You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 
Go to file
Branko Kokanovic 1a402fc63c
Landmark detection (custom model and class-based)
6 years ago
src Landmark detection (custom model and class-based) 6 years ago
tests Landmark detection (custom model and class-based) 6 years ago
.gitignore Adding configure.in to .gitignore 6 years ago
CMakeLists.txt fix: CMAKEList.txt to help CLion 6 years ago
CREDITS first commit 6 years ago
EXPERIMENTAL first commit 6 years ago
README.md Landmark detection (custom model and class-based) 6 years ago
config.m4 Support for raw chinese_whispers 6 years ago
config.w32 first commit 6 years ago
pdlib.cc Landmark detection (custom model and class-based) 6 years ago
pdlib.php first commit 6 years ago
php_pdlib.h first commit 6 years ago

README.md

PDlib - A PHP extension for Dlib

A PHP extension

Requirements

  • Dlib 19.13+
  • PHP 7.0+
  • C++ 11

Dependence

Dlib

Install Dlib as share library

git clone git@github.com:davisking/dlib.git
cd dlib/dlib
mkdir build
cd build
cmake -DBUILD_SHARED_LIBS=ON ..
make
sudo make install

Installation

git clone https://github.com/goodspb/pdlib.git
cd pdlib
phpize
./configure --enable-debug
make
sudo make install

Configure

vim youpath/php.ini

Write the below content into php.ini

[pdlib]
extension="pdlib.so"

Usage

face detection

<?php

// face detection
$faceCount = dlib_face_detection("~/a.jpg");
// how mary face in the picture.
var_dump($faceCount);

face landmark detection

<?php

// face landmark detection
$landmarks = dlib_face_landmark_detection("~/a.jpg");
var_dump($landmarks);

Additionally, you can also use class-based approach:

$rect = array("left"=>value, "top"=>value, "right"=>value, "bottom"=>value);
// You can download a trained facial shape predictor from:
// http://dlib.net/files/shape_predictor_5_face_landmarks.dat.bz2
$fld = new FaceLandmarkDetection("path/to/shape/predictor/model");
$parts = $fld->detect("path/to/image.jpg", $rect);
// $parts is integer array where keys are associative values with "x" and "y" for keys

Note that, if you use class-based approach, you need to feed bounding box rectangle with values obtained from dlib_face_detection. If you use dlib_face_landmark_detection, everything is already done for you (and you are using HOG face detection model).

chinese whispers

Provides raw access to dlib's chinese_whispers function. Client need to build and provide edges. Edges are provided as numeric array. Each element of this array should also be numeric array with 2 elements of long type.

Returned value is also numeric array, containing obtained labels.

<?php
// This example will cluster nodes 0 and 1, but would leave 2 out.
// $labels will look like [0,0,1].
$edges = [[0,0], [0,1], [1,1], [2,2]];
$labels = dlib_chinese_whispers($edges);

Features

  • 1.Face Detection
  • 2.Face Landmark Detection
  • 3.Deep Face Recognition
  • 4.Deep Learning Face Detection
  • 5. Raw chinese_whispers