Thanks to visit codestin.com
Credit goes to github.com

Skip to content

Fix tesseract preprocessor for blank pages #202

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
JSv4 wants to merge 6 commits into
base: main
Choose a base branch
from
Open

Fix tesseract preprocessor for blank pages #202

Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
a7124cf
Line 43 of cli.pawls.preprocessors.tesseract in extract_page_tokens()…
JSv4 Feb 3, 2023
e2bec40
Merge pull request #1 from JSv4/JSv4/fix-parsing-failure-where-page-i…
JSv4 Feb 3, 2023
7de52c5
Merge branch 'allenai:main' into main
JSv4 Feb 25, 2023
7fbdcec
modified extract_page_tokens() in cli.pawls.preprocessors.tesseract t…
JSv4 Feb 26, 2023
cc262fe
Accidentally created two copies of scrubbed df. Cleaned up.
JSv4 Feb 26, 2023
84e7c8e
Accidentally created two copies of scrubbed df. Cleaned up.
JSv4 Feb 26, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
13 changes: 10 additions & 3 deletions cli/pawls/preprocessors/tesseract.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -28,10 +28,17 @@ def extract_page_tokens(
res = pd.read_csv(
io.StringIO(_data), quoting=csv.QUOTE_NONE, encoding="utf-8", sep="\t"
)
# An implementation adopted from https://github.com/Layout-Parser/layout-parser/blob/20de8e7adb0a7d7740aed23484fa8b943126f881/src/layoutparser/ocr.py#L475

# An implementation adopted from https://github.com/Layout-Parser/layout-parser/blob
# /20de8e7adb0a7d7740aed23484fa8b943126f881/src/layoutparser/ocr.py#L475
res_without_na_text_rows = res[~res.text.isna()]

if res_without_na_text_rows.empty:
return []

tokens = (
res[~res.text.isna()]
.groupby(["page_num", "block_num", "par_num", "line_num", "word_num"])
res_without_na_text_rows
.groupby(["page_num", "block_num", "par_num", "line_num", "word_num"], group_keys=False)
.apply(
lambda gp: pd.Series(
[
Expand Down