Yao You a9ff1e70b2
Fix/fix ocr region to elements bug (#3891)
This PR fixes a bug in `build_layout_elements_from_ocr_regions` where
texts are joint in incorrect orders.

The bug is due to incorrect masking of the `ocr_regions` after some are
already selected as one of the final groups. The fix uses simpler method
to mask the indices by simply use the same indices that adds the regions
to the final groups to mask them so they are not considered again.

## Testing

This PR adds a unit test specifically aimed for this bug. Without the
fix the test would fail.
Additionally any PDF files with repeated texts has a potential to
trigger this bug. e.g., create a simple pdf use the test text

```python
"LayoutParser: \n\nA Unified Toolkit for Deep Learning Based Document Image\n\nLayoutParser for Deep Learning"
```
and partition with `ocr_only` mode on main branch would hit this bug and
output text where position of the second "LayoutParser" is incorrect.
```python
[
    'LayoutParser:', 
    'A Unified Toolkit for Deep Learning Based Document Image',
    'for Deep Learning LayoutParser',
]
```
2025-01-29 12:11:17 +00:00

170 lines
5.8 KiB
Python

from unstructured_inference.inference.elements import TextRegion, TextRegions
from unstructured_inference.inference.layoutelement import LayoutElement, LayoutElements
from unstructured.documents.elements import ElementType
from unstructured.partition.pdf_image.inference_utils import (
build_layout_elements_from_ocr_regions,
merge_text_regions,
)
def test_merge_text_regions(mock_embedded_text_regions):
expected = TextRegion.from_coords(
x1=437.83888888888885,
y1=317.319341111111,
x2=1256.334784222222,
y2=406.9837855555556,
text="LayoutParser: A Unified Toolkit for Deep Learning Based Document Image",
)
merged_text_region = merge_text_regions(TextRegions.from_list(mock_embedded_text_regions))
assert merged_text_region == expected
def test_build_layout_elements_from_ocr_regions(mock_embedded_text_regions):
expected = LayoutElements.from_list(
[
LayoutElement.from_coords(
x1=437.83888888888885,
y1=317.319341111111,
x2=1256.334784222222,
y2=406.9837855555556,
text="LayoutParser: A Unified Toolkit for Deep Learning Based Document Image",
type=ElementType.UNCATEGORIZED_TEXT,
),
]
)
elements = build_layout_elements_from_ocr_regions(
TextRegions.from_list(mock_embedded_text_regions)
)
assert elements == expected
def test_build_layout_elements_from_ocr_regions_with_text(mock_embedded_text_regions):
text = "LayoutParser: A Unified Toolkit for Deep Learning Based Document Image"
expected = LayoutElements.from_list(
[
LayoutElement.from_coords(
x1=437.83888888888885,
y1=317.319341111111,
x2=1256.334784222222,
y2=406.9837855555556,
text=text,
type=ElementType.UNCATEGORIZED_TEXT,
),
]
)
elements = build_layout_elements_from_ocr_regions(
TextRegions.from_list(mock_embedded_text_regions),
text,
group_by_ocr_text=True,
)
assert elements == expected
def test_build_layout_elements_from_ocr_regions_with_multi_line_text(mock_embedded_text_regions):
text = "LayoutParser: \n\nA Unified Toolkit for Deep Learning Based Document Image"
elements = build_layout_elements_from_ocr_regions(
TextRegions.from_list(mock_embedded_text_regions),
text,
group_by_ocr_text=True,
)
assert elements == LayoutElements.from_list(
[
LayoutElement.from_coords(
x1=453.00277777777774,
y1=317.319341111111,
x2=711.5338541666665,
y2=358.28571222222206,
text="LayoutParser:",
type=ElementType.UNCATEGORIZED_TEXT,
),
LayoutElement.from_coords(
x1=437.83888888888885,
y1=317.319341111111,
x2=1256.334784222222,
y2=406.9837855555556,
text="A Unified Toolkit for Deep Learning Based Document Image",
type=ElementType.UNCATEGORIZED_TEXT,
),
]
)
def test_build_layout_elements_from_ocr_regions_with_repeated_texts(mock_embedded_text_regions):
mock_embedded_text_regions.extend(
[
LayoutElement.from_coords(
x1=453.00277777777774,
y1=417.319341111111,
x2=711.5338541666665,
y2=458.28571222222206,
text="LayoutParser",
type=ElementType.UNCATEGORIZED_TEXT,
),
LayoutElement.from_coords(
x1=453.00277777777774,
y1=468.319341111111,
x2=711.5338541666665,
y2=478.28571222222206,
text="for",
type=ElementType.UNCATEGORIZED_TEXT,
),
LayoutElement.from_coords(
x1=453.00277777777774,
y1=488.319341111111,
x2=711.5338541666665,
y2=500.28571222222206,
text="Deep",
type=ElementType.UNCATEGORIZED_TEXT,
),
LayoutElement.from_coords(
x1=453.00277777777774,
y1=510.319341111111,
x2=711.5338541666665,
y2=550.28571222222206,
text="Learning",
type=ElementType.UNCATEGORIZED_TEXT,
),
]
)
text = (
"LayoutParser: \n\nA Unified Toolkit for Deep Learning Based Document Image\n\n"
"LayoutParser for Deep Learning"
)
elements = build_layout_elements_from_ocr_regions(
TextRegions.from_list(mock_embedded_text_regions),
text,
group_by_ocr_text=True,
)
assert elements == LayoutElements.from_list(
[
LayoutElement.from_coords(
x1=453.00277777777774,
y1=317.319341111111,
x2=711.5338541666665,
y2=358.28571222222206,
text="LayoutParser:",
type=ElementType.UNCATEGORIZED_TEXT,
),
LayoutElement.from_coords(
x1=437.83888888888885,
y1=317.319341111111,
x2=1256.334784222222,
y2=406.9837855555556,
text="A Unified Toolkit for Deep Learning Based Document Image",
type=ElementType.UNCATEGORIZED_TEXT,
),
LayoutElement.from_coords(
x1=453.00277777777774,
y1=417.319341111111,
x2=711.5338541666665,
y2=550.28571222222206,
text="LayoutParser for Deep Learning",
type=ElementType.UNCATEGORIZED_TEXT,
),
]
)