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Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
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import pytest
import unstructured_pytesseract
from pdf2image.exceptions import PDFPageCountError
from PIL import Image, UnidentifiedImageError
from unstructured_inference.inference.elements import EmbeddedTextRegion, TextRegion
from unstructured_inference.inference.layout import DocumentLayout
from unstructured_inference.inference.layoutelement import (
LayoutElement,
)
from unstructured.partition import ocr
from unstructured.partition.ocr import pad_element_bboxes
from unstructured.partition.utils.ocr_models import paddle_ocr
@pytest.mark.parametrize(
("is_image", "expected_error"),
[
(True, UnidentifiedImageError),
(False, PDFPageCountError),
],
)
def test_process_data_with_ocr_invalid_file(is_image, expected_error):
invalid_data = b"i am not a valid file"
with pytest.raises(expected_error):
_ = ocr.process_data_with_ocr(
data=invalid_data,
is_image=is_image,
out_layout=DocumentLayout(),
)
@pytest.mark.parametrize(
("is_image"),
[
(True),
(False),
],
)
def test_process_file_with_ocr_invalid_filename(is_image):
invalid_filename = "i am not a valid file name"
with pytest.raises(FileNotFoundError):
_ = ocr.process_file_with_ocr(
filename=invalid_filename,
is_image=is_image,
out_layout=DocumentLayout(),
)
# TODO(yuming): Add this for test coverage, please update/move it in CORE-1886
def test_supplement_page_layout_with_ocr_invalid_ocr(monkeypatch):
monkeypatch.setenv("ENTIRE_PAGE_OCR", "invalid_ocr")
with pytest.raises(ValueError):
_ = ocr.supplement_page_layout_with_ocr(
page_layout=None,
image=None,
)
def test_get_ocr_layout_from_image_tesseract(monkeypatch):
monkeypatch.setattr(
unstructured_pytesseract,
"image_to_data",
lambda *args, **kwargs: {
"level": ["line", "line", "word"],
"left": [10, 20, 30],
"top": [5, 15, 25],
"width": [15, 25, 35],
"height": [10, 20, 30],
"text": ["Hello", "World", "!"],
},
)
image = Image.new("RGB", (100, 100))
ocr_layout = ocr.get_ocr_layout_from_image(
image,
ocr_languages="eng",
entire_page_ocr="tesseract",
)
expected_layout = [
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
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TextRegion.from_coords(10, 5, 25, 15, "Hello", source="OCR-tesseract"),
TextRegion.from_coords(20, 15, 45, 35, "World", source="OCR-tesseract"),
TextRegion.from_coords(30, 25, 65, 55, "!", source="OCR-tesseract"),
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
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]
assert ocr_layout == expected_layout
def mock_ocr(*args, **kwargs):
return [
[
(
[(10, 5), (25, 5), (25, 15), (10, 15)],
["Hello"],
),
],
[
(
[(20, 15), (45, 15), (45, 35), (20, 35)],
["World"],
),
],
[
(
[(30, 25), (65, 25), (65, 55), (30, 55)],
["!"],
),
],
]
def monkeypatch_load_agent():
class MockAgent:
def __init__(self):
self.ocr = mock_ocr
return MockAgent()
def test_get_ocr_layout_from_image_paddle(monkeypatch):
monkeypatch.setattr(
paddle_ocr,
"load_agent",
monkeypatch_load_agent,
)
image = Image.new("RGB", (100, 100))
ocr_layout = ocr.get_ocr_layout_from_image(image, ocr_languages="eng", entire_page_ocr="paddle")
expected_layout = [
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
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TextRegion.from_coords(10, 5, 25, 15, "Hello", source="OCR-paddle"),
TextRegion.from_coords(20, 15, 45, 35, "World", source="OCR-paddle"),
TextRegion.from_coords(30, 25, 65, 55, "!", source="OCR-paddle"),
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
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]
assert ocr_layout == expected_layout
def test_get_ocr_text_from_image_tesseract(monkeypatch):
monkeypatch.setattr(
unstructured_pytesseract,
"image_to_string",
lambda *args, **kwargs: {"text": "Hello World"},
)
image = Image.new("RGB", (100, 100))
ocr_text = ocr.get_ocr_text_from_image(image, ocr_languages="eng", entire_page_ocr="tesseract")
assert ocr_text == "Hello World"
def test_get_ocr_text_from_image_paddle(monkeypatch):
monkeypatch.setattr(
paddle_ocr,
"load_agent",
monkeypatch_load_agent,
)
image = Image.new("RGB", (100, 100))
ocr_text = ocr.get_ocr_text_from_image(image, ocr_languages="eng", entire_page_ocr="paddle")
assert ocr_text == "HelloWorld!"
@pytest.fixture()
def mock_ocr_regions():
return [
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
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EmbeddedTextRegion.from_coords(10, 10, 90, 90, text="0", source=None),
EmbeddedTextRegion.from_coords(200, 200, 300, 300, text="1", source=None),
EmbeddedTextRegion.from_coords(500, 320, 600, 350, text="3", source=None),
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
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]
@pytest.fixture()
def mock_out_layout(mock_embedded_text_regions):
return [
LayoutElement(
text=None,
source=None,
type="Text",
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
bbox=r.bbox,
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
)
for r in mock_embedded_text_regions
]
def test_aggregate_ocr_text_by_block():
expected = "A Unified Toolkit"
ocr_layout = [
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
TextRegion.from_coords(0, 0, 20, 20, "A"),
TextRegion.from_coords(50, 50, 150, 150, "Unified"),
TextRegion.from_coords(150, 150, 300, 250, "Toolkit"),
TextRegion.from_coords(200, 250, 300, 350, "Deep"),
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
]
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
region = TextRegion.from_coords(0, 0, 250, 350, "")
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
text = ocr.aggregate_ocr_text_by_block(ocr_layout, region, 0.5)
assert text == expected
def test_merge_text_regions(mock_embedded_text_regions):
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
expected = TextRegion.from_coords(
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
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 = ocr.merge_text_regions(mock_embedded_text_regions)
assert merged_text_region == expected
def test_get_elements_from_ocr_regions(mock_embedded_text_regions):
expected = [
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
LayoutElement.from_coords(
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
x1=437.83888888888885,
y1=317.319341111111,
x2=1256.334784222222,
y2=406.9837855555556,
text="LayoutParser: A Unified Toolkit for Deep Learning Based Document Image",
type="UncategorizedText",
),
]
elements = ocr.get_elements_from_ocr_regions(mock_embedded_text_regions)
assert elements == expected
@pytest.fixture()
def mock_layout(mock_embedded_text_regions):
return [
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
LayoutElement(text=r.text, type="UncategorizedText", bbox=r.bbox)
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
for r in mock_embedded_text_regions
]
@pytest.fixture()
def mock_embedded_text_regions():
return [
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
EmbeddedTextRegion.from_coords(
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
x1=453.00277777777774,
y1=317.319341111111,
x2=711.5338541666665,
y2=358.28571222222206,
text="LayoutParser:",
),
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
EmbeddedTextRegion.from_coords(
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
x1=726.4778125,
y1=317.319341111111,
x2=760.3308594444444,
y2=357.1698966666667,
text="A",
),
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
EmbeddedTextRegion.from_coords(
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
x1=775.2748177777777,
y1=317.319341111111,
x2=917.3579885555555,
y2=357.1698966666667,
text="Unified",
),
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
EmbeddedTextRegion.from_coords(
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
x1=932.3019468888888,
y1=317.319341111111,
x2=1071.8426522222221,
y2=357.1698966666667,
text="Toolkit",
),
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
EmbeddedTextRegion.from_coords(
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
x1=1086.7866105555556,
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text="for",
),
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
EmbeddedTextRegion.from_coords(
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
x1=1156.154472611111,
y1=317.319341111111,
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y2=357.1698966666667,
text="Deep",
),
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
EmbeddedTextRegion.from_coords(
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
x1=437.83888888888885,
y1=367.13322999999986,
x2=610.0171992222222,
y2=406.9837855555556,
text="Learning",
),
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
EmbeddedTextRegion.from_coords(
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
x1=624.9611575555555,
y1=367.13322999999986,
x2=741.6754646666665,
y2=406.9837855555556,
text="Based",
),
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
EmbeddedTextRegion.from_coords(
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
x1=756.619423,
y1=367.13322999999986,
x2=958.3867708333332,
y2=406.9837855555556,
text="Document",
),
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
EmbeddedTextRegion.from_coords(
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
x1=973.3307291666665,
y1=367.13322999999986,
x2=1092.0535042777776,
y2=406.9837855555556,
text="Image",
),
]
def test_supplement_layout_with_ocr_elements(mock_layout, mock_ocr_regions):
ocr_elements = [
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
LayoutElement(text=r.text, source=None, type="UncategorizedText", bbox=r.bbox)
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
for r in mock_ocr_regions
]
final_layout = ocr.supplement_layout_with_ocr_elements(mock_layout, mock_ocr_regions)
# Check if the final layout contains the original layout elements
for element in mock_layout:
assert element in final_layout
# Check if the final layout contains the OCR-derived elements
assert any(ocr_element in final_layout for ocr_element in ocr_elements)
# Check if the OCR-derived elements that are subregions of layout elements are removed
for element in mock_layout:
for ocr_element in ocr_elements:
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
if ocr_element.bbox.is_almost_subregion_of(
element.bbox,
ocr.SUBREGION_THRESHOLD_FOR_OCR,
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
):
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
assert ocr_element not in final_layout
def test_merge_out_layout_with_ocr_layout(mock_out_layout, mock_ocr_regions):
ocr_elements = [
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
LayoutElement(text=r.text, source=None, type="UncategorizedText", bbox=r.bbox)
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
for r in mock_ocr_regions
]
final_layout = ocr.merge_out_layout_with_ocr_layout(mock_out_layout, mock_ocr_regions)
# Check if the out layout's text attribute is updated with aggregated OCR text
assert final_layout[0].text == mock_ocr_regions[2].text
# Check if the final layout contains both original elements and OCR-derived elements
assert all(element in final_layout for element in mock_out_layout)
assert any(element in final_layout for element in ocr_elements)
@pytest.mark.parametrize(
("padding", "expected_bbox"),
[
(5, (5, 15, 35, 45)),
(-3, (13, 23, 27, 37)),
(2.5, (7.5, 17.5, 32.5, 42.5)),
(-1.5, (11.5, 21.5, 28.5, 38.5)),
],
)
def test_pad_element_bboxes(padding, expected_bbox):
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
element = LayoutElement.from_coords(
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
x1=10,
y1=20,
x2=30,
y2=40,
text="",
source=None,
type="UncategorizedText",
)
expected_original_element_bbox = (10, 20, 30, 40)
padded_element = pad_element_bboxes(element, padding)
padded_element_bbox = (
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
padded_element.bbox.x1,
padded_element.bbox.y1,
padded_element.bbox.x2,
padded_element.bbox.y2,
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
)
assert padded_element_bbox == expected_bbox
# make sure the original element has not changed
chore: process chipper hierarchy (#1634) PR to support schema changes introduced from [PR 232](https://github.com/Unstructured-IO/unstructured-inference/pull/232) in `unstructured-inference`. Specifically what needs to be supported is: * Change to the way `LayoutElement` from `unstructured-inference` is structured, specifically that this class is no longer a subclass of `Rectangle`, and instead `LayoutElement` has a `bbox` property that captures the location information and a `from_coords` method that allows construction of a `LayoutElement` directly from coordinates. * Removal of `LocationlessLayoutElement` since chipper now exports bounding boxes, and if we need to support elements without bounding boxes, we can make the `bbox` property mentioned above optional. * Getting hierarchy data directly from the inference elements rather than in post-processing * Don't try to reorder elements received from chipper v2, as they should already be ordered. #### Testing: The following demonstrates that the new version of chipper is inferring hierarchy. ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper") children = [el for el in elements if el.metadata.parent_id is not None] print(children) ``` Also verify that running the traditional `hi_res` gives different results: ```python from unstructured.partition.pdf import partition_pdf elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res") ``` --------- Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com>
2023-10-12 20:28:46 -05:00
original_element_bbox = (element.bbox.x1, element.bbox.y1, element.bbox.x2, element.bbox.y2)
Refactor: support entire page OCR with `ocr_mode` and `ocr_languages` (#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in https://github.com/Unstructured-IO/unstructured-inference/pull/231. This PR adds OCR process logics to entire page OCR, and support two OCR modes, "entire_page" or "individual_blocks". The updated workflow for `Hi_res` partition: * pass the document as data/filename to inference repo to get `inferred_layout` (DocumentLayout) * pass the document as data/filename to OCR module, which first open the document (create temp file/dir as needed), and split the document by pages (convert PDF pages to image pages for PDF file) * if ocr mode is `"entire_page"` * OCR the entire image * merge the OCR layout with inferred page layout * if ocr mode is `"individual_blocks"` * from inferred page layout, find element with no extracted text, crop the entire image by the bboxes of the element * replace empty text element with the text obtained from OCR the cropped image * return all merged PageLayouts and form a DocumentLayout subject for later on process This PR also bump `unstructured-inference==0.7.2` since the branch relay on OCR refactor from unstructured-inference. ## Test ``` from unstructured.partition.auto import partition entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res") individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res") print([el.text for el in entrie_page_ocr_mode_elements]) print([el.text for el in individual_blocks_ocr_mode_elements]) ``` latest output: ``` # entrie_page ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고'] # individual_blocks ['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email'] ``` --------- Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com> Co-authored-by: yuming-long <yuming-long@users.noreply.github.com> Co-authored-by: christinestraub <christinemstraub@gmail.com> Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
2023-10-06 18:54:49 -04:00
assert original_element_bbox == expected_original_element_bbox