hblock | blocking ads , tracking and malware domains | Privacy library

by hectorm Shell Version: 3.4.5 License: MIT

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

kandi X-RAY | hblock Summary

hblock is a Shell library typically used in Security, Privacy applications. hblock has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub, GitLab.

hBlock is a POSIX-compliant shell script that gets a list of domains that serve ads, tracking scripts and malware from multiple sources and creates a hosts file, among other formats, that prevents your system from connecting to them.

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Support

hblock has a medium active ecosystem.

It has 1271 star(s) with 96 fork(s). There are 36 watchers for this library.

There were 1 major release(s) in the last 6 months.

There are 5 open issues and 114 have been closed. On average issues are closed in 4 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of hblock is 3.4.5

Quality

hblock has no bugs reported.

Security

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

License

hblock 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

hblock releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

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hblock Key Features

No Key Features are available at this moment for hblock.

hblock Examples and Code Snippets

No Code Snippets are available at this moment for hblock.

Community Discussions

Trending Discussions on hblock

Edge based binarization

How to calculate the mean of 3D matrices in an image without NaN?

QUESTION

Edge based binarization

Asked 2017-Dec-29 at 11:26

I am trying to implement the edge based binarization algorithm that was written in the research paper "Automatic License Plate Recognition Using Deep Learning Technique" but i as i implemented it i get the final image all black and can not find the problem.

...

ANSWER

Answered 2017-Dec-29 at 11:26

After comparing the given code with what has been stated in the paper, I must say that the appended implementation in the paper is wrong.

I didn't search for another proof, but from what was said in the paper, the algorithm binarizes an image by estimating a local threshold at edge pixels within a 10x5 pixel region and later assembling the whole binary image from these rather small patches.

The given implementation instead slices the image into 10 vertical and 5 horizontal blocks, resulting in much larger regions.

Source https://stackoverflow.com/questions/48020440

QUESTION

How to calculate the mean of 3D matrices in an image without NaN?

Asked 2017-Oct-13 at 14:18

I need to calculate the mean of a 3D matrices (last step in the code). However, there are many NaNs in the (diff_dataframe./dataframe_vor) calculation. So when I use this code, some results will be NaN. How could I calculate the mean of this matrix by ignoring the NaNs? I attached the code as below.

...

ANSWER

Answered 2017-Oct-13 at 14:18

mean2 is a shortcut function that's part of the image processing toolbox that finds the entire average of a 2D region which doesn't include handling NaN. In that case, simply remove all values that are NaN and find the resulting average. Note that the removal of NaN unrolls the 2D region into a 1D vector, so we can simply use mean in this case. As an additional check, let's make sure there are no divide by 0 errors, so also check for Inf as well.

Therefore, replace this line:

Source https://stackoverflow.com/questions/46731236

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

Vulnerabilities

No vulnerabilities reported

Install hblock

hBlock is available in various package managers. Please check the PACKAGES.md file for an up-to-date list.

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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