text2image | : fax : A lightweight for convert text to image by canvas | Computer Vision library

by xg4 TypeScript Version: v0.2.0 License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | text2image Summary

text2image is a TypeScript library typically used in Artificial Intelligence, Computer Vision applications. text2image has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

convert text to image by canvas.

Support

Quality

Security

License

Reuse

Support

text2image has a low active ecosystem.

It has 7 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 12 months.

text2image has no issues reported. There are 22 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of text2image is v0.2.0

Quality

text2image has 0 bugs and 0 code smells.

Security

text2image has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

text2image code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

text2image is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

text2image releases are available to install and integrate.

Installation instructions are not available. Examples and code snippets are available.

It has 40 lines of code, 0 functions and 8 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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text2image Key Features

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text2image Examples and Code Snippets

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Community Discussions

Trending Discussions on text2image

Tesseract not detecting any text on RGB images on Python

QUESTION

Tesseract not detecting any text on RGB images on Python

Asked 2020-Apr-23 at 03:14

Hey I started working with Tesseract OCR but I'm having problems getting the text from really simple RGB images. It works just fine with text2image images. Here is my code:

...

ANSWER

Answered 2020-Apr-23 at 03:14

After thresholding, you can use findContours to find contour for each shape. Then you can filter the contours and put every contour you are interested in into a blank white image. By then, you will get the letters and ready to process using tesseract. You can see the detail in the code below.

Source https://stackoverflow.com/questions/61363243

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