Refactor: Remove OCR related code for entire page OCR #231
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
yuming-long
force-pushed
the
yuming/remove_ocr_code
branch
from
041c465 to
12c30c3
Compare
yuming-long
force-pushed
the
yuming/remove_ocr_code
branch
from
12c30c3 to
abd95d1
Compare
yuming-long
changed the title
benjats07
suggested changes
Oct 3, 2023
benjats07
approved these changes
Oct 4, 2023
christinestraub
requested changes
Oct 4, 2023
christinestraub
changed the title
cragwolfe
reviewed
Oct 4, 2023
christinestraub
requested changes
Oct 4, 2023
cragwolfe
approved these changes
Oct 5, 2023
github-merge-queue bot
pushed a commit
to Unstructured-IO/unstructured
that referenced
this pull request
Oct 6, 2023
…#1579) ## Summary Second part of OCR refactor to move it from inference repo to unstructured repo, first part is done in Unstructured-IO/unstructured-inference#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 [email protected] 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 [email protected] 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 <[email protected]> Co-authored-by: yuming-long <[email protected]> Co-authored-by: christinestraub <[email protected]> Co-authored-by: christinestraub <[email protected]>
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Summary
First part of OCR refactor to move it from inference repo to unstructured repo. This PR removes all OCR related code for entire page OCR, which means all table related OCR still remain the same (will be moved after table refactor to accept preprocessed OCR data)
Test
Please see test description in Unstructured-IO/unstructured#1579, since those two need to work together.
Note
The ingest test won't pass until we merge the unstructured refactor PR