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Add PLAYA-PDF and update release dates #17

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855b7b8
chore: update requirements to current versions
dhdaines Sep 6, 2023
5e33cfd
fix: remove unsupported argument in pydantic2
dhdaines Sep 6, 2023
1f1596f
fix: use `use_text_flow` for pdfplumber
dhdaines Sep 6, 2023
dc1cb6b
chore: rebuild
dhdaines Sep 6, 2023
0f8b84b
Merge branch 'py-pdf:main' into main
dhdaines Feb 20, 2025
a640d1e
feat: add PLAYA-PDF
dhdaines Feb 20, 2025
4592803
chore: update all versions
dhdaines Feb 20, 2025
ff365e1
fix: nope! postprocess not compatible with playa (yet)
dhdaines Feb 20, 2025
2c2da35
chore: rerun with playa
dhdaines Feb 20, 2025
f624925
fix: use playa main branch with xobject fix
dhdaines Feb 20, 2025
6508f30
feat: use 2 CPUs for PLAYA
dhdaines Feb 20, 2025
6622f6c
fix: correct pdfplumber version
dhdaines Feb 20, 2025
1871f18
feat: update to use new PLAYA extract_text (and improve accuracy)
dhdaines Feb 20, 2025
a4fdbba
fix: update release dates
dhdaines Feb 20, 2025
75e22bd
chore: update for playa 0.3.0
dhdaines Feb 21, 2025
f4bb730
fix: update release dates
dhdaines Feb 21, 2025
3df099c
fix: outpath no longer used
dhdaines Feb 21, 2025
c928275
chore: update to 0.4.1
dhdaines Apr 1, 2025
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fix: use playa main branch with xobject fix
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@dhdaines
dhdaines committed Feb 20, 2025
commit f624925826dbcdaac22f70a08417a6ef17897db2
14 changes: 7 additions & 7 deletions README.md
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152 changes: 76 additions & 76 deletions cache.json
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Original file line number Diff line number Diff line change
Expand Up @@ -206,46 +206,46 @@
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Expand Down Expand Up @@ -292,50 +292,6 @@
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Expand Down Expand Up @@ -523,6 +479,50 @@
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Expand Down Expand Up @@ -607,22 +607,6 @@
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Expand Down Expand Up @@ -670,6 +654,22 @@
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Expand All @@ -694,7 +694,6 @@
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Expand Down Expand Up @@ -727,6 +726,7 @@
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9 changes: 8 additions & 1 deletion read/results/playa/1602.06541.txt
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Expand Up @@ -401,7 +401,14 @@ images were labeled by anonymous untrained workers
to which they refer to as knowledge workers (KWs).
One crowd annotation was obtained for each image by
a majority vote on a pixel basis of 10 segmentations
given by 10 different KWs. Figure 2: A typical segmentation pipeline gets raw
given by 10 different KWs. Training
Prediction
Post-
processingWindow-wise
ClassificationWindow
extraction Data
augmentation
Feature extraction Preprocessing Figure 2: A typical segmentation pipeline gets raw
pixel data, applies preprocessing techniques
like scaling and feature extraction like HOG
features. For training, data augmentation
Expand Down
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