passport-photo | Passport Photo Maker | Runtime Evironment library

by patmood JavaScript Version: Current License: No License

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kandi X-RAY | passport-photo Summary

passport-photo is a JavaScript library typically used in Server, Runtime Evironment, Nodejs applications. passport-photo has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Passport Photo Maker

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passport-photo has a low active ecosystem.

It has 12 star(s) with 4 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of passport-photo is current.

Quality

passport-photo has no bugs reported.

Security

passport-photo has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

passport-photo 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

passport-photo releases are not available. You will need to build from source code and install.

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passport-photo Key Features

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passport-photo Examples and Code Snippets

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Community Discussions

Trending Discussions on passport-photo

AWS recognition face API: Crop teeth section (mouth) from face

MATLAB - How to plot the boundary of a face?

QUESTION

AWS recognition face API: Crop teeth section (mouth) from face

Asked 2020-Oct-01 at 10:22

I'm cropping teeth section (mouth) from face based on x,y co-ordinates received from AWS recognition face API

this code is working and cropping the teeth section like

but I need only teeth section to be cropped.

AWS recognition API image response
...

ANSWER

Answered 2020-Oct-01 at 10:22

Your calculations for the mouth co-ordinates appear to be correct.

However, I see you are using:

Source https://stackoverflow.com/questions/64115639

QUESTION

MATLAB - How to plot the boundary of a face?

Asked 2017-Mar-26 at 09:01

I've been working with MATLAB for a couple of weeks now. But I am having trouble getting an accurate inner boundary of an input face image.

My code involves using Haar cascades to get the box around the face and the nose. Then I use the mid point of the nose box as the tip of the nose [nx, ny]. From then on, I try to get the boundary of the face by:

Converting it to gray scale
Increasing the contrast
Plotting the "Active Countour" of the face by searching only in the box bounded by the mask of range [rows, cols] plotted in blue. This active contour gives a rough image around the face
Since The boundary started going outside the face, I thought I needed to "erode" the image with imerode. This is followed by bwboundaries. I also commented out the alternative of using bwmorph and bwtraceboundaries.
imgradient, imfilter may be unnecessary, but I was playing around with it to see how everything would play out. When the boundary came inside the face, I thought of dialating the image with imdilate. I don't know if it is common practice to do so, but the boundary is mehh, but very ugly.

Here is the original image (without markers) : http://images.wisegeek.com/passport-photo.jpg

Here is the ungly bordered image:

The code that powers this :

...

ANSWER

Answered 2017-Mar-26 at 09:01

I extended your code to detect the face as shown below.

I started from the detection of nose and eyes using the CascadeObjectDetector. I extended these regions to include the mouth and eyebrows, respectively. These regions are forced to be part of the final face region.
The detection of the face boundary is done by thresholding the second order derivatives of the gray scale image. Especially the chin is hard to detect correctly. The border between the chin and the neck is highlighted by applying a large erosion step. Because this step is sensitive to noise in the face region, the image is first filtered non linearly by applying a small dilation and erosion step.
The face region is determined using the eroded image, otherwise the boundary between the chin and the neck may not be clear. Afterwards, the large erosion is undone by applying the (inverse) dilation step.
The results are quite good for the simple approach, but not perfect. You may obtain better results by iteratively changing the threshold used for the second order derivatives. If you start from a large threshold the neck will be included in the face region. You can detect it by assuming some maximum distance between the nose region and the bottom of the face. Then, you can decrease the threshold until the neck is not included anymore. Another alternative to make this method more robust may be to normalise the LoG.

Source https://stackoverflow.com/questions/43006950

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Vulnerabilities

No vulnerabilities reported

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