Currently there are some cases when `partition_pdf` is run using the
`hi_res` strategy, in which elements can come back with category
`UncategorizedText`. This happens when the detection model fails to
detect an element, but we're able to find it anyway either because it
was embedded in the PDF, or we found it using OCR.
This commit is to allow for attempting to categorize these uncategorized
elements using our text-based classification function,
`element_from_text`.
### Summary
In order to support language functionality other than Tesseract OCR, we
want to represent languages provided for either partitioning accuracy or
OCR as a standard list of langcodes as strings.
### Details
Adds `languages` (a list of strings) as a parameter to pdf partitioning
functions. Marks `ocr_languages` for deprecation. Adds a new file
`lang.py` for language-related helper functions.
Coming up: langcode standardization, language detection
### Test
Call `partition_pdf` or `partition_pdf_or_image` with a variety of
strategies, languages, or `ocr_languages`.
- inclusion of `ocr_languages` as a parameter should display a
deprecation warning
- the other valid call outputs should be no different from the current
outputs.
ex:
```
from unstructured.partition.pdf import partition_pdf
elements = partition_pdf(filename="example-docs/DA-1p.pdf", strategy="hi_res", languages=["eng", "spa"])
print("\n\n".join([str(el) for el in elements]))
```
### Summary
Partial solution to #1185.
Related to #1222.
Creates decorator from `chunk_by_title` cleaning brick.
Breaks a document into sections based on the presence of Title elements.
Also starts a new section under the following conditions:
- If metadata changes, indicating a change in section or page or a
switch to processing attachments. If `multipage_sections=True`, sections
can span pages. `multipage_sections` defaults to True.
- If the length of the section exceeds `new_after_n_chars` characters.
The default is 1500. The **chunking function does not split individual
elements**, so it's possible for a section to exceed that threshold if
an individual element if over `new_after_n_chars characters`, which
could occur with a long NarrativeText element.
Combines sections under these conditions
- Sections under `combine_under_n_chars` characters are combined. The
default is 500.
### Testing
from unstructured.partition.html import partition_html
url = "https://understandingwar.org/backgrounder/russian-offensive-campaign-assessment-august-27-2023-0"
chunks = partition_html(url=url, chunking_strategy="by_title")
for chunk in chunks:
print(chunk)
print("\n\n" + "-"*80)
input()
If a layout model is used from unstructured-inference, you get back
class probabilities in the element metadata from partition.
extra-pdf-image-in in requirements already has the newest version of
unstructured-inference in there without a pinned version. Is there any
place else that the unstructured-inference version needs to be updated
to the required release version, 0.5.22?
- revert the layout parser fast pdf file to original with just two pages
- add a new file that has one empty page and one page says "this page is
intentionally left blank" for tests
This PR resolves#1247 by using the matching elements and bbox for
coordinate computation.
This PR also updates the example doc
`example-docs/layout-parser-paper-fast.pdf` so that it includes a true
blank page and a page with text "this page is intentionally left blank".
This change helps us testing:
- differences between fast and hi_res
- code handling empty pages in between pages with contents (which
triggers the bug found in #1247 )
Lastly, this PR updates the names of the variables inside
`_partition_pdf_or_image_with_ocr` so that matching inputs all starts
with `_` like `_elements`, `_text`, and `_bboxes` to improve
readability.
This change also improves partition performance for multi-page pdfs as
it reduces the amount of iterations inside
`add_pytesseract_bbox_to_elements`. Testing locally on m2 mac + Rocky
docker shows it reduces partition time for DA-619p.pdf file from around
1min to around 23s.
Update `test_json` to not use auto partition due to dependencies. Previously, to run `test_json` requires full requirements installation library to read file types, including but not limited to, docx, pptx, as well as others. Therefore the test will raise error with base installation. With the update, this fix also add to other test files to check its invariant with `elements_to_json`.
### Summary
Address
[#1136](https://github.com/Unstructured-IO/unstructured/issues/1136) for
`hi_res` and `fast` strategies. The `ocr_only` strategy does not include
coordinates.
- add functionality to switch sort mode between the current `basic`
sorting and the new `xy-cut` sorting for `hi_res` and `fast` strategies
- add the script to evaluate the `xy-cut` sorting approach
- add jupyter notebook to provide evaluation and visualization for the
`xy-cut` sorting approach
### Evaluation
```
export PYTHONPATH=.:$PYTHONPATH && python examples/custom-layout-order/evaluate_xy_cut_sorting.py <file_path> <strategy>
```
Here, the file should be under the project root directory. For example,
```
export PYTHONPATH=.:$PYTHONPATH && python examples/custom-layout-order/evaluate_xy_cut_sorting.py example-docs/multi-column-2p.pdf fast
```
Add test case test_partition_image_with_multipage_tiff that reads multipage TIFF file and
- confirms that the function reads all the pages in the TIFF.
- page number is added to the metadata
This PR is branched from and developed on top of 6d6be99 commit.
- fixes#1079 where partitioning is happening twice in the case of
`strategy="ocr_only"`
- only calls `extractable_elements` if we can predetermine that
`ocr_only` is not a possible strategy even if it was the intended
strategy.
- Adds additional assertion test that `_partition_pdf_or_image_with_ocr`
is not called when falling back to `fast` from `ocr_only`
* pip-compile in order to bump unstructured-inference
* Set the default `ocr_mode` back to `enitre_page` now that [this
error](https://github.com/Unstructured-IO/unstructured-inference/pull/183)
is addressed
* Explicitly add `sphinx-tabs` to `build.in`. This file provides
`docs/requirements.txt`.
* Remove a pinned `pydantic` version
* Fix a makefile command to `pip-compile` a missing ingest file.
**Summary**
Closes#747
* Create CI Pipeline for running text, xml, email, and html doc tests
against the library installed without extras
* Create CI Pipeline for running each library extra against their
respective tests
