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https://github.com/symisc/pixlab-php

Official PHP Client for the PixLab Machine Vision API
https://github.com/symisc/pixlab-php
api client computer-vision machine-learning php-library pixlab
Last synced: 3 days ago
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Official PHP Client for the PixLab Machine Vision API
Host: GitHub
URL: https://github.com/symisc/pixlab-php
Owner: symisc
License: bsd-2-clause
Created: 2017-05-02T00:54:52.000Z (over 7 years ago)
Default Branch: master
Last Pushed: 2023-10-09T01:50:45.000Z (about 1 year ago)
Last Synced: 2024-10-24T18:04:43.525Z (22 days ago)
Topics: api, client, computer-vision, machine-learning, php-library, pixlab
Language: PHP
Homepage: https://pixlab.io/start
Size: 23.4 KB
Stars: 10
Watchers: 4
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE
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README

        # PixLab Machine Vision APIs - Official PHP Client 

[![GitHub package version](https://img.shields.io/badge/Packagist-Ready-green.svg)](https://packagist.org/packages/symisc/pixlab-php)

This is the official PixLab PHP Client for the [PixLab](https://pixlab.io) Machine Vision API. The client is a single PHP class which let you interact with the API server using the GET and POST HTTP methods.

For the full list of samples using this class, please refer to: 

* [PHP Code Samples](https://github.com/symisc/pixlab/tree/master/PHP)

* [PixLab Examples Page](https://pixlab.io/examples)

* [Implement a Minimalistic KYC Form & Identify Verification Check ](https://dev.to/unqlite_db/implement-a-minimalistic-kyc-form-identify-verification-check-36f5)

* [Step-by-step guide to do e-KYC in your app](https://itnext.io/step-by-step-guide-to-do-e-kyc-in-your-app-c3b4e240617)

* [Scanning Malaysian, UAE, India & Others ID Cards with PixLab API](https://levelup.gitconnected.com/scanning-malaysian-id-cards-with-pixlab-api-33dd527a9408)

## Example: Scan Passports, Visas or ID cards from various countries:

```php

require_once "pixlab.php";

# Given a government issued passport document, extract the user face and parse all MRZ fields.

#

# PixLab recommend that you connect your AWS S3 bucket via your dashboard at https://pixlab.io/dashboard

# so that any cropped face or MRZ crop is stored automatically on your S3 bucket rather than the PixLab one.

# This feature should give you full control over your analyzed media files.

#

# https://pixlab.io/cmd?id=docscan for additional information.

/* Passport prototype: Of course, replace with a real government issued passport if you 

 * want to deal with a real world situation.

 */

$passport = 'https://i.stack.imgur.com/oJY2K.png';

# Your PixLab key

$key = 'PIXLAB_API_KEY';

/* Process */

$pix = new Pixlab($key);

if( !$pix->get('docscan',[

	'img' => $passport,  /* Passport scanned image */ 

	'type' => 'passport' /* Type of document we are going to scan */ 

	]) ){

	echo $pix->get_error_message()."\n";

	die;

}

/* Output the scan result */

echo "User Cropped Face: " . $pix->json->face_url . "\n";

echo "MRZ Cropped Image: " . $pix->json->mrz_img_url . "\n";

echo "Raw MRZ Text: " . $pix->json->mrz_raw_text . "\n";

echo "MRZ Fields:\n";

/* Display all parsed MRZ fields */

echo "\tIssuing Country: " . $pix->json->fields->issuingCountry . "\n";

echo "\tFull Name: "       . $pix->json->fields->fullName . "\n";

echo "\tDocument Number: " . $pix->json->fields->documentNumber  . "\n";

echo "\tCheck Digit: "   . $pix->json->fields->checkDigit . "\n";

echo "\tNationality: "   . $pix->json->fields->nationality . "\n";

echo "\tDate Of Birth: " . $pix->json->fields->dateOfBirth . "\n";

echo "\tSex: "           . $pix->json->fields->sex . "\n";

echo "\tDate Of Expiry: "    . $pix->json->fields->dateOfExpiry . "\n";

echo "\tPersonal Number: "   . $pix->json->fields->personalNumber . "\n";

echo "\tFinal Check Digit: " . $pix->json->fields->finalcheckDigit . "\n";

```

## First Example: Blur all human faces:

```php

require_once "pixlab.php";

/*

 * Detect all human faces in a given image or video frame via `facedetect` and blur all of them via `mogrify`.

 * https://pixlab.io/#/cmd?id=facedetect & https://pixlab.io/#/cmd?id=mogrify for additional information.

 */

 

# Target Image: Feel free to change to whatever image holding faces you want

$img = 'http://cf.broadsheet.ie/wp-content/uploads/2015/03/jeremy-clarkson_3090507b.jpg';

$key = 'My_Pix_Key';

$pix = new Pixlab($key);

echo "Detecting faces first...\n";

/* Invoke facedetect first  */

if( !$pix->get('facedetect',array('img' => $img)) ){

	echo $pix->get_error_message();

	die;

}

/* Grab the total number of detected faces */

$faces = $pix->json->faces;

if( count($faces) < 1 ){

	echo "No human faces were were detected on this picture\n";

}else{

	echo "Total number of detected faces: ".count($faces)."\n";

	echo "Censuring faces...\n";

	/* Call mogrify (Only POST) */

	if( !$pix->post('mogrify',array('img' => $img,'cord' => $faces)) ){

		echo $pix->get_error_message();

	}else{

		echo "Censured Faces: ".$pix->json->link."\n";

	}

}

```

## Second Example: Mimic Snapchat Filters

```php

/*

 * PixLab PHP Client which is just a single class PHP file without any dependency that you can get from Github

 * https://github.com/symisc/pixlab-php 

 */

require_once "pixlab.php";

# Detect all human faces & extract their landmark regions via facelandmarks & make a small Snapchat filter effect.

# Only three commands are actually needed in order to mimic the Snapchat filters effects:

# face landmarks:         https://pixlab.io/#/cmd?id=facelandmarks

# smart resize:           https://pixlab.io/#/cmd?id=smartresize

# merge:                  https://pixlab.io/#/cmd?id=merge

# Optionally: blur, grayscale, oilpaint, etc. for cool background effects.

$img = 'http://cf.broadsheet.ie/wp-content/uploads/2015/03/jeremy-clarkson_3090507b.jpg';

$pix = new Pixlab('My_Pix_Key');

/* Grab the face landmarks first */

if( !$pix->get('facelandmarks',[

	'img' => $img

	]) ){

	echo $pix->get_error_message()."\n";

	die;

}

$total = count($pix->json->faces); # Total detected faces

print($total." faces were detected\n");

$snap = [];

# Iterate all over the detected faces

foreach ($pix->json->faces as $face){

	$cord = $face->rectangle;

	# Show the face coordinates 

	print ("Coordinates...\n");

	print ("\n\twidth: " . $cord->width . ' height: ' . $cord->height . ' x: ' . $cord->left .' y: ' . $cord->top);

	

	# Show landmarks:

	print ("\nLandmarks...\n");

	

	$landmarks = $face->landmarks;

	

	print ("\n\tNose: X: "       . $landmarks->nose->x      . ", Y: ".$landmarks->nose->y);

	print ("\n\tBottom Lip: X: " . $landmarks->bottom_lip->x. ", Y: ".$landmarks->bottom_lip->y);

	print ("\n\tTop Lip: X: "    . $landmarks->top_lip->x   . ", Y: ".$landmarks->top_lip->y);

	print ("\n\tChin: X: "       . $landmarks->chin->x      . ", Y: ".$landmarks->chin->y);

	

	print ("\n\tBone Center: X: "     . $landmarks->bone->center->x     . ", Y: ".$landmarks->bone->center->y);

	print ("\n\tBone Outer Left: X: " . $landmarks->bone->outer_left->x . ", Y: ".$landmarks->bone->outer_left->y);

	print ("\n\tBone Outer Right: X: ". $landmarks->bone->outer_right->x. ", Y: ".$landmarks->bone->outer_right->y);

	

	print ("\n\tBone Center: X: " . $landmarks->bone->center->x . ", Y: ".$landmarks->bone->center->y);

	

	print ("\n\tEye Pupil Left: X: " . $landmarks->eye->pupil_left->x . ", Y: ".$landmarks->eye->pupil_left->y);

	print ("\n\tEye Pupil Right: X: " . $landmarks->eye->pupil_right->x . ", Y: ".$landmarks->eye->pupil_right->y);

	

	print ("\n\tEye Left Brown Inner: X: " . $landmarks->eye->left_brow_inner->x . ", Y: ".$landmarks->eye->left_brow_inner->y);

	print ("\n\tEye Right Brown Inner: X: " . $landmarks->eye->right_brow_inner->x . ", Y: ".$landmarks->eye->right_brow_inner->y);

	

	print ("\n\tEye Left Outer: X: " . $landmarks->eye->left_outer->x . ", Y: ".$landmarks->eye->left_outer->y);

	print ("\n\tEye Right Outer: X: " . $landmarks->eye->right_outer->x . ", Y: ".$landmarks->eye->right_outer->y); 

	

	# More landmarks on the docs..

	

	# Pick the last face in this loop for the sack of simplicity. Refer to the sample set for a complete example

	$snap = $face;

}

# Make a quick Snapchat filter on top of the last detected face

if ($total < 1){

    # No faces were detected

	die;

}

 

# The flower crown to be composited on top of the target face

$flower = 'http://pixlab.xyz/images/flower_crown.png';

# Resize the flower crown which is quite big right now to exactly the face width using smart resize.

print ("\nResizing the snap flower crown...\n");

if( !$pix->get('smartresize',[

	'img' => $flower,

	'width' => 20 + $snap->rectangle->width, # Face width

	'height' => 0 # Let Pixlab decide the best height for this picture

	]) ){

	echo $pix->get_error_message()."\n";

}else{

	$flower = $pix->json->link;

}

# Finally, Perform the composite operation

print ("Composite operation...\n");

if( !$pix->post('merge',[

	'src' => $img,

	'cord' => [

	array( /* Array for each landmarks */

		'img' => $flower,

		'x' => $snap->landmarks->bone->outer_left->x,

		'y' => $snap->landmarks->bone->outer_left->y /* Adjust for optimal effect */

	)

	]]) ){

	echo $pix->get_error_message();

}else{

	 # Optionally call blur, oilpaint, grayscale for more stuff..

	print ("Snap Filter Effect: ".$pix->json->link);

}

echo "\n";

```

## Third example: Blur an image or video frame based on its NSFW score

```php

require_once "pixlab.php";

# Target Image: Change to any link (Possibly adult) you want or switch to POST if you want to upload your image directly.

# The target API endpoint we'll be using here: nsfw (https://pixlab.io/cmd?id=nsfw).

$img = 'https://i.redd.it/oetdn9wc13by.jpg';

# Your PixLab key

$key = 'My_Pixlab_Key';

# Blur an image based on its NSFW score

$pix = new Pixlab($key);

/* Invoke NSFW */

if( !$pix->get('nsfw',array('img' => $img)) ){

	echo $pix->get_error_message();

	die;

}

/* Grab the NSFW score */

$score = $pix->json->score;

if( $score < 0.5 ){

	echo "No adult content were detected on this picture\n";

}else{

	echo "Censuring NSFW picture...\n";

	/* Call blur with the highest possible radius and sigma */

	if( !$pix->get('blur',array('img' => $img,'rad' => 50,'sig' =>30)) ){

		echo $pix->get_error_message();

	}else{

		echo "Censured Picture: ".$pix->json->link."\n";

	}

}

?>

```

### Last example:  Detect input language & extract text content from there using PixLab OCR.

```php

/*

 * PixLab PHP Client which is just a single class PHP file without any dependency that you can get from Github

 * https://github.com/symisc/pixlab-php 

 */

require_once "pixlab.php";

# Given an image with human readable characters. Detect input language & extract text content from there.

# https://pixlab.io/#/cmd?id=ocr for additional information.

/* Target image with human readable text input */

$img = 'http://quotesten.com/wp-content/uploads/2016/06/Confucius-Quote.jpg';

# Your PixLab key

$key = 'My_PixLab_Key';

/* Process */

$pix = new Pixlab($key);

if( !$pix->get('ocr',array('img' => $img)) ){

	echo $pix->get_error_message()."\n";

	die;

}

echo "Input language: ".$pix->json->lang;

echo "\nText Output: ".$pix->json->output."\n";

```

## Useful Links

* [The PixLab API in 5 minutes or less](https://pixlab.io/start).

* [List of API endpoints](https://pixlab.io/api).

* [The PixLab API Reference Guide](https://pixlab.io/cmdls).

* [The PixLab Sample Set](https://pixlab.io/examples).