mobile-document-scanner | Trying to improve https | Learning library

by LuizFritsch Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | mobile-document-scanner Summary

mobile-document-scanner is a Python library typically used in Tutorial, Learning, OpenCV applications. mobile-document-scanner has no bugs, it has no vulnerabilities and it has low support. However mobile-document-scanner build file is not available. You can download it from GitHub, GitLab.

Trying to improve tutorial

Support

Quality

Security

License

Reuse

Support

mobile-document-scanner has a low active ecosystem.

It has 4 star(s) with 0 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

mobile-document-scanner has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of mobile-document-scanner is current.

Quality

mobile-document-scanner has 0 bugs and 0 code smells.

Security

mobile-document-scanner has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

mobile-document-scanner code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

mobile-document-scanner does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

mobile-document-scanner releases are not available. You will need to build from source code and install.

mobile-document-scanner has no build file. You will be need to create the build yourself to build the component from source.

It has 45 lines of code, 0 functions and 1 files.

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

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mobile-document-scanner Key Features

No Key Features are available at this moment for mobile-document-scanner.

mobile-document-scanner Examples and Code Snippets

No Code Snippets are available at this moment for mobile-document-scanner.

Community Discussions

Trending Discussions on mobile-document-scanner

Finding the contour closest to image center in OpenCV2

Why everybody convert image to gray-scale before performing operations on openCV

QUESTION

Finding the contour closest to image center in OpenCV2

Asked 2020-May-01 at 16:24

I am trying to use openCV2 to automatically delineate the contours of churches and cathedrals from static maps.

In a nutshell, I am:

scraping the building's coordinates from this Wikipedia page.
creating a map centered on those coordinates using Folium, a Python library.
saving the map as a jpg image.
applying openCV2's findContours method to delineate the contours of the buildings.

I initially assumed that the cathedrals would be the largest building within a few hundred meters, so I sorted the contours by area following this PyImageSearch tutorial:

...

ANSWER

Answered 2020-May-01 at 16:24

I used cv2.moments(contour) as shown in this article to get the center of each contour. Then you can use distance.euclidian from the scipy.spatial module to calculate the distance of each contour to the image center.

Sample Image:

Code:

Source https://stackoverflow.com/questions/61541559

QUESTION

Why everybody convert image to gray-scale before performing operations on openCV

Asked 2020-Jan-15 at 02:10

been trying to find the answer to why everybody converts an image to grayscale before processing?

For example, this website with instructions teaching people how to build a simple scanning program converts photo to greyscale first before passing commands to manipulate the image itself.

In the second example, this thread on stackoverflow shows a person also converts the image to grayscale before extracting text from his image.

Does this process make the image easier to manipulate? Or does it give better results when extracting text? If so, shouldn't a binary image give the best result in the case of extracting text?

...

ANSWER

Answered 2020-Jan-15 at 02:10

More often than not, grayscale has all the relevant information to complete a particular task. So reducing the image to grayscale greatly simplifies calculations and removes redundancies.

Binary image is great too but it sacrifices too many information for it to be useful in many cases. And most library supports a minimum of 8 bit image processing anyway for a true binary data structure to be useful.

Imagine having to create a program to recognize text on paper. Having a color image doesn't help you to better read the text. The text can be in various color but you can read the text even if its in black and white. You can argue that binary image should also give the same performance and that is true IF there are no noise such as shadow on the paper.

Once there are noise elements exist on the image, you will need more information to separate text from noise and that is when grayscale is useful.

Moreover the most used and reliable information for advanced image processing is the edges and its textures. Both which can be obtained from a grayscale image.

Source https://stackoverflow.com/questions/59729902

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

Vulnerabilities

No vulnerabilities reported

Install mobile-document-scanner

You can download it from GitHub, GitLab.
You can use mobile-document-scanner 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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