This PR aims to add support for link extraction in pdf `hi_res`
strategy. The `partition_pdf()` function now supports link extraction
when using the `hi_res` strategy, allowing users to extract hyperlinks
from PDF documents.
### Summary
- Added functionalities to support link extraction in hi_res flow
- Enhanced word extraction functionality used for link extraction in
both `fast` and `hi_res` flows, resulted in more correct `start_index`
and `text` in `links` metadata.
- Updated ingest fixture update workflow to not skip Astra DB source
test
### Testing
```
elements = partition_pdf(
filename="example-docs/pdf/embedded-link.pdf",
strategy="hi_res"
)
assert len(elements[0].metadata.links) == 3
```
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
Co-authored-by: cragwolfe <crag@unstructured.io>
This PR implements splitting of `pdfminer` elements (`groups of text
chunks`) into smaller bounding boxes (`text lines`). This implementation
prevents loss of information from the object detection model and
facilitates more effective removal of duplicated `pdfminer` text. This
PR also addresses #3430.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
This PR aims to expand removal of `pdfminer` elements to include those
inside all `non-pdfminer` elements, not just `tables`.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
V2 refactor of ingest code introduces the removal of original file
extensions. Since the upgrade of connectors is incomplete this means
that some connectors will remove the original file extension and some
will not. Still TBD whether this is actually something we want at all.
This PR reverts specifically that change in the V2 ingest code so that
original file extension is preserved downstream.
## Testing
CI is passing with filenames updated via `Ingest Test Fixtures Update`
workflow.
---------
Co-authored-by: ryannikolaidis <ryannikolaidis@users.noreply.github.com>
### Description
This refactors the current ingest CLI process to support better
granularity in how the steps are ran
* Both multiprocessing and async now supported. Given that a lot of the
steps are IO-bound, such as downloading and uploading content, we can
achieve better parallelization by using async here
* Destination step broken up into a stager step and an upload step. This
will allow for steps that require manipulation of the data between
formats, such as converting the elements json into a csv format to
upload for tabular destinations, to be pulled out of the step that does
the actual upload.
* The process of writing the content to a local destination was now
pulled out as it's own dedicated destination connector, meaning you no
longer need to persist the content locally once the process is done if
the content was uploaded elsewhere.
* Quick update to the chunker/partition step to use the python client.
* Move the uncompress suppport as a pipeline step since this can
arbitrarily apply to any concrete files that have been downloaded,
regardless of where they came from.
* Leverage last modified date to mark files to be reprocessed, even if
the file already exists locally.
### Callouts
Retry configs haven't been moved over yet. This is an open question
because the intent was for it to wrap potential connection errors but
now any of the other steps that leverage an API might run into network
connection issues. Should those be isolated in each of the steps and
wrapped with the same retry configs? Or do we need to expose a unique
retry config for each step? This would bloat the input params even more.
### Testing
* If you want to run the new code as an SDK, there's an example file
that was added to highlight how to do that:
[example.py](https://github.com/Unstructured-IO/unstructured/blob/roman/refactor-ingest/unstructured/ingest/v2/example.py)
* If you want to run the new code as an isolated CLI:
```shell
PYTHONPATH=. python unstructured/ingest/v2/main.py --help
```
* If you want to see which commands have been migrated to the new
version, there's now a `v2` short help text next to those commands when
running the current cli:
```shell
PYTHONPATH=. python unstructured/ingest/main.py --help
Usage: main.py [OPTIONS] COMMAND [ARGS]...main.py --help
Options:
--help Show this message and exit.
Commands:
airtable
azure
biomed
box
confluence
delta-table
discord
dropbox
elasticsearch
fsspec
gcs
github
gitlab
google-drive
hubspot
jira
local v2
mongodb
notion
onedrive
opensearch
outlook
reddit
s3 v2
salesforce
sftp
sharepoint
slack
wikipedia
```
You can run any of the local or s3 specific ingest tests and these
should now work.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: rbiseck3 <rbiseck3@users.noreply.github.com>
Part two of: https://github.com/Unstructured-IO/unstructured/pull/2842
Main changes compared to part one:
* hash computation includes element's sequence number on page, page
number, document filename and its text
* there are more test for deterministic behavior of IDs returned by
partitioning functions + their uniqueness (guaranteed at the document
level, and high probability across multiple documents)
This PR addresses the following issue:
https://github.com/Unstructured-IO/unstructured/issues/2461
Part one of the issue described here:
https://github.com/Unstructured-IO/unstructured/issues/2461
It does not change how hashing algorithm works, just reworks how ids are
assigned:
> Element ID Design Principles
>
> 1. A partitioning function can assign only one of two available ID
types to a returned element: a hash or UUID.
> 2. All elements that are returned come with an ID, which is never
None.
> 3. No matter which type of ID is used, it will always be in string
format.
> 4. Partitioning a document returns elements with hashes as their
default IDs.
Big thanks to @scanny for explaining the current design and suggesting
ways to do it right, especially with chunking.
Here's the next PR in line:
https://github.com/Unstructured-IO/unstructured/pull/2673
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: micmarty-deepsense <micmarty-deepsense@users.noreply.github.com>
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>
- there are multiple places setting the default `hi_res_model_name` in
both `unstructured` and `unstructured-inference`
- they lead to inconsistency and unexpected behaviors
- this fix removes a helper in `unstructured` that tries to set the
default hi_res layout detection model; instead we rely on the
`unstructured-inference` to provide that default when no explicit model
name is passed in
## test
```bash
UNSTRUCTURED_INCLUDE_DEBUG_METADATA=true ipython
```
```python
from unstructured.partition.auto import partition
# find a pdf file
elements = partition("foo.pdf", strategy="hi_res")
assert elements[0].metadata.detection_origin == "yolox"
```
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: badGarnet <badGarnet@users.noreply.github.com>
### Summary
The goal of this PR is to keep all image elements when using "hi_res"
strategy. Previously, `Image` elements with small chunks of text were
ignored unless the image block extraction parameters
(`extract_images_in_pdf` or `extract_image_block_types`) were specified.
Now, all image elements are kept regardless of whether the image block
extraction parameters are specified.
### Testing
- on `main` branch,
```
elements = partition_pdf(
filename="example-docs/embedded-images.pdf",
strategy="hi_res",
)
image_elements = [el for el in elements if el.category == ElementType.IMAGE]
print("number of image elements: ", len(image_elements))
```
The above code will display `number of image elements: 0`.
- on this `feature` branch,
The same code will display `number of image elements: 3`
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
### Description
When passing in a remote path for fsspec-based source connectors, the
base directory was always being included in the output path itself. This
was updated to exclude the base directory any only include any child
directories relative to the base one.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: rbiseck3 <rbiseck3@users.noreply.github.com>
Canonicalize JSON produced for ingest tests such that incidental changes
is _form_ of the JSON objects (keys moving around) that does not change
the _content_ of that JSON object does not trigger an ingest-test
failure.
### Summary
Closes#2011
`languages` was missing from the metadata when partitioning pdfs via
`hi_res` and `fast` strategies and missing from image partitions via
`hi_res`. This PR adds `languages` to the relevant function calls so it
is included in the resulting elements.
### Testing
On the main branch, `partition_image` will include `languages` when
`strategy='ocr_only'`, but not when `strategy='hi_res'`:
```
filename = "example-docs/english-and-korean.png"
from unstructured.partition.image import partition_image
elements = partition_image(filename, strategy="ocr_only", languages=['eng', 'kor'])
elements[0].metadata.languages
elements = partition_image(filename, strategy="hi_res", languages=['eng', 'kor'])
elements[0].metadata.languages
```
For `partition_pdf`, `'ocr_only'` will include `languages` in the
metadata, but `'fast'` and `'hi_res'` will not.
```
filename = "example-docs/korean-text-with-tables.pdf"
from unstructured.partition.pdf import partition_pdf
elements = partition_pdf(filename, strategy="ocr_only", languages=['kor'])
elements[0].metadata.languages
elements = partition_pdf(filename, strategy="fast", languages=['kor'])
elements[0].metadata.languages
elements = partition_pdf(filename, strategy="hi_res", languages=['kor'])
elements[0].metadata.languages
```
On this branch, `languages` is included in the metadata regardless of
strategy
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: Coniferish <Coniferish@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>
### Description
* If the contents of a doc were updated by the process of
reading/downloading it, this was not being persisted. To fix this, the
data being passed around was updated to use a multiprocessing safe dict
rather than the json string. Now that dict is updated after the
`get_file` method is called.
* Wikipedia connector was updated to use a static filename rather than
one requiring a call to fetch data.
* The read config param `re_download` was not being leveraged by the
source node, this was fixed.
* Added fix: chunking and embedding order reversed so chunking runs
before embeddings
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: rbiseck3 <rbiseck3@users.noreply.github.com>
This pull request includes updated ingest test fixtures.
Please review and merge if appropriate.
Co-authored-by: benjats07 <benjats07@users.noreply.github.com>
### Summary
Some `OCR` elements with only spaces in the text have full-page width in
the bounding box, which causes the `xycut` sorting to not work as
expected. Now the logic to parse OCR results removes any elements with
only spaces (more than one space).
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
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>
## 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>
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>
- bump `unstructured-inference` to `0.6.6`
- specify default model name for element detection to be
`detectron2_onnx` to keep current behavior
- NOTE: the updated inference package by default would use yolox as
element detection model; this will be evaluated and enabled in a
separated PR
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: badGarnet <badGarnet@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>
Addresses
[#1332](https://github.com/Unstructured-IO/unstructured/issues/1332)
with `unstructured-inference` PR
[#208](https://github.com/Unstructured-IO/unstructured-inference/pull/208).
### Summary
- Add `image_path` to element metadata
- Pass parameters related to extracting images in PDF
- Preserve image elements ignored due to garbage text if
`el.metadata.image_path` is `True`
### Testing
from unstructured.partition.pdf import partition_pdf
f_path = "example-docs/embedded-images.pdf"
# default image output directory
elements = partition_pdf(
f_path,
strategy=strategy,
extract_images_in_pdf=True,
)
# specific image output directory
elements = partition_pdf(
f_path,
strategy=strategy,
extract_images_in_pdf=True,
image_output_dir_path=<directory path>,
)
**Summary**
Adds logic to combine broken numbered list for pdf fast strategy.
**Details**
Previously the document reads the numbered list items part of the
`layout-parser-paper-fast.pdf` file as:
```
'1. An off-the-shelf toolkit for applying DL models for layout detection, character'
'recognition, and other DIA tasks (Section 3)'
'2. A rich repository of pre-trained neural network models (Model Zoo) that'
'underlies the off-the-shelf usage'
'3. Comprehensive tools for efficient document image data annotation and model'
'tuning to support different levels of customization'
'4. A DL model hub and community platform for the easy sharing, distribu- tion, and discussion of DIA models and pipelines, to promote reusability, reproducibility, and extensibility (Section 4)'
```
Now it reads:
```
'1. An off-the-shelf toolkit for applying DL models for layout detection, character recognition, and other DIA tasks (Section 3)'
'2. A rich repository of pre-trained neural network models (Model Zoo) that underlies the off-the-shelf usage'
'3. Comprehensive tools for efficient document image data annotation and model' tuning to support different levels of customization'
'4. A DL model hub and community platform for the easy sharing, distribu- tion, and discussion of DIA models and pipelines, to promote reusability, reproducibility, and extensibility (Section 4)'
```
The added logic leverages `ElementType` and `coordinates` to determine
whether the following lines is a part of the previously detected
`ListItem` or not.
**Test**
Add test that checks the element length less than original version with
broken numbered list. The test also checks whether the first detected
numbered list ends with previously broken line.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: Klaijan <Klaijan@users.noreply.github.com>
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`.
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
Bumps unstructured-inference==05.23 to pull in @christinestraub's fix:
https://github.com/Unstructured-IO/unstructured-inference/pull/198 , so
embedded Images
in PDF's are now included in partition results ("hi_res").
From the perspective of elements with clean text, this is not a big win
as a lot of the images have OCR garbage. However, it is important to
preserve image elements for other downstream use cases, so overall this
is a step forward.
The issue was that for blocks detected in an image such as:
, where the full image is:
https://utic-dev-tech-fixtures.s3.us-east-2.amazonaws.com/pastebin//Users/cragwolfe/tmp/IRS-form-1987.png
, many ListItem's would be extracted that were not adding much value to
the output (assuming the block was determined to be of type List from
the layout model). This particular file is also used in ingest tests,
and you can see the prior output here:
https://github.com/Unstructured-IO/unstructured/blob/483b09b/test_unstructured_ingest/expected-structured-output/azure/IRS-form-1987.png.json#L93-L280
Test Instructions:
1. run the following snippet:
```
import json
import os
from datetime import datetime
from unstructured.__version__ import __version__
from unstructured.partition.auto import partition
from unstructured.staging.base import elements_to_json
filename = "/opt/home/tmp/IRS-form-1987.png"
output_dir = "/opt/home/tmp/json"
base_name_with_ext = os.path.basename(filename)
output_filename_part = os.path.join(output_dir, base_name_with_ext)
print(f"unstructured version: {__version__}")
#for strategy in ("hi_res", "fast", "auto"):
for strategy in ("hi_res",):
d1 = datetime.now()
elements = partition(filename=filename, strategy=strategy)
elems_as_dicts = json.loads(elements_to_json(elements, indent=2))
# strip out metadata for the sake of more readable results
for element_dict in elems_as_dicts:
del element_dict["metadata"]
json_filename=f"{output_filename_part}-{strategy}.json"
with open(json_filename, "w") as jsonf:
jsonf.write(json.dumps(elems_as_dicts, indent=2))
d2 = datetime.now()
print(f"num elements for {strategy}: {len(elements)}")
print(f"time elapsed {strategy}: {(d2-d1).total_seconds()}")
```
updating the `filename` and `output_dir` paths for your particular local
environment.
2. Open the json file that was writen to your `output_dir`, named
IRS-form-1987.png-hi_res.json
Witness the new element:
```
{
"type": "ListItem",
"element_id": "7d3ba328af2c20ddeef5d2c1d270f60f",
"text": "Long-term contracts.\u2014If you are required to change your method of accounting for long-term contracts under section 460, see Notice 87
-61 (9/21/87), 1987-38 IRB 40, for the notification procedures that must be followed Other methods. \u2014Unless the Service has Published a regulation
or procedure to the contrary, all other changes in accounting methods required by the Act are automatically considered to be approved by the Commissio
ner. Examples of method changes automatically approved by the Commissioner are those changes required to effect: (1) the repeal of the reserve method f
or bad debts of taxpayers other than financial institutions (Act section 805); (2) the repeal of the installment method for sales under a revolving cre
dit plan (Act section 812); (3) the Inclusion of income attributable to the sale or furnishing of utility services no later than the year in which the
services were provided to customers (Act section 821); and (4) the repeal of the deduction for qualified discount coupons (Act section 823). Do not fil
e Form 3115 for these changes."
},
```
### 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
```
* 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.
Set to individual_blocks for now to work around [this
bug](https://github.com/Unstructured-IO/unstructured-inference/issues/179).
I verified by printing the current ocr_mode in inference. The
`entire_page` default is overridden.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: awalker4 <awalker4@users.noreply.github.com>
Bump to unstructured-inference==0.5.13, which includes:
Fix extracted image elements being included in layout merge, addresses the issue
where an entire-page image in a PDF was not passed to the layout model when using hi_res.
More deterministic element ordering when using hi_res PDF parsing strategy (from unstructured-inference bump to 0.5.4)
Make large model available (from unstructured-inference bump to 0.5.3)
Combine inferred elements with extracted elements (from unstructured-inference bump to 0.5.2)
---------
Co-authored-by: Roman Isecke <roman@unstructured.io>
Co-authored-by: Crag Wolfe <crag@unstructured.io>
- Adds reusable validation scripts (check-x.sh) to minimize repeated (or near-repeated) code and create one source of truth
- Restructures the location of download and output folders such that they are nested in the test_unstructured_ingest directory
- Adds gitignore for output folders / files to avoid them accidentally getting checked into the repository
- Construct paths as reusable variables declared at top of scripts
- Sort order of flag for ingest calls, across all tests (this makes it easier to parse at a glance)
- OVERWRITE_FIXTURES removes all old fixtures for path to guarantee no stale results are left behind
- Bonus: don't check/exit on expected number of expected outputs when OVERWRITE_FIXTURES is true
- Bonus: exclude file_directory from Slack and Discord test scripts (match convention in all others)
