTableDetectorLazyInit:
    """Tests for lazy initialization of PP-StructureV3."""

    def test_lazy_init_flag_starts_false(self):
        """Test that pipeline is not initialized on construction."""
        detector = TableDetector()
        assert detector._initialized is False
        assert detector._pipeline is None

    def test_lazy_init_with_injected_pipeline(self):
        """Test that injected pipeline skips lazy initialization."""
        mock_pipeline = MagicMock()
        mock_pipeline.predict.return_value = []

        detector = TableDetector(pipeline=mock_pipeline)

        assert detector._initialized is True
        assert detector._pipeline is mock_pipeline

        # Detection should work without triggering _ensure_initialized import
        image = np.zeros((100, 100, 3), dtype=np.uint8)
        results = detector.detect(image)

        assert results == []
        mock_pipeline.predict.assert_called_once()

    def test_import_error_without_paddleocr(self):
        """Test ImportError when paddleocr is not available."""
        detector = TableDetector()

        # Simulate paddleocr not being installed
        with patch.dict("sys.modules", {"paddleocr": None}):
            with pytest.raises(ImportError) as exc_info:
                detector._ensure_initialized()

            assert "paddleocr" in str(exc_info.value).lower()


class TestTableDetectorParseResults:
    """Tests for result parsing logic."""

    def test_parse_element_with_box_attribute(self):
        """Test parsing element with 'box' instead of 'bbox'."""
        mock_pipeline = MagicMock()
        element = MagicMock()
        element.label = "table"
        element.box = [10, 20, 300, 400]  # 'box' instead of 'bbox'
        element.html = "<table></table>"
        element.score = 0.9
        element.cells = []
        del element.bbox  # Remove bbox attribute

        mock_result = MagicMock(spec=["layout_elements"])
        mock_result.layout_elements = [element]
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1
        assert results[0].bbox == (10.0, 20.0, 300.0, 400.0)

    def test_parse_element_with_table_html_attribute(self):
        """Test parsing element with 'table_html' instead of 'html'."""
        mock_pipeline = MagicMock()
        element = MagicMock()
        element.label = "table"
        element.bbox = [0, 0, 100, 100]
        element.table_html = "<table><tr><td>Content</td></tr></table>"
        element.score = 0.9
        element.cells = []
        del element.html

        mock_result = MagicMock(spec=["layout_elements"])
        mock_result.layout_elements = [element]
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1
        assert "<table>" in results[0].html

    def test_parse_element_with_type_attribute(self):
        """Test parsing element with 'type' instead of 'label'."""
        mock_pipeline = MagicMock()
        element = MagicMock()
        element.type = "table"  # 'type' instead of 'label'
        element.bbox = [0, 0, 100, 100]
        element.html = "<table></table>"
        element.score = 0.9
        element.cells = []
        del element.label

        mock_result = MagicMock(spec=["layout_elements"])
        mock_result.layout_elements = [element]
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1

    def test_parse_cells_data(self):
        """Test parsing cell-level data from element."""
        mock_pipeline = MagicMock()

        # Create mock cells
        cell1 = MagicMock()
        cell1.text = "Header"
        cell1.row = 0
        cell1.col = 0
        cell1.row_span = 1
        cell1.col_span = 1
        cell1.bbox = [0, 0, 50, 20]

        cell2 = MagicMock()
        cell2.text = "Value"
        cell2.row = 1
        cell2.col = 0
        cell2.row_span = 1
        cell2.col_span = 1
        cell2.bbox = [0, 20, 50, 40]

        element = MagicMock()
        element.label = "table"
        element.bbox = [0, 0, 100, 100]
        element.html = "<table></table>"
        element.score = 0.9
        element.cells = [cell1, cell2]

        mock_result = MagicMock(spec=["layout_elements"])
        mock_result.layout_elements = [element]
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1
        assert len(results[0].cells) == 2
        assert results[0].cells[0]["text"] == "Header"
        assert results[0].cells[0]["row"] == 0
        assert results[0].cells[1]["text"] == "Value"
        assert results[0].cells[1]["row"] == 1


class TestTableDetectorEdgeCases:
    """Tests for edge cases and error handling."""

    def test_handles_malformed_element_gracefully(self):
        """Test graceful handling of malformed element data."""
        mock_pipeline = MagicMock()

        # Element missing required attributes
        bad_element = MagicMock()
        bad_element.label = "table"
        # Missing bbox, html, score
        del bad_element.bbox
        del bad_element.box

        good_element = MagicMock()
        good_element.label = "table"
        good_element.bbox = [0, 0, 100, 100]
        good_element.html = "<table></table>"
        good_element.score = 0.9
        good_element.cells = []

        mock_result = MagicMock(spec=["layout_elements"])
        mock_result.layout_elements = [bad_element, good_element]
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        # Should not raise, should skip bad element
        results = detector.detect(image)

        assert len(results) == 1

    def test_handles_empty_layout_elements(self):
        """Test handling of empty layout_elements list."""
        mock_pipeline = MagicMock()
        mock_result = MagicMock(spec=["layout_elements"])
        mock_result.layout_elements = []
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert results == []

    def test_handles_result_without_layout_elements(self):
        """Test handling of result without layout_elements attribute."""
        mock_pipeline = MagicMock()
        mock_result = MagicMock(spec=[])  # No attributes
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert results == []

    def test_confidence_as_list(self):
        """Test handling confidence score as list."""
        mock_pipeline = MagicMock()
        element = MagicMock()
        element.label = "table"
        element.bbox = [0, 0, 100, 100]
        element.html = "<table></table>"
        element.score = [0.95]  # Score as list
        element.cells = []

        mock_result = MagicMock(spec=["layout_elements"])
        mock_result.layout_elements = [element]
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1
        assert results[0].confidence == 0.95


class TestPaddleX3xAPI:
    """Tests for PaddleX 3.x API support (LayoutParsingResultV2)."""

    def test_parse_paddlex_result_with_tables(self):
        """Test parsing PaddleX 3.x LayoutParsingResultV2 with tables."""
        mock_pipeline = MagicMock()

        # Simulate PaddleX 3.x dict-like result
        mock_result = {
            "table_res_list": [
                {
                    "cell_box_list": [[0, 0, 50, 20], [50, 0, 100, 20]],
                    "pred_html": "<table><tr><td>Cell1</td><td>Cell2</td></tr></table>",
                    "table_ocr_pred": ["Cell1", "Cell2"],
                    "table_region_id": 0,
                }
            ],
            "parsing_res_list": [
                {"label": "table", "bbox": [10, 20, 200, 300]},
            ],
        }
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1
        assert results[0].html == "<table><tr><td>Cell1</td><td>Cell2</td></tr></table>"
        assert results[0].bbox == (10.0, 20.0, 200.0, 300.0)
        assert len(results[0].cells) == 2
        assert results[0].cells[0]["text"] == "Cell1"
        assert results[0].cells[1]["text"] == "Cell2"

    def test_parse_paddlex_result_empty_tables(self):
        """Test parsing PaddleX 3.x result with no tables."""
        mock_pipeline = MagicMock()

        mock_result = {
            "table_res_list": None,
            "parsing_res_list": [
                {"label": "text", "bbox": [10, 20, 200, 300]},
            ],
        }
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 0

    def test_parse_paddlex_result_multiple_tables(self):
        """Test parsing PaddleX 3.x result with multiple tables."""
        mock_pipeline = MagicMock()

        mock_result = {
            "table_res_list": [
                {
                    "cell_box_list": [[0, 0, 50, 20]],
                    "pred_html": "<table>1</table>",
                    "table_ocr_pred": ["Text1"],
                    "table_region_id": 0,
                },
                {
                    "cell_box_list": [[0, 0, 100, 40]],
                    "pred_html": "<table>2</table>",
                    "table_ocr_pred": ["Text2"],
                    "table_region_id": 1,
                },
            ],
            "parsing_res_list": [
                {"label": "table", "bbox": [10, 20, 200, 300]},
                {"label": "table", "bbox": [10, 350, 200, 600]},
            ],
        }
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 2
        assert results[0].html == "<table>1</table>"
        assert results[1].html == "<table>2</table>"
        assert results[0].bbox == (10.0, 20.0, 200.0, 300.0)
        assert results[1].bbox == (10.0, 350.0, 200.0, 600.0)

    def test_parse_paddlex_result_with_numpy_arrays(self):
        """Test parsing PaddleX 3.x result where bbox/cell_box are numpy arrays."""
        mock_pipeline = MagicMock()

        # Simulate PaddleX 3.x result with numpy arrays (real PP-StructureV3 returns these)
        mock_result = {
            "table_res_list": [
                {
                    "cell_box_list": [
                        np.array([0.0, 0.0, 50.0, 20.0]),
                        np.array([50.0, 0.0, 100.0, 20.0]),
                    ],
                    "pred_html": "<table><tr><td>A</td><td>B</td></tr></table>",
                    "table_ocr_pred": ["A", "B"],
                }
            ],
            "parsing_res_list": [
                {"label": "table", "bbox": np.array([10.0, 20.0, 200.0, 300.0])},
            ],
        }
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1
        assert results[0].bbox == (10.0, 20.0, 200.0, 300.0)
        assert results[0].html == "<table><tr><td>A</td><td>B</td></tr></table>"
        assert len(results[0].cells) == 2
        assert results[0].cells[0]["text"] == "A"
        assert results[0].cells[0]["bbox"] == [0.0, 0.0, 50.0, 20.0]
        assert results[0].cells[1]["text"] == "B"

    def test_parse_paddlex_result_with_empty_numpy_arrays(self):
        """Test parsing PaddleX 3.x result where some arrays are empty."""
        mock_pipeline = MagicMock()

        mock_result = {
            "table_res_list": [
                {
                    "cell_box_list": np.array([]),  # Empty numpy array
                    "pred_html": "<table></table>",
                    "table_ocr_pred": np.array([]),  # Empty numpy array
                }
            ],
            "parsing_res_list": [
                {"label": "table", "bbox": np.array([10.0, 20.0, 200.0, 300.0])},
            ],
        }
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1
        assert results[0].cells == []  # Empty cells list
        assert results[0].html == "<table></table>"

    def test_parse_paddlex_result_with_dict_ocr_data(self):
        """Test parsing PaddleX 3.x result with dict-format table_ocr_pred."""
        mock_pipeline = MagicMock()

        mock_result = {
            "table_res_list": [
                {
                    "cell_box_list": [[0, 0, 50, 20], [50, 0, 100, 20]],
                    "pred_html": "<table><tr><td>A</td><td>B</td></tr></table>",
                    "table_ocr_pred": {
                        "rec_texts": ["A", "B"],
                        "rec_scores": [0.99, 0.98],
                    },
                }
            ],
            "parsing_res_list": [
                {"label": "table", "bbox": [10, 20, 200, 300]},
            ],
        }
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1
        assert len(results[0].cells) == 2
        assert results[0].cells[0]["text"] == "A"
        assert results[0].cells[1]["text"] == "B"

    def test_parse_paddlex_result_no_bbox_in_parsing_res(self):
        """Test parsing PaddleX 3.x result when table bbox not in parsing_res."""
        mock_pipeline = MagicMock()

        mock_result = {
            "table_res_list": [
                {
                    "cell_box_list": [[0, 0, 50, 20]],
                    "pred_html": "<table><tr><td>A</td></tr></table>",
                    "table_ocr_pred": ["A"],
                }
            ],
            "parsing_res_list": [
                {"label": "text", "bbox": [10, 20, 200, 300]},  # Not a table
            ],
        }
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1
        # Should use default bbox [0,0,0,0] when not found
        assert results[0].bbox == (0.0, 0.0, 0.0, 0.0)


class TestIteratorResults:
    """Tests for iterator/generator result handling."""

    def test_handles_iterator_results(self):
        """Test handling of iterator results from pipeline."""
        mock_pipeline = MagicMock()

        # Return a generator instead of list
        def result_generator():
            element = MagicMock()
            element.label = "table"
            element.bbox = [0, 0, 100, 100]
            element.html = "<table></table>"
            element.score = 0.9
            element.cells = []
            mock_result = MagicMock(spec=["layout_elements"])
            mock_result.layout_elements = [element]
            yield mock_result

        mock_pipeline.predict.return_value = result_generator()

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1

    def test_handles_failed_iterator_conversion(self):
        """Test handling when iterator conversion fails."""
        mock_pipeline = MagicMock()

        # Create an object that has __iter__ but fails when converted to list
        class FailingIterator:
            def __iter__(self):
                raise RuntimeError("Iterator failed")

        mock_pipeline.predict.return_value = FailingIterator()

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        # Should return empty list, not raise
        assert results == []


class TestPathConversion:
    """Tests for path handling."""

    def test_converts_path_object_to_string(self):
        """Test that Path objects are converted to strings."""
        from pathlib import Path

        mock_pipeline = MagicMock()
        mock_pipeline.predict.return_value = []

        detector = TableDetector(pipeline=mock_pipeline)
        path = Path("/some/path/to/image.png")

        detector.detect(path)

        # Should be called with string, not Path
        mock_pipeline.predict.assert_called_with("/some/path/to/image.png")


class TestHtmlExtraction:
    """Tests for HTML extraction from different element formats."""

    def test_extracts_html_from_res_dict(self):
        """Test extracting HTML from element.res dictionary."""
        mock_pipeline = MagicMock()
        element = MagicMock()
        element.label = "table"
        element.bbox = [0, 0, 100, 100]
        element.res = {"html": "<table><tr><td>From res</td></tr></table>"}
        element.score = 0.9
        element.cells = []
        # Remove direct html attribute
        del element.html
        del element.table_html

        mock_result = MagicMock(spec=["layout_elements"])
        mock_result.layout_elements = [element]
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1
        assert results[0].html == "<table><tr><td>From res</td></tr></table>"

    def test_returns_empty_html_when_not_found(self):
        """Test empty HTML when no html attribute found."""
        mock_pipeline = MagicMock()
        element = MagicMock()
        element.label = "table"
        element.bbox = [0, 0, 100, 100]
        element.score = 0.9
        element.cells = []
        # Remove all html attributes
        del element.html
        del element.table_html
        del element.res

        mock_result = MagicMock(spec=["layout_elements"])
        mock_result.layout_elements = [element]
        mock_pipeline.predict.return_value = [mock_result]

        detector = TableDetector(pipeline=mock_pipeline)
        image = np.zeros((100, 100, 3), dtype=np.uint8)

        results = detector.detect(image)

        assert len(results) == 1
        assert results[0].html == ""


class TestTableTypeDetection:
    """Tests for table type detection."""

    def test_detects_borderless_table(self):
        """Test detection of borderless table type via _get_table_type."""
        detector = TableDetector()

        # Create mock element with borderless label
        element = MagicMock()
        element.label = "borderless_table"

        result = detector._get_table_type(element)
        assert result == "wireless"

    def test_detects_wireless_table_label(self):
        """Test detection of wireless table type."""
        detector = TableDetector()

        element = MagicMock()
        element.label = "wireless_table"

        result = detector._get_table_type(element)
        assert result == "wireless"

    def test_defaults_to_wired_table(self):
        """Test default table type is wired."""
        detector = TableDetector()

        element = MagicMock()
        element.label = "table"

        result = detector._get_table_type(element)
        assert result == "wired"

    def test_type_attribute_instead_of_label(self):
        """Test table type detection using type attribute."""
        detector = TableDetector()

        element = MagicMock()
        element.type = "wireless"
        del element.label  # Remove label

        result = detector._get_table_type(element)
        assert result == "wireless"


class TestPipelineRuntimeError:
    """Tests for pipeline runtime errors."""

    def test_raises_runtime_error_when_pipeline_none(self):
        """Test RuntimeError when pipeline is None during detect."""
        detector = TableDetector()
        detector._initialized = True  # Bypass lazy init
        detector._pipeline = None

        image = np.zeros((100, 100, 3), dtype=np.uint8)

        with pytest.raises(RuntimeError) as exc_info:
            detector.detect(image)

        assert "not initialized" in str(exc_info.value).lower()