7de8d060b3
This change extends existing landmark detection in new ways: 1. Existing logic is hiding HOG model (frontal_face_detector) underneath and user cannot use other models (CNN model, for example). 2. Bounding box is exposed as additional argument, and user can define custom bounding box (which is needed, if image used to detect faces is changed (for example scaled), and we want to crop only face from original image to feed into shape predictor). 3. This approach is class-based, so no need for multiple loadings of shape predictor model (only once, in ctor) |
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| src | ||
| tests | ||
| .gitignore | ||
| CMakeLists.txt | ||
| config.m4 | ||
| config.w32 | ||
| CREDITS | ||
| EXPERIMENTAL | ||
| pdlib.cc | ||
| pdlib.php | ||
| php_pdlib.h | ||
| 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