diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..79e3b1b5455702cd2d86be384f3da8c7e0d69f41 --- /dev/null +++ b/.gitignore @@ -0,0 +1,3 @@ +.ipynb_checkpoints +__pycache__ +.venv diff --git a/README.md b/README.md index edb9737c28d5045adffff651756cb17911798ec1..78ac1cc0e5e951966b5596d77c436393e7f45b49 100644 --- a/README.md +++ b/README.md @@ -1,92 +1,34 @@ # Anno Event 2023 +In diesem Repo sammeln wir Ressourcen für den Programmpunkt „Vom Bild zum Text – automatische Texterkennung mit Hilfe von OCR“ beim Event **20 Jahre ANNO – Österreichs größtes Webportal von historischen Zeitungen** am 19. Oktober 2023. +## Inhalt -## Getting started +- Arbeitsschritte der OCR +- Annolyzer +- Preprocessing pipeline für Esperanto-Bestände +- Verwendung von Tesseract +- Verwendung von Transkribus -To make it easy for you to get started with GitLab, here's a list of recommended next steps. +## Arbeitsschritte der OCR -Already a pro? Just edit this README.md and make it your own. Want to make it easy? [Use the template at the bottom](#editing-this-readme)! +... -## Add your files +## Annolyzer -- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files -- [ ] [Add files using the command line](https://docs.gitlab.com/ee/gitlab-basics/add-file.html#add-a-file-using-the-command-line) or push an existing Git repository with the following command: +Die Annolyzer-Plattform ist ein Werkzeug, welches entwickelt wurde um vereinfachten Zugriff auf historische Zeitschriften für eine große Palette von Benutzern zur Verfügung zu stellen. Es handelt sich dabei um eine Weiterentwicklung aus dem NewsEye Projekt, welches nach Projektende in die ÖNB Labs integriert wurde. Siehe den [entsprechenden Beitrag](https://labs.onb.ac.at/de/topic/annolyzer/) auf der Webseite der ÖNB Labs zum Thema. Beim Event stellen wir den Verwendungszweck der Plattform und ihre Funktionen vor: +- Korpus bestehend aus vier österreichischen Zeitschriften aus dem 19. und 20. Jahrhundert +- solr-basierte Volltext-Suche, Filter und Viewer +- Erstellen von eigenen Datensets und Download -``` -cd existing_repo -git remote add origin http://labs.onb.ac.at/gitlab/labs-team/anno-event-2023.git -git branch -M main -git push -uf origin main -``` +## Preprocessing pipeline für Esperanto-Bestände -## Integrate with your tools +Für zwei Projekte, die sich mit Beständen der Sammlung für Plansprachen befassen, kommt eine speziell dafür entwickelte Bildverarbeitungs-Pipeline zum Einsatz. Diese ist zugeschnitten auf das historische Bildmaterial und beseitigt Scanränder, rotiert Bilder waagerecht und wandelt das Bild in Graustufen um. Siehe das Jupyter-Notebook [preprocessing-showcase.ipynb](preprocessing-showcase.ipynb) für mehr Details. -- [ ] [Set up project integrations](http://labs.onb.ac.at/gitlab/labs-team/anno-event-2023/-/settings/integrations) +## Verwendung von Tesseract -## Collaborate with your team +Dies ist eine freie Software für die Texterkennung mit vielen Einstellungen wie etwa unterschiedliche Sprachen und Layoutanalyse. -- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/) -- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html) -- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically) -- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/) -- [ ] [Set auto-merge](https://docs.gitlab.com/ee/user/project/merge_requests/merge_when_pipeline_succeeds.html) +## Verwendung von Transkribus -## Test and Deploy - -Use the built-in continuous integration in GitLab. - -- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/index.html) -- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing(SAST)](https://docs.gitlab.com/ee/user/application_security/sast/) -- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html) -- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/) -- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html) - -*** - -# Editing this README - -When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thank you to [makeareadme.com](https://www.makeareadme.com/) for this template. - -## Suggestions for a good README -Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information. - -## Name -Choose a self-explaining name for your project. - -## Description -Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors. - -## Badges -On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge. - -## Visuals -Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method. - -## Installation -Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection. - -## Usage -Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README. - -## Support -Tell people where they can go to for help. It can be any combination of an issue tracker, a chat room, an email address, etc. - -## Roadmap -If you have ideas for releases in the future, it is a good idea to list them in the README. - -## Contributing -State if you are open to contributions and what your requirements are for accepting them. - -For people who want to make changes to your project, it's helpful to have some documentation on how to get started. Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps explicit. These instructions could also be useful to your future self. - -You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser. - -## Authors and acknowledgment -Show your appreciation to those who have contributed to the project. - -## License -For open source projects, say how it is licensed. - -## Project status -If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers. +Transkribus ist ein Softwarepaket, das auf die Erkennung von (historischen) Handschriften spezialisiert ist. Wir demonstrieren die Verwendung dieses Tools im Projekt [Bibliotheca Eugeniana Digital](https://labs.onb.ac.at/bed/). diff --git a/img/Laufon_009.jpg b/img/Laufon_009.jpg new file mode 100644 index 0000000000000000000000000000000000000000..4bebb1226241cabdf306d34ab54fcdefd13bdf12 Binary files /dev/null and b/img/Laufon_009.jpg differ diff --git a/img/Laufon_009_preprocessed.jpg b/img/Laufon_009_preprocessed.jpg new file mode 100644 index 0000000000000000000000000000000000000000..b9aa9ae4234a3e7ef0a81ca6328a3ed8d0419108 Binary files /dev/null and b/img/Laufon_009_preprocessed.jpg differ diff --git a/img/Zeitungsausschnitt.jpg b/img/Zeitungsausschnitt.jpg new file mode 100644 index 0000000000000000000000000000000000000000..00b089c0a303a08bbdd4c79eff17b497a9904a39 Binary files /dev/null and b/img/Zeitungsausschnitt.jpg differ diff --git a/img/Zeitungsausschnitt_preprocessed.jpg b/img/Zeitungsausschnitt_preprocessed.jpg new file mode 100644 index 0000000000000000000000000000000000000000..81d45d80fce743a49a017a7cf001b7931e1e8565 Binary files /dev/null and b/img/Zeitungsausschnitt_preprocessed.jpg differ diff --git a/img/debug_img/Laufon_009_debug.jpg b/img/debug_img/Laufon_009_debug.jpg new file mode 100644 index 0000000000000000000000000000000000000000..3a1fe02d25580e3fc657cb75d653c6d4ca5cdc3c Binary files /dev/null and b/img/debug_img/Laufon_009_debug.jpg differ diff --git a/img/debug_img/Laufon_009_debug_crop.jpg b/img/debug_img/Laufon_009_debug_crop.jpg new file mode 100644 index 0000000000000000000000000000000000000000..3cb05203cb33def78addcaee464954a1697600d6 Binary files /dev/null and b/img/debug_img/Laufon_009_debug_crop.jpg differ diff --git a/img/debug_img/Zeitungsausschnitt_debug.jpg b/img/debug_img/Zeitungsausschnitt_debug.jpg new file mode 100644 index 0000000000000000000000000000000000000000..126f8f77673a5052aae7bdb2d242ed445eeb2b8b Binary files /dev/null and b/img/debug_img/Zeitungsausschnitt_debug.jpg differ diff --git a/img/debug_img/Zeitungsausschnitt_debug_crop.jpg b/img/debug_img/Zeitungsausschnitt_debug_crop.jpg new file mode 100644 index 0000000000000000000000000000000000000000..bf971071fcd51af524c5cadf0b9a87058deca927 Binary files /dev/null and b/img/debug_img/Zeitungsausschnitt_debug_crop.jpg differ diff --git a/output/Laufon_009.hocr b/output/Laufon_009.hocr new file mode 100644 index 0000000000000000000000000000000000000000..dc8983eafaee8a14701ded8b99cbd23affd512ab --- /dev/null +++ b/output/Laufon_009.hocr @@ -0,0 +1,370 @@ + + + + + + + + + + +
+
+
+

+ + Al + la + amikoj! + +

+
+
+

+ + La + eldono + de + detala + raporto + pri + la + oficialaj + paroladoj, + + + diskutadoj + kaj + decidoj + de + l’Bulonja + kongreso + estas + certe + + + sperantistoj, + ĉar + ĝi + mon- + + + amenon + de + nia + lingvo. + +

+
+
+
+

+ + la + plej + valora + memoraĵo + por + ĉiuj + +

+
+
+
+

+ + tras + la + gloran + venkon, + la + sukcesan + e + +

+
+
+

+ + | + La + verkisto + uzis + la + alfaron + de + l'sistemo + Stolze-Sehrey + + + al + la + helpa + lingvo + por + fiksi + la + parolojn + de + l’reprezentantoj + + + aj + popoloj, + konvenintaj + al + la + kongreso, + kaj + + + stenografiaj + notoj + por + + + oj + de + la + tuta + landaro + +

+
+
+
+
+
+

+ + de + la + plej + div + + + prezentas + nun + la + tradukon + de + si + + + provi + al + la + publiko, + ke + la + esperantis + + + facile + interkompreniĝis + kaj + diskutadis + per + la + lingvo + Es- + +

+
+
+
+
+

+ + ato + +

+
+
+
+
+

+ + Legante + la + raporton + la + kongresanoj + duafoje + travivos + + + la + impresplenajn + horojn + de + Bulonjo-sur-Maro, + kaj + la + nekon- + + + gresanoj + ricevos + la + plej + klaran + bildon + de + la + gravaj + mo- + + + uj + la + „nova + sento“ + vere + ekformiĝis + en + la + +

+
+
+
+
+

+ + mentoj + en + | + +

+
+
+
+

+ + mondo + + + Donacante + la + verketon + al + la + tutmonda + +

+ +

+ + la + aŭtoro + diras + koran + dankon + al + ĉiuj + amikoj, + kiuj + per + sendo + + + de + resumoj + + de + bonaj + konsiloj + faciligis + la + plenumon + de + + + l’entreprenita + tasko, + kaj + li + esperas, + ke + la + laboro + farita + + + oj + de + la + neforgesebla + kongreso, + ne + +

+
+
+

+ + mideanaro, + +

+
+
+
+
+
+
+

+ + inter + la + plej + vi + + + estu + senutila + por + + + lingvo + +

+
+
+
+

+ + ama + progresado + de + nia + mirinda + +

+
+
+
+

+ + Laŭfon + (Svisujo), + en + la + Kristnaska + tempo + 1905. + +

+
+
+

+ + Fr, + Schneeberger. + +

+
+
+ + diff --git a/output/Laufon_009.txt b/output/Laufon_009.txt new file mode 100644 index 0000000000000000000000000000000000000000..98df99c2845aad61a55323619eb1074b28dccb22 --- /dev/null +++ b/output/Laufon_009.txt @@ -0,0 +1,50 @@ +Al la amikoj! + +La eldono de detala raporto pri la oficialaj paroladoj, +diskutadoj kaj decidoj de l’Bulonja kongreso estas certe +sperantistoj, ĉar ĝi mon- +amenon de nia lingvo. + +la plej valora memoraĵo por ĉiuj + +tras la gloran venkon, la sukcesan e + +| La verkisto uzis la alfaron de l'sistemo Stolze-Sehrey +al la helpa lingvo por fiksi la parolojn de l’reprezentantoj +aj popoloj, konvenintaj al la kongreso, kaj +stenografiaj notoj por +oj de la tuta landaro + +de la plej div +prezentas nun la tradukon de si +provi al la publiko, ke la esperantis +facile interkompreniĝis kaj diskutadis per la lingvo Es- + +ato + +Legante la raporton la kongresanoj duafoje travivos +la impresplenajn horojn de Bulonjo-sur-Maro, kaj la nekon- +gresanoj ricevos la plej klaran bildon de la gravaj mo- +uj la „nova sento“ vere ekformiĝis en la + +mentoj en | + +mondo +Donacante la verketon al la tutmonda + +la aŭtoro diras koran dankon al ĉiuj amikoj, kiuj per sendo +de resumoj aŭ de bonaj konsiloj faciligis la plenumon de +l’entreprenita tasko, kaj li esperas, ke la laboro farita +oj de la neforgesebla kongreso, ne + +mideanaro, + +inter la plej vi +estu senutila por +lingvo + +ama progresado de nia mirinda + +Laŭfon (Svisujo), en la Kristnaska tempo 1905. + +Fr, Schneeberger. diff --git a/output/Laufon_009.xml b/output/Laufon_009.xml new file mode 100644 index 0000000000000000000000000000000000000000..6442659442d4ba57f24032760cc4fe02c816b69d --- /dev/null +++ b/output/Laufon_009.xml @@ -0,0 +1,376 @@ + + + + pixel + + img/Laufon_009.jpg + + + + + tesseract 5.3.2 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/output/Laufon_009_preprocessed.hocr b/output/Laufon_009_preprocessed.hocr new file mode 100644 index 0000000000000000000000000000000000000000..e79b7e8beea2d2515e48f2f83d3d88b88d377b49 --- /dev/null +++ b/output/Laufon_009_preprocessed.hocr @@ -0,0 +1,292 @@ + + + + + + + + + + +
+
+

+ + Al + la + amikoj! + +

+
+
+

+ + La + eldono + de + detala + raporto + pri + la + oficialaj + paroladoj, + + + diskutadoj + kaj + decidoj + de + Bulonja + kongreso + estas + certe + + + la + plej + valora + memoraĵo + por + ĉiuj + Esperantistoj, + ĉar + ĝi + mon- + + + tras + la + gloran + venkon, + la + sukcesan + ekzamenon + de + nia + lingvo. + +

+
+
+

+ + La + verkisto + uzis + la + alfaron + de + l'sistemo + Stolze-Schrey + + + al + la + helpa + lingvo + por + fiksi + la + parolojn + de + l'reprezentantoj + + + de + la + plej + diversaj + popoloj, + konvenintaj + al + la + kongreso, + kaj + + + prezentas + nun + la + tradukon + de + siaj + stenografiaj + notoj + por + + + provi + al + la + publiko, + ke + la + esperantistoj + de + la + tuta + landaro + + + facile + interkompreniĝis + kaj + diskutadis + per + la + lingvo + Es- + + + peranto. + +

+ +

+ + Legante + la + raporton + la + kongresanoj + duafoje + travivos + + + la + impresplenajn + horojn + de + Bulonjo-sur-Maro, + kaj + la + nekon- + + + gresanoj + ricevos + la + plej + klaran + bildon + de + la + gravaj + mo- + + + mentoj + en + kiuj + la + „nova + sento“ + vere + ekformiĝis + en + la + + + mondo. + +

+ +

+ + Donacante + la + verketon + al + la + tutmonda + samideanaro, + + + la + aŭtoro + diras + koran + dankon + al + ĉiuj + amikoj, + kiuj + per + sendo + + + de + resumoj + + de + bonaj + konsiloj + faciligis + la + plenumon + de + + + entreprenita + tasko, + kaj + li + esperas, + ke + la + laboro + farita + + + inter + la + plej + vivaj + impresoj + de + la + neforgesebla + kongreso, + ne + + + estu + senutila + por + la + ĉiama + progresado + de + nia + mirinda + + + lingvo. + +

+
+
+

+ + Laŭfon + (Svisujo), + en + la + Kristnaska + tempo + 1905. + +

+
+
+

+ + Fr. + Schneeberger. + +

+
+
+ + diff --git a/output/Laufon_009_preprocessed.txt b/output/Laufon_009_preprocessed.txt new file mode 100644 index 0000000000000000000000000000000000000000..726cc7406e5e4c4b8298df73b8aca6820150d1df --- /dev/null +++ b/output/Laufon_009_preprocessed.txt @@ -0,0 +1,32 @@ +Al la amikoj! + +La eldono de detala raporto pri la oficialaj paroladoj, +diskutadoj kaj decidoj de Bulonja kongreso estas certe +la plej valora memoraĵo por ĉiuj Esperantistoj, ĉar ĝi mon- +tras la gloran venkon, la sukcesan ekzamenon de nia lingvo. + +La verkisto uzis la alfaron de l'sistemo Stolze-Schrey +al la helpa lingvo por fiksi la parolojn de l'reprezentantoj +de la plej diversaj popoloj, konvenintaj al la kongreso, kaj +prezentas nun la tradukon de siaj stenografiaj notoj por +provi al la publiko, ke la esperantistoj de la tuta landaro +facile interkompreniĝis kaj diskutadis per la lingvo Es- +peranto. + +Legante la raporton la kongresanoj duafoje travivos +la impresplenajn horojn de Bulonjo-sur-Maro, kaj la nekon- +gresanoj ricevos la plej klaran bildon de la gravaj mo- +mentoj en kiuj la „nova sento“ vere ekformiĝis en la +mondo. + +Donacante la verketon al la tutmonda samideanaro, +la aŭtoro diras koran dankon al ĉiuj amikoj, kiuj per sendo +de resumoj aŭ de bonaj konsiloj faciligis la plenumon de +entreprenita tasko, kaj li esperas, ke la laboro farita +inter la plej vivaj impresoj de la neforgesebla kongreso, ne +estu senutila por la ĉiama progresado de nia mirinda +lingvo. + +Laŭfon (Svisujo), en la Kristnaska tempo 1905. + +Fr. Schneeberger. diff --git a/output/Laufon_009_preprocessed.xml b/output/Laufon_009_preprocessed.xml new file mode 100644 index 0000000000000000000000000000000000000000..ec574e14655a6ea71b150ce3f7cfffb37b35d4a3 --- /dev/null +++ b/output/Laufon_009_preprocessed.xml @@ -0,0 +1,297 @@ + + + + pixel + + img/Laufon_009_preprocessed.jpg + + + + + tesseract 5.3.2 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/output/Zeitungsausschnitt.hocr b/output/Zeitungsausschnitt.hocr new file mode 100644 index 0000000000000000000000000000000000000000..0e2fd08f8187008e33f06e7ff10ea4053a793267 --- /dev/null +++ b/output/Zeitungsausschnitt.hocr @@ -0,0 +1,82 @@ + + + + + + + + + + +
+
+
+

+ + Grou + +

+
+
+
+

+ + pe + Esperantiste + +

+
+
+

+ + Spera + ntiste + + + ias + +

+
+
+

+ + + depuis + deux + + + CONsiderable + : + ] + + + 8, + ainsi + qu’ + +

+
+
+

+ + avoir + lieu + + + u + mois + d’août + Prochain, + et + + + plusieurs + Membres + +

+
+
+
+ + diff --git a/output/Zeitungsausschnitt.txt b/output/Zeitungsausschnitt.txt new file mode 100644 index 0000000000000000000000000000000000000000..322c95f80c1c00a7ef36d932e882c355c2cc4886 --- /dev/null +++ b/output/Zeitungsausschnitt.txt @@ -0,0 +1,15 @@ +Grou + +pe Esperantiste + +Spera ntiste +ias + +aŭ depuis deux +CONsiderable : ] +8, ainsi qu’ + +avoir lieu +u mois d’août Prochain, et +plusieurs Membres + diff --git a/output/Zeitungsausschnitt.xml b/output/Zeitungsausschnitt.xml new file mode 100644 index 0000000000000000000000000000000000000000..55c28aa9d644e06f4ac205eb6a98c910439385aa --- /dev/null +++ b/output/Zeitungsausschnitt.xml @@ -0,0 +1,89 @@ + + + + pixel + + img/Zeitungsausschnitt.jpg + + + + + tesseract 5.3.2 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/output/Zeitungsausschnitt_preprocessed.hocr b/output/Zeitungsausschnitt_preprocessed.hocr new file mode 100644 index 0000000000000000000000000000000000000000..8d8ecacaaf45aaf8bd575b86e6575b4e6a8e09f6 --- /dev/null +++ b/output/Zeitungsausschnitt_preprocessed.hocr @@ -0,0 +1,306 @@ + + + + + + + + + + +
+
+

+ + » + : + od + mando + dean + cet + + + à + Groupe + Espérantiste + +

+
+
+

+ + Le + Groupe + espérantiste + qui + s’est + fondé + +

+ +

+ + en, + l'an + dernier + et + dont + les + réunions + ont + + + été + suivies + avec + tant + d’intérêt, + recommence + + + ses + cours + à + partir + de + lundi + prochain, + 15 + octo- + + + bre, + à + 8 + h. + 112 + du + soir, + au + Pavilllon + des + So- + + + ciétés + savantes, + 2, + rue + Daniei + Huet. + +

+ +

+ + A + ce + propos, + nous + croyons + devoir + rappeler + + + que + les + congrès + de + Boulogne + et + de + Genève + + + avant + fait + éclater + publiquement + la + facilité + + + surprenante + de + la + langue + et + son + unité + de + pro- + + + nonciation, + l’Esperanto + a + fait + depuis + deux + + + ans + un + progrès + considerable: + introduction + + + dans + le + commerce, + ainsi + qu’en + témoignent, + + + Circulaires + et + prospectus, + dont + quelques + +

+ +

+ + érhippées + ont + circulé + à + Caen, + dépôt + à + la + +

+ +

+ + Chambre + des + Députés + d'un + projet + de + loi + ter- + +

+ +

+ + dant + à + l’enseignement + de + l’espéranto + dans + les + + + écoles, + institutions + d'agences + commerciales, + +

+ +

+ + dans + les + centres + de + relations + internationales, + + + fondation + de + Sociétés + industrielle, + etc + +

+ +

+ + = + Le + + congrès + d'Esperanto + devant + avoir + lieu + + + ~en + Angleterre, + au + mois + d'aoŭt + prochain, + et + + + devant + être + pour + plusieurs + membres + du + + + . + Groupe + une + occasion + merveilteuse + d'utiliser + + + | + la + langue, + les + cours + seront + surtout + dirigés + en + + + vue + de + la + conversation. + +

+ +

+ + Ŝ + Les + adhésions + au + groupe + seront + reçues + à + + + louverture + de + la + première + réunion. + +

+
+
+
+ + diff --git a/output/Zeitungsausschnitt_preprocessed.txt b/output/Zeitungsausschnitt_preprocessed.txt new file mode 100644 index 0000000000000000000000000000000000000000..41dceffdf5b131729a180cf7de964858e1dd41ab --- /dev/null +++ b/output/Zeitungsausschnitt_preprocessed.txt @@ -0,0 +1,40 @@ +» : od mando dean cet +à Groupe Espérantiste + +Le Groupe espérantiste qui s’est fondé + +en, l'an dernier et dont les réunions ont +été suivies avec tant d’intérêt, recommence +ses cours à partir de lundi prochain, 15 octo- +bre, à 8 h. 112 du soir, au Pavilllon des So- +ciétés savantes, 2, rue Daniei Huet. + +A ce propos, nous croyons devoir rappeler +que les congrès de Boulogne et de Genève +avant fait éclater publiquement la facilité +surprenante de la langue et son unité de pro- +nonciation, l’Esperanto a fait depuis deux +ans un progrès considerable: introduction +dans le commerce, ainsi qu’en témoignent, +Circulaires et prospectus, dont quelques + +érhippées ont circulé à Caen, dépôt à la + +Chambre des Députés d'un projet de loi ter- + +dant à l’enseignement de l’espéranto dans les +écoles, institutions d'agences commerciales, + +dans les centres de relations internationales, +fondation de Sociétés industrielle, etc + += Le 3° congrès d'Esperanto devant avoir lieu +~en Angleterre, au mois d'aoŭt prochain, et +devant être pour plusieurs membres du +. Groupe une occasion merveilteuse d'utiliser +| la langue, les cours seront surtout dirigés en +vue de la conversation. + +Ŝ Les adhésions au groupe seront reçues à + louverture de la première réunion. + diff --git a/output/Zeitungsausschnitt_preprocessed.xml b/output/Zeitungsausschnitt_preprocessed.xml new file mode 100644 index 0000000000000000000000000000000000000000..488d2c17a9a903bde1ef4f7e235d22585101fd2e --- /dev/null +++ b/output/Zeitungsausschnitt_preprocessed.xml @@ -0,0 +1,305 @@ + + + + pixel + + img/Zeitungsausschnitt_preprocessed.jpg + + + + + tesseract 5.3.2 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/preprocessing-showcase.ipynb b/preprocessing-showcase.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..482655212e433b6d95a411ad955eb1842c29fc6e --- /dev/null +++ b/preprocessing-showcase.ipynb @@ -0,0 +1,326 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "e37d37b4-6c3a-4b97-a590-0914c914d128", + "metadata": {}, + "outputs": [], + "source": [ + "from preprocessing import *\n", + "from pathlib import Path\n", + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "7119fb20-e86d-409f-a1a5-535266b95082", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
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img/Laufon_009.jpg
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img/Laufon_009_preprocessed.jpg
\n", + "
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img/Zeitungsausschnitt.jpg
\n", + "
\n", + " \n", + "
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img/Zeitungsausschnitt_preprocessed.jpg
\n", + "
\n", + " \n", + "
\n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "paths = sorted(Path('img').glob('*.jpg'))\n", + "gallery(paths, row_height='600px')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "cafe3bae-b78c-4a62-be12-d3811ca0f7f0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "#!/bin/bash\n", + "\n", + "for f in img/*.jpg\n", + "do\n", + " out_path=${f/img/output}\n", + " out_file=${out_path/.jpg/}\n", + " echo \"Run tesseract on $f with output at $out_file\"\n", + " tesseract -l epo+fra --psm 4 $f $out_file alto hocr txt\n", + "done\n", + "Run tesseract on img/Laufon_009.jpg with output at output/Laufon_009\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Detected 91 diacritics\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Run tesseract on img/Laufon_009_preprocessed.jpg with output at output/Laufon_009_preprocessed\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Estimating resolution as 190\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Run tesseract on img/Zeitungsausschnitt.jpg with output at output/Zeitungsausschnitt\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Estimating resolution as 404\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Run tesseract on img/Zeitungsausschnitt_preprocessed.jpg with output at output/Zeitungsausschnitt_preprocessed\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Estimating resolution as 441\n" + ] + } + ], + "source": [ + "%%sh\n", + "cat run_tesseract.sh\n", + "./run_tesseract.sh" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "68df8008-6fe3-4497-a4bf-3b16198e01a7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
output/Laufon_009.txtoutput/Laufon_009_preprocessed.txtoutput/Zeitungsausschnitt.txtoutput/Zeitungsausschnitt_preprocessed.txt
0Al la amikoj!

La eldono de detala raporto pri la oficialaj paroladoj,
diskutadoj kaj decidoj de l’Bulonja kongreso estas certe
sperantistoj, ĉar ĝi mon-
amenon de nia lingvo.

la plej valora memoraĵo por ĉiuj

tras la gloran venkon, la sukcesan e

| La verkisto uzis la alfaron de l'sistemo Stolze-Sehrey
al la helpa lingvo por fiksi la parolojn de l’reprezentantoj
aj popoloj, konvenintaj al la kongreso, kaj
stenografiaj notoj por
oj de la tuta landaro

de la plej div
prezentas nun la tradukon de si
provi al la publiko, ke la esperantis
facile interkompreniĝis kaj diskutadis per la lingvo Es-

ato

Legante la raporton la kongresanoj duafoje travivos
la impresplenajn horojn de Bulonjo-sur-Maro, kaj la nekon-
gresanoj ricevos la plej klaran bildon de la gravaj mo-
uj la „nova sento“ vere ekformiĝis en la

mentoj en |

mondo
Donacante la verketon al la tutmonda

la aŭtoro diras koran dankon al ĉiuj amikoj, kiuj per sendo
de resumoj aŭ de bonaj konsiloj faciligis la plenumon de
l’entreprenita tasko, kaj li esperas, ke la laboro farita
oj de la neforgesebla kongreso, ne

mideanaro,

inter la plej vi
estu senutila por
lingvo

ama progresado de nia mirinda

Laŭfon (Svisujo), en la Kristnaska tempo 1905.

Fr, Schneeberger.
Al la amikoj!

La eldono de detala raporto pri la oficialaj paroladoj,
diskutadoj kaj decidoj de Bulonja kongreso estas certe
la plej valora memoraĵo por ĉiuj Esperantistoj, ĉar ĝi mon-
tras la gloran venkon, la sukcesan ekzamenon de nia lingvo.

La verkisto uzis la alfaron de l'sistemo Stolze-Schrey
al la helpa lingvo por fiksi la parolojn de l'reprezentantoj
de la plej diversaj popoloj, konvenintaj al la kongreso, kaj
prezentas nun la tradukon de siaj stenografiaj notoj por
provi al la publiko, ke la esperantistoj de la tuta landaro
facile interkompreniĝis kaj diskutadis per la lingvo Es-
peranto.

Legante la raporton la kongresanoj duafoje travivos
la impresplenajn horojn de Bulonjo-sur-Maro, kaj la nekon-
gresanoj ricevos la plej klaran bildon de la gravaj mo-
mentoj en kiuj la „nova sento“ vere ekformiĝis en la
mondo.

Donacante la verketon al la tutmonda samideanaro,
la aŭtoro diras koran dankon al ĉiuj amikoj, kiuj per sendo
de resumoj aŭ de bonaj konsiloj faciligis la plenumon de
entreprenita tasko, kaj li esperas, ke la laboro farita
inter la plej vivaj impresoj de la neforgesebla kongreso, ne
estu senutila por la ĉiama progresado de nia mirinda
lingvo.

Laŭfon (Svisujo), en la Kristnaska tempo 1905.

Fr. Schneeberger.
Grou

pe Esperantiste

Spera ntiste
ias

aŭ depuis deux
CONsiderable : ]
8, ainsi qu’

avoir lieu
u mois d’août Prochain, et
plusieurs Membres

» : od mando dean cet
à Groupe Espérantiste

Le Groupe espérantiste qui s’est fondé

en, l'an dernier et dont les réunions ont
été suivies avec tant d’intérêt, recommence
ses cours à partir de lundi prochain, 15 octo-
bre, à 8 h. 112 du soir, au Pavilllon des So-
ciétés savantes, 2, rue Daniei Huet.

A ce propos, nous croyons devoir rappeler
que les congrès de Boulogne et de Genève
avant fait éclater publiquement la facilité
surprenante de la langue et son unité de pro-
nonciation, l’Esperanto a fait depuis deux
ans un progrès considerable: introduction
dans le commerce, ainsi qu’en témoignent,
Circulaires et prospectus, dont quelques

érhippées ont circulé à Caen, dépôt à la

Chambre des Députés d'un projet de loi ter-

dant à l’enseignement de l’espéranto dans les
écoles, institutions d'agences commerciales,

dans les centres de relations internationales,
fondation de Sociétés industrielle, etc

= Le 3° congrès d'Esperanto devant avoir lieu
~en Angleterre, au mois d'aoŭt prochain, et
devant être pour plusieurs membres du
. Groupe une occasion merveilteuse d'utiliser
| la langue, les cours seront surtout dirigés en
vue de la conversation.

Ŝ Les adhésions au groupe seront reçues à
louverture de la première réunion.

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "txtpaths = sorted(Path('output').glob('*.txt'))\n", + "txts = [open(txt).read() for txt in txtpaths]\n", + "txt_df = pd.DataFrame([txts], columns=txtpaths)\n", + "pd.set_option(\"display.max_colwidth\", None)\n", + "display(HTML(txt_df.to_html().replace(\"\\\\n\",\"
\")))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "e094a868-4c3e-4658-9f9c-a381259d0849", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Weighted average angle is -0.53 degrees\n" + ] + }, + { + "data": { + "image/png": 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3qsrnb/bS2oET5frfb32hj3cd0Z9vHKPEeL76gHDBTwNEpX98WtCq20p9fqN3txU2OU7F4ZIKfVHgDSqE1CmprNHGfSeCnzFKbdx3XLcuXq/KGl+L29J8/fjoyyO6468bGWcECCMEEUQdv9+0aiC2Oj6/UUlFTaOveduwXEkqKmvb/NGiotqnHz2zQX6/CaoLeb+RPt51VE999FXoigMQFIIIoo7j1D7awtXEAuJj2nZZxd2J+xRpT29tOagTZdWtGsfGSFq0cg9nRYAwwbceoo7jOOrVzd3q+d2xLiUlNN7GIDXZrYS41u9WA1K6tnreaLJ45R615SaYoyer9MH2w+1XEIBWI4ggKs0am9mqA1mMy9HVY/o2eStoQlyMZo7JDHp8FZcjnZ3dQ4NSugVfVJTZfeSkthZ42zSqb4wj/ffG/e1XFIBWI4ggKt0wvl+rGpT6/EY3TWi+6/Gbc7KDbgjrN9ItE/sHX1AUKiwOrFO55viMtL+orB2qAdBWBBFEpcweiZo5pm9QZ0VcjnTh0BQNz/A0O92w9GTdem7/gJcb40jnndZbl45ID7yYKFZR3T6DEZZXtf+ghgCCx830iFq/vXqk8k+Ua93e4y2eHXE50rA+yXr8hjEBLfvfLztD5VU+vbg+v35cme+qy0DjBvTSkzePpaOtACUltM+IvOEwsm9FtU9vbzmoVzbma/+JcsW6HI3o69FNE7I1fkBPurlHVCCIIGq5Y2P07G3j9ODr2/T3jfmSTg0MMY4jvzGaMjxdj80apa7uwHaZGJej+VeP1ISBvfSXj7/S1gKvXE7t3TbG1HZgltmji2ZP7K9bcvp36hF429uQtG6KdTn1oyS3RozL0WjLI6+uzD2qnz6/ScXl1Q3Cav6Jcr215aCGZyTr6dnnKN0T+ECLQCRirBlA0sHicr2wNk9/37hfR07Wds/eIzFeV43uqxvG91N2r7bdzbJlf5HWfnVcJRXVSnTHakSGRxMH9WL8k1a696VP9cZnreuUrs6Sn1+gwWlJ7VhV4FbmHtUtC9fJb0yTZ+NiXI5Sk9z6x13nKSWp9Xd5ATYEc/wmiACIOJvzTuiqP69q1bwuRxqb3UOv3DGxnasKTFWNXxPmL1VRWVWLd/7EuBxdfmYf/ed1o1v9fn6/UWWNXwlxLi71oMMw6B2ATu2srO763pAUfbzrSKtu4/3594e0f1EBendboY6XVgU0rc9v9PaWg3rw8jPUO4i+bwqKyvXCujy9uD5fR09Wypjay4z9eiXq5gnZmjk2MyzayAASZ0SAiFVR7dM7Ww/qpfX5yjtWJp/fqFc3t64YlaFrzs5sU6dtkeBkZY1mLVilnYdKAgojjmp7VX346pG6bly/UJfXpNkL1wUVoBxHmnf5GZpz7oAWpy0srtCDb2zVB9sPydGpbZ7qzofEx7o06+xM/dulZ6hLfHC9AVfW+PTO54VatvOwjpdWyeU46tUtXlOGp+viYak0uoYkzogAnd7f1ubp4Xe2y1tR06Ch46GSSm0v9Oo/3t+pa8/J0kNXnCF3bOcczbebO1Yv35GjO57bqJW5x5odTdnl1F7m+P01Z+mKURkdXGlDB4rKgzqLE+tyVOitbHG6XYdKdMNf1up4aZWMqQ1d31X3XGWNX39bm6fP8ov17A/HqUfX+BaX762o1oLlu/W3tXmnNLCNcTl6ddMBpSS5NTsnWz86f2CnHkUa7Suqg0hpVantEhCkPUdP6uX1+dqQd0KlFTXqmhCrc7J76Jpz+ql/GxuURoo/frhLC5bvrv/7lIOaqe2w6/l1X2pH4RH9v1vO7rQHBZdLeurmEVq755ieX5unD3ccPuX/I6VbvG6ckK2rx2QqpZvb+n7vuCrkV+CdsvmMI6PyZusu9Jbrmv+3SkVlNfIFeJLbb6StByt186KP9Myt45r9jBwsLtdtz6zXvmNl9f+/3/5/9n89bM+hkgo9tmSL3tu+TwtuGBtQwIF9XePtfndG3aWZsqoavfFpgT7LL9IjW0e1yzIBAIhUZl77xwAuzTRh16ESXf9fa3T0ZFXtWCCd+xI6AABhL2qCiN9vdPuzG3SitFpSbWv0rPK/17/+2xkjdPWYTFvlWVVUVqXjZVVKS0oIuMOujlJR7dP0P32iA8UVAfUZEeNylNU9Qa/NPa/TXY74OPeIfvzsxqDni3E5mpOTrV9OGRaCqtAacxau04a8EwF9pu+bOlRzJjbdUPXR93bomVX7Ar4k0+RyfnCmLj+zYfuZwycrdOGjy1s9wGA3d6w++tcLg24Qi+gSXkedEFqz55j2Hms4yJVLtT0WOo704rrDunnCUBulWVNQVK55/9impdsPyW9qh7e/5uwsPXDpMCXGh8dH453P92v/CSPJHdDASMYv5R03+uhLr64a3bmC5ftbdynO1SXoTryMX/rHp8c174roaEMTCZ66+VzNenKV9h4tazZAXHN2pn76veFN9v9hjNGrG4/KmMD2j6a4HOmNzcd07dmDGzz/1uaC+u/J1iirlD7cUaxrzs5qQ3Xo7KLmPqt9x5oeadMYae/R6Gq4WlRWpZkLVjVo3FdZ49fza/fp1kXr5W/LGOvtaPHKPUENTCfVfqkuXrk3JPXYVBjgWaHGnCirUhg3B4s6PbvG67W55+q6cVlyf929f6zLqb1kLCktya2HLj9Dj8w8s9lOyMqrffJW1LS5Hr+R8o6f+h356uYDrT4bItX+yHtt04E2VIZoEB4/eztAenLTqd6R1MfTpeOKCQPPr83TIW/FKV8yfiOt3XNcn+Qe1QVDUuwU97X842XaWuANej6/kT7bX6yConJldI+u7YrIkZwQp99eNVL3TRumd7cW6mBRhWJjHA1LT9Kkoan1oaQ5pZXtN4JwWSOjER8pCfzunsYYIx3ytm0Z6PyiJoicP7i3UpPcOnqystGEf+MEex0c2bBk26Emf+nEuhwt3X7IehA5erLlvhOac+xkVacKIumehGb7ymhOz67xdO8dppIT4lp96aJbO7bp6uo+tR1HWwYWrFPl87d5GejcoiaIxMa4tOCmMbr56XWqqPbJb1TfIc/Fp6fppgnZtkvsUC01bGtrw7f2EOtq25XDNs4edmac1VevtuI0d4wj/WAs1+jborzKpze3FGhnYYkqqn3ydInTRcNSNTa7h9WAlxDnUq+u8ToWYJfxTYlxHA3s3e2U55PccaqobtsPgu6J9CWC5kVNEJGksdk9teyXk/S3tXnanHdCyV3idMWoDH3/9LSoGwV10tAUbSsobvSsSI3f6LzT7J4NkaQ+3RPqu+UOluM0fzkuEp13Wm9l9uii/SfKg5rPb6Qbx0fXGb/2UlJRrT98sEsvrstTaZVPsV9/TxhJf16+W4NTu+mui07T9LP6WqnPcRzdOCFbf/pwV5vacviMafQzcv7g3m0a5djl1C4DaE4n+83YsrTkBP38+0P07G3j9acbxmjK8PSoCyGSdPOEbCV3iVPMd37NxbgcnZ6epMmnp1qq7Bu9u7k1aWhKQNfKvy3G5eiiYamdbqwVl8vRLy8J7s4ulyPNHJuprJ6JIaqq8zpSUqmr/rxKi1fuVenX7Sdq/EY1flN/YM49fFJ3v/ipHn5nh7XGwNePa/vZrtQkty4aduo+f3NOdqtDiFTbRuQGi+P6IDJEXRBBrdTkBL38kxyN6PtNj3eOI108LFXP3z4hbAauumVi/6C/CH1+o9k5/UNTkGUzRvfVzycHNnKs40gTBvbSb68aEeKqOp/KGp/mLFqnPUdLm71MWffKkyt26+lP9nRMcd/Rx9NFU0ekn/KjIlCOpFvPHdDoPn9WVncNS08K+s41qfYHwaShKYRgtCiqLs1Eqqoav97/olDr9hxXQlyMpo5I1+is7m2+Nj0kLUlv3HWedh85qSMllcrulRh2dw99b3CKzh/cWytzjwZ06tnlSBcMSdF5p3Xe08F3Tx6stGS3Hnl3h06UNRx8TKoNILEuRzeM66d/u+wMxceGR6iMJG9+dlDbgrxj67H3d+q6cf3atQFpoP7PVSO17YBX+4vKgwrudfvL7ec33mGa4zj69ZXDdcNf1tae3giQ49T2S3T/tNMDngfRK+rGmok0B4rKdeN/rdHeY2X116dr/EaXjeyjP1x3luLC5MxFKJ2srNGti9Zp474TzYYRx5HG9e+phXPOCbseYkOhqsav97YV6qX1+co7XqYan1+9u7l1xagM/WBsJgOOtcHlf/xYXxz0BtXuwpH0v2aM0M2WGr4fKCrXTX9Zq7xjzXeSVsdRbfuNBTeNbXF/eWtLgf7lhc2SGhlk8TtiHEexMY4WzTlHEzvxDwI0L5jjN0EkzE3/0yfaWuA95VeOI+nn3x+if7l4cOMzdjKVNT49sWy3/rp6r06UVdeHMqk2mPVMjNctE7P100mncQYAbfLVkZO66D9WBD2fI2lkpkf/uOu89i8qQMXl1frduzv09437VVVTe9vst7856s6e9UiM063nDtBPJw0K+DLsqtyj+sUrn+lgcUWjt5HXPTcopav+87rRGtHX016rhQhEEOkkPt9frCv+9EmTr/dIjNOGf/9+0I05I1ndWYDNeUUqraxRV3esxmR315Th6VFxdgihtyr3aO2liFZISXJr/b9NbueKguetqNbrmw/opfX5KigqV0W1X4nxMTottZtumpCtKcPTWxXY/X6jFbuO6NlVe7X8yyP1V2tiXI6mDk/XLTnZGjegJ33WgNF3O4tdh0uaff1EWbWKy6vVM4pOwcfHunTFqAxdMSqj5YmBKJWcEKdbcvrrlnZutO1yObpwaKouHJoqv9+opKJGjkvqFh8blXcfon0QRMJYS7efxsU4jfaGCKD10j2t63+mdqiIztV3TXNcLkeexDjbZaAT4Fx2GJs4qJd6dYtXY2c5Y1yOpp+VIXcsQQRoTwNTumlkX0/Qt6waiVFmgVYgiISxuBiX/u81ZzUYlVOqbXCWluzW/5gyzGJ1QOc1Z2L/oHsq7RIXoxmj7fSwCkQygkg78vuN1u89rne3Fiq/kSG1W+OCISl662fna+aYvsrs0UWnpXTTv1w8WG//7HyldrIuzIFwcfmoPhrRNzmohuD/OmWolT5EgEjHXTPtZMv+Is19fpPyvx4HxJF06cg+emzWKHWJ5/IJEGmOnqzUDf+1RrmHTzZ5dsRxavv5+umkQfrXKUO5WwT4GnfNdLDjpVW64b/Wqqyqpv45I+mdrQcVH+vS/732LGu1Aa1VVlWjHYUl8pZXKyEuRv16Jiqje3j1vBtKvbu59d93TtTjH+bqhbV5KqmsUVyMI2Nq92+f32hoWpLmXngad3EBbcAZkXbw1IrdevjdHY32gOxypDUPXMxlFESM3MMlem5Nnl7akK/yrwd7q3P+4N6andNfFw5Ljar+ayqqffrn5we1o7BEFdU+ebrE6aJhqTqrHYZaADojzoh0sB2FJXJJ8jXymt9Iuw6fJIgg7Blj9Nj7O/XEst2N9pwpSat2H9PHu45qRN9kLZozTilJnWuE46YkxMXo6jGZtssAOiWCSDtITXJ/c7G4qdejzGf5Rfrj0l36aNcRuRxHl5yRprsnD9ZpqUm2S0MjjDH61T+26ZnV+ySpyYHT6p7ffrBEMxes0utzz42qDvUAtD/ummkHPxibKX8jX9wxLkdn9vVocFp0HXzXfnVMP3hylZZ/eUTVPqPKGr/+ubVQV/5ppXYWNt9bLOz4+8b99SEkED6/0YGics19flMIqwIQDQgi7WBwWpJ+M2OEHOfrkSe/vnbeu1u8/nj9aMvVdbxfv/mFfH7T4Fe1z29UWe3X797bYbEyNMYYoyeW5SrYlg4+v9Hqr45p64HikNQFIDpwaaad3DQhW+cP7q3XNh/Q8dIqjcjw6IpRGVF36+6BonJ9cdDb6Gs+Y/ThjsOqrPHRI2wYWfPVce091rp+b2Jcjp5bs08PzzyznasCEC0IIu0ou1dX3TN5iO0yrKqsbqzJ7jeMkWp8RvT7FD5e33ygycapLfH5jV7bfED/56qRDHoGoFW4NIN21a9nYpONcx1HOiMjWV1JIWHlYHF5q0JIncoav0oqalqeEAAaQRBBu4qNcTV5VsgY6d4oP2MUjmraEELqVPv97VAJgGjET1O0uxvG91ON36//eP9LFZdXS6q9hfnfLjtdk89Is1wdvqtH13i5HAU9yFsdR5KnC8PBA2gdgghC4pac/rr2nCx9UeBVrMulMzKCG0AMHefiYal6e8vBVs0b43I0cVAvxcVwchVA64Ts2+O3v/2tJk6cqMTERHXv3j1Ub4Mw5o6N0eh+PTQy00MICWOXjuyj5ITW/Sbx+Y1m5/Rv34IARJWQBZGqqirNmjVLd955Z6jeAkA7SIiL0Y0TshVsVnQ5Uh9Pgi4clhqawgBEhZBdmvn1r38tSVq8eHGo3gJAO7n74sFamXtU2wq8Ad1B43KkuBiXnrp5LGe7ALRJWF3YrayslNfrbfAAEHoJcTF69ofjNCrTI0dqtpfVGJejLvExeuaH43RmZvcOqhBAZxVWQWT+/PnyeDz1j6ysLNslAVGje2K8XvjxBP3qyuHK7pUoqTZ0xMV8M2xBYnyMbp6QrXfvvkATBvayWS6ATsIxpokhYxtx//3365FHHml2mu3bt2vYsGH1fy9evFj33HOPioqKWlx+ZWWlKisr6//2er3KyspScXGxkpOTAy0TQBsZY7Tmq+Nav/e4SiqqlRAXo349E3XpyD50SAegRV6vVx6PJ6Djd1DfKL/4xS80Z86cZqcZOHBgMItswO12y+1uvFdOAB3HcRzlDOqlnEGc9QAQWkEFkZSUFKWkpISqFgAAEGVCdo41Ly9Px48fV15ennw+nz799FNJ0mmnnaZu3bqF6m0BAEAECVkQeeihh/TMM8/U/z169GhJ0rJlyzRp0qRQvS0AAIggQTVW7WjBNHYBAADhIZjjd1jdvgsAAKILQQQAAFhDEAEAANYQRAAAgDUEEQAAYA1BBAAAWEMQAQAA1hBEAACANQQRAABgDUEEAABYQxABAADWEEQAAIA1BBEAAGANQQQAAFhDEAEAANYQRAAAgDUEEQAAYA1BBAAAWEMQAQAA1hBEAACANQQRAABgDUEEAABYQxABAADWEEQAAIA1BBEAAGANQQQAAFhDEAEAANYQRAAAgDUEEQAAYA1BBAAAWEMQAQAA1hBEAACANQQRAABgDUEEAABYQxABAADWEEQAAIA1BBEAAGANQQQAAFhDEAEAANYQRAAAgDUEEQAAYA1BBAAAWEMQAQAA1hBEAACANQQRAABgDUEEAABYQxABAADWEEQAAIA1BBEAAGANQQQAAFhDEAEAANYQRAAAgDUEEQAAYA1BBAAAWEMQAQAA1hBEAACANQQRAABgDUEEAABYQxABAADWEEQAAIA1BBEAAGANQQQAAFhDEAEAANYQRAAAgDUEEQAAYA1BBAAAWBOyILJ3717ddtttGjBggLp06aJBgwZp3rx5qqqqCtVbAgCACBMbqgXv2LFDfr9fTz31lE477TRt3bpVt99+u0pLS/XYY4+F6m0BAEAEcYwxpqPe7NFHH9WCBQv01VdfBTS91+uVx+NRcXGxkpOTQ1wdAABoD8Ecv0N2RqQxxcXF6tmzZ5OvV1ZWqrKysv5vr9fbEWUBAABLOqyxam5urh5//HH95Cc/aXKa+fPny+Px1D+ysrI6qjwAAGBB0EHk/vvvl+M4zT527NjRYJ4DBw5o6tSpmjVrlm6//fYml/3AAw+ouLi4/pGfnx/8GgEAgIgRdBuRI0eO6NixY81OM3DgQMXHx0uSCgoKNGnSJE2YMEGLFy+WyxV49qGNCAAAkSekbURSUlKUkpIS0LQHDhzQhRdeqLFjx2rRokVBhRAAAND5hayx6oEDBzRp0iRlZ2frscce05EjR+pfS09PD9XbAgCACBKyILJkyRLl5uYqNzdXmZmZDV7rwDuGAQBAGAvZtZI5c+bIGNPoAwAAQGKsGQAAYBFBBAAAWEMQAQAA1nRoF+8AAHQ2xWXVuvflT7V2zzENSumm/7xutPr37mq7rIjBGREAANpg3j+2avnOIzpZ6dPWA17d8dxG2yVFFIIIAABtsGV/sXxf3xHqM0Y7D5XI7+cO0UARRAAAaIOz+/eQy6n9d4zL0YgMj1x1T6BFtBEBAKANHrpiuMqrfVq9+5iGpCXp0VmjbJcUUQgiAAC0QTd3rB6/foztMiIWl2YAAIA1BBEAAGANQQQAAFhDEAEAANYQRAAAgDUEEQAAYA1BBAAAWEMQAQAA1hBEAACANQQRAABgDUEEAABYQxABAADWhPWgd8YYSZLX67VcCQAACFTdcbvuON6csA4iJSUlkqSsrCzLlQAAgGCVlJTI4/E0O41jAokrlvj9fhUUFCgpKUmO47Trsr1er7KyspSfn6/k5OR2XXY4YP0iX2dfx86+flLnX0fWL/KFah2NMSopKVFGRoZcruZbgYT1GRGXy6XMzMyQvkdycnKn/YBJrF9n0NnXsbOvn9T515H1i3yhWMeWzoTUobEqAACwhiACAACsidog4na7NW/ePLndbtulhATrF/k6+zp29vWTOv86sn6RLxzWMawbqwIAgM4tas+IAAAA+wgiAADAGoIIAACwhiACAACs6dRB5IknnlD//v2VkJCg8ePHa926dc1O/8orr2jYsGFKSEjQyJEj9c9//rODKg3O/Pnzdc455ygpKUmpqamaMWOGdu7c2ew8ixcvluM4DR4JCQkdVHHwfvWrX51S77Bhw5qdJ1K2nyT179//lPVzHEdz585tdPpw334fffSRrrjiCmVkZMhxHL3++usNXjfG6KGHHlKfPn3UpUsXTZ48Wbt27WpxucHuw6HU3DpWV1frvvvu08iRI9W1a1dlZGTolltuUUFBQbPLbM3nPFRa2oZz5sw5pdapU6e2uNxI2YaSGt0nHcfRo48+2uQyw2UbBnJcqKio0Ny5c9WrVy9169ZNM2fO1KFDh5pdbmv33WB02iDy0ksv6d5779W8efO0adMmjRo1SlOmTNHhw4cbnX7VqlW6/vrrddttt2nz5s2aMWOGZsyYoa1bt3Zw5S1bsWKF5s6dqzVr1mjJkiWqrq7WJZdcotLS0mbnS05O1sGDB+sf+/bt66CKW2f48OEN6v3kk0+anDaStp8krV+/vsG6LVmyRJI0a9asJucJ5+1XWlqqUaNG6Yknnmj09d/97nf64x//qCeffFJr165V165dNWXKFFVUVDS5zGD34VBrbh3Lysq0adMmPfjgg9q0aZNeffVV7dy5U1deeWWLyw3mcx5KLW1DSZo6dWqDWl944YVmlxlJ21BSg3U7ePCgFi5cKMdxNHPmzGaXGw7bMJDjws9//nO9+eabeuWVV7RixQoVFBTo6quvbna5rdl3g2Y6qXHjxpm5c+fW/+3z+UxGRoaZP39+o9Nfc8015rLLLmvw3Pjx481PfvKTkNbZHg4fPmwkmRUrVjQ5zaJFi4zH4+m4otpo3rx5ZtSoUQFPH8nbzxhj7r77bjNo0CDj9/sbfT2Stp8k89prr9X/7ff7TXp6unn00UfrnysqKjJut9u88MILTS4n2H24I313HRuzbt06I8ns27evyWmC/Zx3lMbWb/bs2Wb69OlBLSfSt+H06dPNRRdd1Ow04boNv3tcKCoqMnFxceaVV16pn2b79u1Gklm9enWjy2jtvhusTnlGpKqqShs3btTkyZPrn3O5XJo8ebJWr17d6DyrV69uML0kTZkypcnpw0lxcbEkqWfPns1Od/LkSWVnZysrK0vTp0/Xtm3bOqK8Vtu1a5cyMjI0cOBA3XjjjcrLy2ty2kjeflVVVXruuef0wx/+sNnBHSNt+9XZs2ePCgsLG2wfj8ej8ePHN7l9WrMPh5vi4mI5jqPu3bs3O10wn3Pbli9frtTUVA0dOlR33nmnjh071uS0kb4NDx06pLffflu33XZbi9OG4zb87nFh48aNqq6ubrA9hg0bpn79+jW5PVqz77ZGpwwiR48elc/nU1paWoPn09LSVFhY2Og8hYWFQU0fLvx+v+655x6de+65GjFiRJPTDR06VAsXLtQbb7yh5557Tn6/XxMnTtT+/fs7sNrAjR8/XosXL9a7776rBQsWaM+ePTr//PNVUlLS6PSRuv0k6fXXX1dRUZHmzJnT5DSRtv2+rW4bBLN9WrMPh5OKigrdd999uv7665sdSCzYz7lNU6dO1bPPPqulS5fqkUce0YoVKzRt2jT5fL5Gp4/0bfjMM88oKSmpxUsX4bgNGzsuFBYWKj4+/pRg3NJxsW6aQOdpjbAefRctmzt3rrZu3driNcmcnBzl5OTU/z1x4kSdfvrpeuqpp/Sb3/wm1GUGbdq0afX/PvPMMzV+/HhlZ2fr5ZdfDugXSiR5+umnNW3aNGVkZDQ5TaRtv2hWXV2ta665RsYYLViwoNlpI+lzft1119X/e+TIkTrzzDM1aNAgLV++XBdffLHFykJj4cKFuvHGG1tsFB6O2zDQ40K46JRnRHr37q2YmJhTWgMfOnRI6enpjc6Tnp4e1PTh4K677tJbb72lZcuWKTMzM6h54+LiNHr0aOXm5oaouvbVvXt3DRkypMl6I3H7SdK+ffv0wQcf6Ec/+lFQ80XS9qvbBsFsn9bsw+GgLoTs27dPS5YsCXpY9ZY+5+Fk4MCB6t27d5O1Ruo2lKSPP/5YO3fuDHq/lOxvw6aOC+np6aqqqlJRUVGD6Vs6LtZNE+g8rdEpg0h8fLzGjh2rpUuX1j/n9/u1dOnSBr8qvy0nJ6fB9JK0ZMmSJqe3yRiju+66S6+99po+/PBDDRgwIOhl+Hw+ff755+rTp08IKmx/J0+e1O7du5usN5K237ctWrRIqampuuyyy4KaL5K234ABA5Sent5g+3i9Xq1du7bJ7dOafdi2uhCya9cuffDBB+rVq1fQy2jpcx5O9u/fr2PHjjVZayRuwzpPP/20xo4dq1GjRgU9r61t2NJxYezYsYqLi2uwPXbu3Km8vLwmt0dr9t3WFt8pvfjii8btdpvFixebL774wvz4xz823bt3N4WFhcYYY26++WZz//3310+/cuVKExsbax577DGzfft2M2/ePBMXF2c+//xzW6vQpDvvvNN4PB6zfPlyc/DgwfpHWVlZ/TTfXb9f//rX5r333jO7d+82GzduNNddd51JSEgw27Zts7EKLfrFL35hli9fbvbs2WNWrlxpJk+ebHr37m0OHz5sjIns7VfH5/OZfv36mfvuu++U1yJt+5WUlJjNmzebzZs3G0nm97//vdm8eXP9HSMPP/yw6d69u3njjTfMli1bzPTp082AAQNMeXl5/TIuuugi8/jjj9f/3dI+3NGaW8eqqipz5ZVXmszMTPPpp5822C8rKyvrl/HddWzpcx4u61dSUmJ++ctfmtWrV5s9e/aYDz74wIwZM8YMHjzYVFRUNLl+kbQN6xQXF5vExESzYMGCRpcRrtswkOPCHXfcYfr162c+/PBDs2HDBpOTk2NycnIaLGfo0KHm1Vdfrf87kH23rTptEDHGmMcff9z069fPxMfHm3Hjxpk1a9bUv/a9733PzJ49u8H0L7/8shkyZIiJj483w4cPN2+//XYHVxwYSY0+Fi1aVD/Nd9fvnnvuqf+/SEtLM5deeqnZtGlTxxcfoGuvvdb06dPHxMfHm759+5prr73W5Obm1r8eyduvznvvvWckmZ07d57yWqRtv2XLljX6maxbB7/fbx588EGTlpZm3G63ufjii09Z7+zsbDNv3rwGzzW3D3e05tZxz549Te6Xy5Ytq1/Gd9expc95R2pu/crKyswll1xiUlJSTFxcnMnOzja33377KYEikrdhnaeeesp06dLFFBUVNbqMcN2GgRwXysvLzU9/+lPTo0cPk5iYaK666ipz8ODBU5bz7XkC2Xfbyvn6jQEAADpcp2wjAgAAIgNBBAAAWEMQAQAA1hBEAACANQQRAABgDUEEAABYQxABAADWEEQAAIA1BBEAAGANQQQAAFhDEAEAANYQRAAAgDX/Hxzx4ymi0bWrAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\tBorderRegion: upperleft_point=(40, 61) lowerright_point=(770, 1176) (total image size: (810, 1237))\n", + "\tEliminated 6 contours, 247 surviving (total number contours: 253)\n", + "\tBoundingBox of surviving contours: (141, 210, 601, 734) -> upperleft_point=(141, 210) lowerright_point(742, 944)\n", + "Weighted average angle is 5.88 degrees\n" + ] + }, + { + "data": { + "image/png": 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", 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\n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "debug_imgpaths = sorted(Path('img/debug_img').glob('*.jpg'))\n", + "gallery(debug_imgpaths, row_height='600px')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "40a60755-b6a0-44ff-bbbe-7398f6d9417b", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.0" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/preprocessing.py b/preprocessing.py new file mode 100644 index 0000000000000000000000000000000000000000..a3344e138ec2c4681622ed2653326ad5b5385aff --- /dev/null +++ b/preprocessing.py @@ -0,0 +1,380 @@ +# auth: simon.mayer@onb.ac.at alexander.rabensteiner@onb.ac.at +# date: 2023-2-16 +# desc: Provides functions to preprocess image to enhcance tesseract reults, currently applied: +# - deskew image (code adapted from https://docs.opencv.org/4.7.0/d1/dee/tutorial_introduction_to_pca.html) +# - crop image border regions +# - upscale image + +import os +import cv2 as cv +import numpy as np +import matplotlib.pyplot as plt +from math import atan2, cos, sin, sqrt, pi +# import editdistance +from IPython.display import HTML, Image, display + + +def _src_from_data(data): + """Base64 encodes image bytes for inclusion in an HTML img element""" + img_obj = Image(data=data) + for bundle in img_obj._repr_mimebundle_(): + for mimetype, b64value in bundle.items(): + if mimetype.startswith('image/'): + return f'data:{mimetype};base64,{b64value}' + + +def gallery(images, row_height='auto'): + """Shows a set of images in a gallery that flexes with the width of the notebook. + + Parameters + ---------- + images: list of str or bytes + URLs or bytes of images to display + + row_height: str + CSS height value to assign to all images. Set to 'auto' by default to show images + with their native dimensions. Set to a value like '250px' to make all rows + in the gallery equal height. + """ + figures = [] + for image in images: + if isinstance(image, bytes): + src = _src_from_data(image) + caption = '' + else: + src = image + caption = f'
{image}
' + figures.append(f''' +
+ + {caption} +
+ ''') + return HTML(data=f''' +
+ {''.join(figures)} +
+ ''') + + +def draw_axis(img, p_, q_, colour, scale): + p = list(p_) + q = list(q_) + angle = atan2(p[1] - q[1], p[0] - q[0]) # angle in radians + hypotenuse = sqrt((p[1] - q[1]) * (p[1] - q[1]) + (p[0] - q[0]) * (p[0] - q[0])) + # Here we lengthen the arrow by a factor of scale + q[0] = p[0] - scale * hypotenuse * cos(angle) + q[1] = p[1] - scale * hypotenuse * sin(angle) + cv.line(img, (int(p[0]), int(p[1])), (int(q[0]), int(q[1])), colour, 1, cv.LINE_AA) + # create the arrow hooks + p[0] = q[0] + 9 * cos(angle + pi / 4) + p[1] = q[1] + 9 * sin(angle + pi / 4) + cv.line(img, (int(p[0]), int(p[1])), (int(q[0]), int(q[1])), colour, 1, cv.LINE_AA) + p[0] = q[0] + 9 * cos(angle - pi / 4) + p[1] = q[1] + 9 * sin(angle - pi / 4) + cv.line(img, (int(p[0]), int(p[1])), (int(q[0]), int(q[1])), colour, 1, cv.LINE_AA) + + +def get_orientation(pts, img, debug=False): + sz = len(pts) + data_pts = np.empty((sz, 2), dtype=np.float64) + for i in range(data_pts.shape[0]): + data_pts[i, 0] = pts[i, 0, 0] + data_pts[i, 1] = pts[i, 0, 1] + # Perform PCA + mean = np.empty((0)) + mean, eigenvectors, eigenvalues = cv.PCACompute2(data_pts, mean) + # Store the center of the object + cntr = (int(mean[0, 0]), int(mean[0, 1])) + p1 = (cntr[0] + 0.02 * eigenvectors[0, 0] * eigenvalues[0, 0], + cntr[1] + 0.02 * eigenvectors[0, 1] * eigenvalues[0, 0]) + p2 = (cntr[0] - 0.02 * eigenvectors[1, 0] * eigenvalues[1, 0], + cntr[1] - 0.02 * eigenvectors[1, 1] * eigenvalues[1, 0]) + if debug: + cv.circle(img, cntr, 3, (255, 0, 255), 2) + draw_axis(img, cntr, p1, (0, 255, 0), 1) + draw_axis(img, cntr, p2, (255, 255, 0), 5) + + angle = atan2(eigenvectors[0, 1], eigenvectors[0, 0]) # orientation in radians + ratio = eigenvalues[1, 0] / eigenvalues[0, 0] + return angle, ratio + + +def deskew_image_pca(image, debug=False, debug_path=None): + (orig_h, orig_w) = image.shape[:2] + shrink_factor = 0.85 + (red_h, red_w) = (int(orig_h * shrink_factor), int(orig_w * shrink_factor)) + red_h_beg = (orig_h - red_h) // 2 + red_h_end = red_h_beg + red_h + red_w_beg = (orig_w - red_w) // 2 + red_w_end = red_w_beg + red_w + image_cutout = image[red_h_beg:red_h_end, red_w_beg:red_w_end] + sharp = unsharp_mask(image_cutout, amount=2.0) + gray = cv.cvtColor(sharp, cv.COLOR_BGR2GRAY) + blur = cv.GaussianBlur(gray, (9, 9), 2) + bw = cv.adaptiveThreshold(blur, 255, cv.ADAPTIVE_THRESH_GAUSSIAN_C, cv.THRESH_BINARY, 5, 4) + inverse = cv.bitwise_not(bw) + kernel = cv.getStructuringElement(cv.MORPH_CROSS, (10, 2)) + dilate = cv.dilate(inverse, kernel, iterations=3) + + contours, _ = cv.findContours(dilate, cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE) + contours = sorted(contours, key=cv.contourArea, reverse=True) + angles_ratios = [] + for i, c in enumerate(contours): + # Calculate the area of each contour + area = cv.contourArea(c) + # Ignore contours that are too small or too large + if area < 1e3 or 2e5 < area: + continue + # Draw each contour only for visualisation purposes + if debug: + cv.drawContours(gray, contours, i, (0, 0, 255), 2) + # Find the orientation of each shape + angle, ratio = get_orientation(c, gray, debug) + angles_ratios.append((angle, ratio)) + if len(angles_ratios) > 0: + angles, ratios = zip(*angles_ratios) + norm_ratios = ratios / np.sum(ratios) + # Inverse ratio as weights + weights = [1 / ratio for ratio in norm_ratios] + # Identify angles which are 90 degrees apart + angles_sin = [np.sin(4 * angle) for angle in angles] + # Perform weighted average + angle_sin = np.average(angles_sin, weights=weights) + angle = np.arcsin(angle_sin) / 4 * 180 / pi + if debug: + print(f'Weighted average angle is {round(angle, 2)} degrees') + _, ax = plt.subplots() + angles_deg = [angle * 180 / pi for angle in angles] + ax.scatter(range(len(angles)), angles_deg, s=weights) + ax.hlines(y=angle, xmin=0, xmax=len(angles), color='g') + plt.show() + horizontal_stack = np.concatenate((inverse, dilate, gray), axis=1) + # cv.imshow('Thresholded image, dilated image, principal components drawn', horizontal_stack) + # cv.waitKey() + fp = debug_path.replace('img/', 'img/debug_img/').replace('.jpg', '_debug.jpg') + cv.imwrite(fp, horizontal_stack) + # Return original image if angle is larger than 2 degrees or if no large enough contours are found + if len(angles_ratios) == 0 or abs(angle) > 10.0: + if debug: + print('Angle too large or no contours found, returning original') + return image, 0 + center = (orig_w // 2, orig_h // 2) + rot_mat = cv.getRotationMatrix2D(center, angle, 1.0) + deskewed_image = cv.warpAffine(image, rot_mat, (orig_w, orig_h), flags=cv.INTER_CUBIC, + borderMode=cv.BORDER_REPLICATE) + return deskewed_image, angle + + +def unsharp_mask(image, kernel_size=(5, 5), sigma=1.0, amount=1.0, threshold=0): + """Return a sharpened version of the image, using an unsharp mask.""" + blurred = cv.GaussianBlur(image, kernel_size, sigma) + sharpened = float(amount + 1) * image - float(amount) * blurred + sharpened = np.maximum(sharpened, np.zeros(sharpened.shape)) + sharpened = np.minimum(sharpened, 255 * np.ones(sharpened.shape)) + sharpened = sharpened.round().astype(np.uint8) + if threshold > 0: + low_contrast_mask = np.absolute(image - blurred) < threshold + np.copyto(sharpened, image, where=low_contrast_mask) + return sharpened + + +def analyse_deskew_method(img_filepaths, measured_angles, debug=False): + calc_angles = [] + for image_fp in img_filepaths: + print(f'Preprocessing image file: {image_fp}') + image = cv.imread(image_fp) + deskewed_img, angle = deskew_image_pca(image, debug=debug) + calc_angles.append(angle) + if debug: + cv.imshow('Deskewed image', deskewed_img) + cv.waitKey() + + # Analysis of automatically determined angles + angle_diff = [angle - m_angle for (angle, m_angle) in zip(calc_angles, measured_angles)] + error = np.linalg.norm(angle_diff) + print('L2 distance between the two angle arrays is', error) + _, ax = plt.subplots() + ax.plot(calc_angles, 'o', label='automatic') + ax.plot(measured_angles, 'or', label='measured') + ax.set_xlabel('Images') + ax.set_ylabel('Rotation angle [°]') + ax.hlines(y=0, xmin=0, xmax=len(calc_angles) - 1, color='g') + plt.title('Comparison of automatic and measured rotation angles') + plt.legend() + plt.show() + + +def get_cropping_corner_points(image, threshold_border=0.05, debug=False, debug_path=None): + # Do some preprocessing magic to exract 'good' contours + gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY) + _, bw = cv.threshold(gray, 50, 255, cv.THRESH_BINARY | cv.THRESH_OTSU) + inverse = cv.bitwise_not(bw) + kernel = cv.getStructuringElement(cv.MORPH_CROSS, (3, 3)) + dilate = cv.dilate(inverse, kernel, iterations=5) + contours, _ = cv.findContours(dilate, cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE) + + # Define borderregion + min_y = int(image.shape[0] * threshold_border) + min_x = int(image.shape[1] * threshold_border) + max_y = image.shape[0] - int(image.shape[0] * threshold_border) + max_x = image.shape[1] - int(image.shape[1] * threshold_border) + if debug: + print( + f'\tBorderRegion: upperleft_point={(min_x, min_y)} lowerright_point={(max_x, max_y)} ' + f'(total image size: {image.shape[1], image.shape[0]})') + + # Remove contours with single point in borderregion + contours_surviving = [] + contours_removed = [] # for debug purposes + check_if_point_in_inner_region = lambda x: min_x < x[0][0] < max_x and min_y < x[0][1] < max_y + for contour in contours: + all_contour_points_in_inner_region = all([check_if_point_in_inner_region(p) for p in contour]) + if all_contour_points_in_inner_region: + contours_surviving.append(contour) + else: + contours_removed.append(contour) + if debug: + print( + f'\tEliminated {len(contours_removed)} contours, {len(contours_surviving)} surviving ' + f'(total number contours: {len(contours)})') + + # Get the 4 min/max x/y points of all surviving contours to create a BoundingBox + extract_x_values_from_contour = lambda cntr: [el for i, el in enumerate(cntr.flatten()) if i % 2 == 0] + extract_y_values_from_contour = lambda cntr: [el for i, el in enumerate(cntr.flatten()) if i % 2 == 1] + bb_precursor = np.array([ + [min([min(extract_x_values_from_contour(c)) for c in contours_surviving]), + min([min(extract_y_values_from_contour(c)) for c in contours_surviving])], + [max([max(extract_x_values_from_contour(c)) for c in contours_surviving]), + max([max(extract_y_values_from_contour(c)) for c in contours_surviving])] + ]) + boundingbox_of_surviving_contours = cv.boundingRect(bb_precursor) + bb_p0 = (boundingbox_of_surviving_contours[0], boundingbox_of_surviving_contours[1]) + bb_p1 = (boundingbox_of_surviving_contours[0] + boundingbox_of_surviving_contours[2], + boundingbox_of_surviving_contours[1] + boundingbox_of_surviving_contours[3]) + if debug: + print( + f'\tBoundingBox of surviving contours: {boundingbox_of_surviving_contours} -> upperleft_point={bb_p0} ' + f'lowerright_point{bb_p1}') + + # TODO evtl move following to seperate draw_nice_boxes_in_original_scan function + if debug: + for i, _ in enumerate(contours_removed): + cv.drawContours(image, contours_removed, i, (255, 0, 255), thickness=1) + for i, _ in enumerate(contours_surviving): + cv.drawContours(image, contours_surviving, i, (0, 0, 255), thickness=1) + cv.rectangle(image, bb_p0, bb_p1, (0, 255, 0), thickness=3) # cropping + cv.rectangle(image, (min_x, min_y), (max_x, max_y), (0, 255, 255), thickness=2) # borderregion + # cv.imshow( + # f'Image Cropping border_threshold={threshold_border} (green->Cropping, yellow->BorderRegion, ' + # f'red=ContoursSurviving, violet=ContoursRejected)', + # image) + fp = debug_path.replace('img/', 'img/debug_img/').replace('.jpg', '_debug_crop.jpg') + cv.imwrite(fp, image) + # cv.waitKey() + # cv.destroyAllWindows() + + return bb_p0, bb_p1 + + +def apply_gamma_correction(img, gamma=2.0): + img_gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY) + look_up_table = np.empty((1, 256), np.uint8) + for i in range(256): + look_up_table[0, i] = np.clip(pow(i / 255.0, gamma) * 255.0, 0, 255) + gamma_res = cv.LUT(img_gray, look_up_table) + return gamma_res + + +def crop_bb_from_img(img, bb, margin=20): + h, w = img.shape[:2] + x_a, x_b = max(bb[0][0] - margin, 0), min(bb[1][0] + margin, w) + y_a, y_b = max(bb[0][1] - margin, 0), min(bb[1][1] + margin, h) + img_crop = img[y_a:y_b, x_a:x_b] + return img_crop + + +def upscale_image(img, scaling=2): + return cv.resize(img, (int(img.shape[1]*scaling), int(img.shape[0]*scaling)), cv.INTER_CUBIC) + + +def preprocess_pipeline(image, debug=False, debug_path=None): + img_rot, img_angle = deskew_image_pca(image, debug=debug, debug_path=debug_path) + img_bb = get_cropping_corner_points(img_rot, threshold_border=0.05, debug=debug, debug_path=debug_path) + img_crop = crop_bb_from_img(img_rot, img_bb, margin=15) + # img_upscld = upscale_image(img_crop, scaling=2) + img_res = cv.cvtColor(img_crop, cv.COLOR_BGR2GRAY) + # Following makes things gloablly worse, so I excluded these steps + # img_erode = cv.erode(img_gray, cv.getStructuringElement(cv.MORPH_CROSS, (3, 3)), iterations=1) + # img_blur = cv.GaussianBlur(img_bright_contrast, (3, 3), 2) + # img_sharp = unsharp_mask(img_gray, kernel_size=(3, 3), sigma=1.5, amount=5.0, threshold=50) + # img_denoise = cv.fastNlMeansDenoising(img_sharp, h=3) + return img_res + + +if __name__ == '__main__': + images = [ + '/home/simon/Downloads/Ruthenica_sample/tesseract_output/00000001.jpg', + '/home/simon/Downloads/Ruthenica_sample/tesseract_output/00000003.jpg', + '/home/simon/Downloads/Ruthenica_sample/tesseract_output/00000004.jpg' + ] + + # images = [ + # 'img/test.jpg', + # 'img/Laufon_009.jpg', + # 'img/Laufon_012.jpg', + # 'img/Laufon_013.jpg', + # 'img/Laufon_055.jpg', + # 'img/Laufon_094.jpg', + # 'img/Laufon_110.jpg', + # 'img/Dresden_008.jpg', + # 'img/Dresden_020.jpg', + # 'img/Dresden_037.jpg', + # 'img/Dresden_063.jpg', + # 'img/Dresden_094.jpg', + # 'img/Dresden_132.jpg', + # 'img/00002_1003102D_00000021.jpg', + # 'img/00005_10026184_00000014.jpg', + # 'img/00063_10029F7D_00000022.jpg' + # ] + # measured_angles = [-0.65, 0.1, -1.3, -0.4, 0.85, 1.2, + # -0.1, -0.7, 0.5, -0.4, -0.7, -1.3, + # 0.5, 0.3, -0.7] + # analyse_deskew_method(images, measured_angles, debug=False) + # ground_truth_fps = [ + # 'ground_truths/GT_Laufon_009.txt', + # 'ground_truths/GT_Laufon_012.txt', + # 'ground_truths/GT_Laufon_013.txt', + # 'ground_truths/GT_Laufon_055.txt', + # 'ground_truths/GT_Laufon_094.txt', + # 'ground_truths/GT_Laufon_110.txt', + # 'ground_truths/GT_Dresden_008.txt', + # 'ground_truths/GT_Dresden_020.txt', + # 'ground_truths/GT_Dresden_037.txt', + # 'ground_truths/GT_Dresden_063.txt', + # 'ground_truths/GT_Dresden_094.txt', + # 'ground_truths/GT_Dresden_132.txt', + # 'ground_truths/GT_00002_1003102D_00000021.txt', + # 'ground_truths/GT_00005_10026184_00000014.txt', + # 'ground_truths/GT_00063_10029F7D_00000022.txt' + # ] + + # ground_truths = [open(fp).read() for fp in ground_truth_fps] + # levenshtein_distances = [] + + for img_path in images: + + img_path_preprocessed = f'{img_path.replace(".jpg", "")}_preprocessed.jpg' + ocred_path_base_preprocessed = img_path_preprocessed.replace('.jpg', '') + + print(f'Processing image {img_path}') + input_image = cv.imread(img_path) + preprocessed_img = preprocess_pipeline(input_image, debug=True) + # cv.imshow('Preprocessed image, rotated, cropped and resized', preprocessed_img) + # cv.waitKey() + + cv.imwrite(img_path_preprocessed, preprocessed_img) + os.system(f'tesseract -l ukr --dpi 300 --psm 4 {img_path_preprocessed} {ocred_path_base_preprocessed} txt') + + # print('Levenshtein distances are:', levenshtein_distances) + # print('L2 norm is:', np.linalg.norm(levenshtein_distances)) diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..401ff43bae75da7fde8230b114f74f68d10c1c3d --- /dev/null +++ b/requirements.txt @@ -0,0 +1,5 @@ +jupyter +opencv-python +nodejs +matplotlib +pandas diff --git a/run_tesseract.sh b/run_tesseract.sh new file mode 100755 index 0000000000000000000000000000000000000000..3d5f6d47962f2adb35d5df4624c31afe4ee1f6ee --- /dev/null +++ b/run_tesseract.sh @@ -0,0 +1,9 @@ +#!/bin/bash + +for f in img/*.jpg +do + out_path=${f/img/output} + out_file=${out_path/.jpg/} + echo "Run tesseract on $f with output at $out_file" + tesseract -l epo+fra --psm 4 $f $out_file alto hocr txt +done