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ocr-post-processing-with-google | search engine | Natural Language Processing library

 by   PedroBarcha Python Version: Current License: GPL-3.0

 by   PedroBarcha Python Version: Current License: GPL-3.0

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kandi X-RAY | ocr-post-processing-with-google Summary

ocr-post-processing-with-google is a Python library typically used in Artificial Intelligence, Natural Language Processing applications. ocr-post-processing-with-google has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However ocr-post-processing-with-google build file is not available. You can download it from GitHub.
Given a text, wrap it into phrases and send them to google's search engine. If it yields a "did you mean:", substitute the original phrase for the suggestion. The software was originally developed for correcting OCR output.
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Quality
Quality
Security
Security
License
License
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kandi-support Support

  • ocr-post-processing-with-google has a low active ecosystem.
  • It has 2 star(s) with 0 fork(s). There are 1 watchers for this library.
  • It had no major release in the last 12 months.
  • ocr-post-processing-with-google has no issues reported. There are no pull requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of ocr-post-processing-with-google is current.
This Library - Support
Best in #Natural Language Processing
Average in #Natural Language Processing
This Library - Support
Best in #Natural Language Processing
Average in #Natural Language Processing

quality kandi Quality

  • ocr-post-processing-with-google has no bugs reported.
This Library - Quality
Best in #Natural Language Processing
Average in #Natural Language Processing
This Library - Quality
Best in #Natural Language Processing
Average in #Natural Language Processing

securitySecurity

  • ocr-post-processing-with-google has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
This Library - Security
Best in #Natural Language Processing
Average in #Natural Language Processing
This Library - Security
Best in #Natural Language Processing
Average in #Natural Language Processing

license License

  • ocr-post-processing-with-google is licensed under the GPL-3.0 License. This license is Strong Copyleft.
  • Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.
This Library - License
Best in #Natural Language Processing
Average in #Natural Language Processing
This Library - License
Best in #Natural Language Processing
Average in #Natural Language Processing

buildReuse

  • ocr-post-processing-with-google releases are not available. You will need to build from source code and install.
  • ocr-post-processing-with-google has no build file. You will be need to create the build yourself to build the component from source.
This Library - Reuse
Best in #Natural Language Processing
Average in #Natural Language Processing
This Library - Reuse
Best in #Natural Language Processing
Average in #Natural Language Processing
Top functions reviewed by kandi - BETA

kandi has reviewed ocr-post-processing-with-google and discovered the below as its top functions. This is intended to give you an instant insight into ocr-post-processing-with-google implemented functionality, and help decide if they suit your requirements.

  • Takes a text file and returns a list of pieces
  • Given a list of strings and a list of words return a single query .
  • Spell check .
  • Trim punctuation .
  • Enhance a query .

ocr-post-processing-with-google Key Features

Given a text, wrap it into phrases and send them to google's search engine. If it yields a "did you mean:", substitute the original phrase for the suggestion. The software was originally developed for correcting OCR output.

ocr-post-processing-with-google Examples and Code Snippets

No Code Snippets are available at this moment for ocr-post-processing-with-google.Refer to component home page for details.

No Code Snippets are available at this moment for ocr-post-processing-with-google.Refer to component home page for details.

Community Discussions

Trending Discussions on Natural Language Processing
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Trending Discussions on Natural Language Processing

QUESTION

number of matches for keywords in specified categories

Asked 2022-Apr-14 at 13:32

For a large scale text analysis problem, I have a data frame containing words that fall into different categories, and a data frame containing a column with strings and (empty) counting columns for each category. I now want to take each individual string, check which of the defined words appear, and count them within the appropriate category.

As a simplified example, given the two data frames below, i want to count how many of each animal type appear in the text cell.

df_texts <- tibble(
  text=c("the ape and the fox", "the tortoise and the hare", "the owl and the the 
  grasshopper"),
  mammals=NA,
  reptiles=NA,
  birds=NA,
  insects=NA
)

df_animals <- tibble(animals=c("ape", "fox", "tortoise", "hare", "owl", "grasshopper"),
           type=c("mammal", "mammal", "reptile", "mammal", "bird", "insect"))

So my desired result would be:

df_result <- tibble(
  text=c("the ape and the fox", "the tortoise and the hare", "the owl and the the 
  grasshopper"),
  mammals=c(2,1,0),
  reptiles=c(0,1,0),
  birds=c(0,0,1),
  insects=c(0,0,1)
)

Is there a straightforward way to achieve this keyword-matching-and-counting that would be applicable to a much larger dataset?

Thanks in advance!

ANSWER

Answered 2022-Apr-14 at 13:32

Here's a way do to it in the tidyverse. First look at whether strings in df_texts$text contain animals, then count them and sum by text and type.

library(tidyverse)

cbind(df_texts[, 1], sapply(df_animals$animals, grepl, df_texts$text)) %>% 
  pivot_longer(-text, names_to = "animals") %>% 
  left_join(df_animals) %>% 
  group_by(text, type) %>% 
  summarise(sum = sum(value)) %>% 
  pivot_wider(id_cols = text, names_from = type, values_from = sum)

  text                                   bird insect mammal reptile
  <chr>                                 <int>  <int>  <int>   <int>
1 "the ape and the fox"                     0      0      2       0
2 "the owl and the the \n  grasshopper"     1      0      0       0
3 "the tortoise and the hare"               0      0      1       1

To account for the several occurrences per text:

cbind(df_texts[, 1], t(sapply(df_texts$text, str_count, df_animals$animals, USE.NAMES = F))) %>% 
  setNames(c("text", df_animals$animals)) %>% 
  pivot_longer(-text, names_to = "animals") %>% 
  left_join(df_animals) %>% 
  group_by(text, type) %>% 
  summarise(sum = sum(value)) %>% 
  pivot_wider(id_cols = text, names_from = type, values_from = sum)

Source https://stackoverflow.com/questions/71871613

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install ocr-post-processing-with-google

You can download it from GitHub.
You can use ocr-post-processing-with-google like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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