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b30d6a601e
Closes GH Issue #1209. ### Summary - add swapped `xycut` sorting - update `xycut` sorting evaluation script PDFs: - [sbaa031.073.pdf](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7234218/pdf/sbaa031.073.pdf) - [multi-column-2p.pdf](https://github.com/Unstructured-IO/unstructured/files/12796147/multi-column-2p.pdf) - [11723901.pdf](https://github.com/Unstructured-IO/unstructured-inference/files/12360085/11723901.pdf) ### Testing ``` elements = partition_pdf("sbaa031.073.pdf", strategy="hi_res") print("\n\n".join([str(el) for el in elements])) ``` ### Evaluation ``` PYTHONPATH=. python examples/custom-layout-order/evaluate_xy_cut_sorting.py sbaa031.073.pdf hi_res xycut_only ```
61 lines
2.1 KiB
Python
61 lines
2.1 KiB
Python
import numpy as np
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import pytest
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from unstructured.partition.utils.xycut import (
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projection_by_bboxes,
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recursive_xy_cut,
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recursive_xy_cut_swapped,
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split_projection_profile,
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)
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def test_projection_by_bboxes():
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boxes = np.array([[10, 20, 50, 60], [30, 40, 70, 80]])
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# Test case 1: Horizontal projection
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result_horizontal = projection_by_bboxes(boxes, 0)
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expected_result_horizontal = np.array(
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
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)
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assert np.array_equal(result_horizontal[:30], expected_result_horizontal)
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# Test case 2: Vertical projection
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result_vertical = projection_by_bboxes(boxes, 1)
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expected_result_vertical = np.array(
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
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)
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assert np.array_equal(result_vertical[:30], expected_result_vertical)
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def test_split_projection_profile():
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# Test case 1: Sample projection profile with given min_value and min_gap
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arr_values = np.array([0, 0, 3, 4, 0, 0, 2, 0, 0, 0, 5, 6, 7, 0, 0, 0])
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min_value = 0
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min_gap = 1
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result = split_projection_profile(arr_values, min_value, min_gap)
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expected_result = (np.array([2, 6, 10]), np.array([4, 7, 13]))
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assert np.array_equal(result, expected_result)
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# Test case 2: Another sample projection profile with different parameters
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arr_values = np.array([0, 2, 0, 0, 0, 3, 0, 0, 4, 5, 6, 0, 0, 0])
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min_value = 1
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min_gap = 2
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result = split_projection_profile(arr_values, min_value, min_gap)
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expected_result = (np.array([1, 5, 8]), np.array([2, 6, 11]))
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assert np.array_equal(result, expected_result)
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@pytest.mark.parametrize(
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("recursive_func", "expected"),
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[
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(recursive_xy_cut, [0, 1, 2]),
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(recursive_xy_cut_swapped, [0, 2, 1]),
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],
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)
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def test_recursive_xy_cut(recursive_func, expected):
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boxes = np.array([[0, 0, 20, 20], [200, 0, 230, 30], [0, 40, 50, 50]])
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indices = np.array([0, 1, 2])
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res = []
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recursive_func(boxes, indices, res)
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assert res == expected
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