This PR introduces GLOBAL_WORKING_DIR and GLOBAL_WORKING_PROCESS_DIR
controlling where temporary files are stored during partition flow, via
tempfile.tempdir.
#### Edit:
Renamed prefixes from STORAGE_ to UNSTRUCTURED_CACHE_
#### Edit 2:
Renamed prefixes from UNSTRUCTURED_CACHE to GLOBAL_WORKING_DIR_
**Summary**
File-types other than PDF need to use OCR on extracted images. Extract
`OCRAgent.get_agent()` such that any file-type partitioner can use it
without risking dependency on PDF-only extras.
This PR aims to remove duplicate embedded images taken by `PDFminer`.
### Summary
- add `clean_pdfminer_duplicate_image_elements()` to remove embedded
images with similar `bboxes` and the same `text`
- add env_config `EMBEDDED_IMAGE_SAME_REGION_THRESHOLD` to consider the
bounding boxes of two embedded images as the same region
- refactor: reorganzie `clean_pdfminer_inner_elements()`
This PR is the second part of fixing "embedded text not getting merged
with inferred elements", the first part is done in
https://github.com/Unstructured-IO/unstructured-inference/pull/331.
### Summary
- replace `Rectangle.is_in()` with `Rectangle.is_almost_subregion_of()`
when removing pdfminer (embedded) elements that were merged with
inferred elements
- use env_config `EMBEDDED_TEXT_AGGREGATION_SUBREGION_THRESHOLD`
introduced in the [first
part](https://github.com/Unstructured-IO/unstructured-inference/pull/331)
when removing pdfminer (embedded) elements that were merged with
inferred elements
- bump `unstructured-inference` to 0.7.25
### Testing
PDF:
[pwc-financial-statements-p114.pdf](https://github.com/Unstructured-IO/unstructured/files/14707146/pwc-financial-statements-p114.pdf)
```
$ pip uninstall unstructured-inference -y
$ git clone -b fix/embedded-text-not-getting-merged-with-inferred-elements git@github.com:Unstructured-IO/unstructured-inference.git && cd unstructured-inference
$ pip install -e .
```
```
elements = partition_pdf(
filename="pwc-financial-statements-p114.pdf",
strategy="hi_res",
infer_table_structure=True,
extract_image_block_types=["Image"],
)
table_elements = [el for el in elements if el.category == "Table"]
print(table_elements[0].text)
```
---------
Co-authored-by: Antonio Jose Jimeno Yepes <antonio.jimeno@gmail.com>
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
**Summary**
The serialization and deserialization (serde) of
`metadata.orig_elements` will be located in `unstructured.staging.base`
alongside `elements_to_json()` and other existing serde functions.
Improve the typing, readability, and structure of that module before
adding the new serde functions for `metadata.orig_elements`.
**Reviewers:** The commits are well-groomed and are probably quicker to
review commit-by-commit than as all files-changed at once.
### Summary
This PR is the second part of `pdfminer` refactor to move it from
`unstructured-inference` repo to `unstructured` repo, the first part is
done in
https://github.com/Unstructured-IO/unstructured-inference/pull/294. This
PR adds logic to merge the extracted layout with the inferred layout.
The updated workflow for the `hi_res` strategy:
* pass the document (as data/filename) to the `inference` repo to get
`inferred_layout` (DocumentLayout)
* pass the `inferred_layout` returned from the `inference` repo and the
document (as data/filename) to the `pdfminer_processing` module, which
first opens the document (create temp file/dir as needed), and splits
the document by pages
* if is_image is `True`, return the passed
inferred_layout(DocumentLayout)
* if is_image is `False`:
* get extracted_layout (TextRegions) from the passed
document(data/filename) by pdfminer
* merge `extracted_layout` (TextRegions) with the passed
`inferred_layout` (DocumentLayout)
* return the `inferred_layout `(DocumentLayout) with updated elements
(all merged LayoutElements) as merged_layout (DocumentLayout)
* pass merged_layout and the document (as data/filename) to the `OCR`
module, which first opens the document (create temp file/dir as needed),
and splits the document by pages (convert PDF pages to image pages for
PDF file)
### Note
This PR also fixes issue #2164 by using functionality similar to the one
implemented in the `fast` strategy workflow when extracting elements by
`pdfminer`.
### TODO
* image extraction refactor to move it from `unstructured-inference`
repo to `unstructured` repo
* improving natural reading order by applying the current default
`xycut` sorting to the elements extracted by `pdfminer`
### Summary
Update `ocr_only` strategy in `partition_pdf()`. This PR adds the
functionality to get accurate coordinate data when partitioning PDFs and
Images with the `ocr_only` strategy.
- Add functionality to perform OCR region grouping based on the OCR text
taken from `pytesseract.image_to_string()`
- Add functionality to get layout elements from OCR regions (ocr_layout)
for both `tesseract` and `paddle`
- Add functionality to determine the `source` of merged text regions
when merging text regions in `merge_text_regions()`
- Merge multiple test functions related to "ocr_only" strategy into
`test_partition_pdf_with_ocr_only_strategy()`
- This PR also fixes [issue
#1792](https://github.com/Unstructured-IO/unstructured/issues/1792)
### Evaluation
```
# Image
PYTHONPATH=. python examples/custom-layout-order/evaluate_natural_reading_order.py example-docs/double-column-A.jpg ocr_only xy-cut image
# PDF
PYTHONPATH=. python examples/custom-layout-order/evaluate_natural_reading_order.py example-docs/multi-column-2p.pdf ocr_only xy-cut pdf
```
### Test
- **Before update**
All elements have the same coordinate data

- **After update**
All elements have accurate coordinate data

---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
This PR introduces `clean_pdfminer_inner_elements` , which deletes
pdfminer elements inside other detection origins such as YoloX or
detectron.
This function returns the clean document.
Also, the ingest-test fixtures were updated to reflect the new standard
output.
The best way to check that this function is working properly is check
the new test `test_clean_pdfminer_inner_elements` in
`test_unstructured/partition/utils/test_processing_elements.py`
---------
Co-authored-by: Roman Isecke <roman@unstructured.io>
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: rbiseck3 <rbiseck3@users.noreply.github.com>
Co-authored-by: Roman Isecke <136338424+rbiseck3@users.noreply.github.com>
Closes#1573.
### Summary
- update `shrink_bbox()` to keep top left rather than center
### Evaluation
Run the following command for this
[PDF](https://utic-dev-tech-fixtures.s3.us-east-2.amazonaws.com/pastebin/patent-11723901-page2.pdf).
```
PYTHONPATH=. python examples/custom-layout-order/evaluate_xy_cut_sorting.py <file_path> <strategy>
```
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Closes GH Issue #1233.
### Summary
- add functionality to shrink all bounding boxes along x and y axes
(still centered around the same center point) before running xy-cut sort
### Evaluation
Run the followin gcommand for this
[PDF](https://utic-dev-tech-fixtures.s3.us-east-2.amazonaws.com/pastebin/patent-11723901-page2.pdf).
PYTHONPATH=. python examples/custom-layout-order/evaluate_xy_cut_sorting.py <file_path> <strategy>
The default sorting algorithm for PDF's, "xycut," would cause an error
when partitioning a document if Y coordinate points were negative. This
change checks for that condition (or more broadly, any negative
coordinates) and falls back to the "basic" sort if that is the case.
This PR does not address the underlying issue of "bad points" which
still should be investigated. However, the sorting code should be less
brittle to unexpected bounding boxes in the first case.
Resolves: https://github.com/Unstructured-IO/unstructured/issues/1296