pdlib/tests/face_landmark_detection_ctor_error.phpt

--TEST--
Testing FaceLandmarkDetection constructor without arguments
--SKIPIF--
<?php if (!extension_loaded("pdlib")) print "skip"; ?>
--FILE--
<?php
try {
	new FaceLandmarkDetection();
} catch (Exception $e) {
	var_dump($e->getMessage());
}
try {
	new FaceLandmarkDetection("non-existent file");
} catch (Exception $e) {
	var_dump($e->getMessage());
}
?>
--EXPECTF--
Warning: FaceLandmarkDetection::__construct() expects exactly 1 parameter, 0 given in %s on line 3
string(41) "Unable to parse shape_predictor_file_path"
string(45) "Unable to open non-existent file for reading."
Landmark detection (custom model and class-based) 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) 2018-08-25 06:51:46 +08:00			`--TEST--`
			`Testing FaceLandmarkDetection constructor without arguments`
			`--SKIPIF--`
			`<?php if (!extension_loaded("pdlib")) print "skip"; ?>`
			`--FILE--`
			`<?php`
			`try {`
			`new FaceLandmarkDetection();`
			`} catch (Exception $e) {`
			`var_dump($e->getMessage());`
			`}`
			`try {`
			`new FaceLandmarkDetection("non-existent file");`
			`} catch (Exception $e) {`
			`var_dump($e->getMessage());`
			`}`
			`?>`
Fixing tests, closes #14 2019-11-29 06:14:34 +08:00			`--EXPECTF--`
			`Warning: FaceLandmarkDetection::__construct() expects exactly 1 parameter, 0 given in %s on line 3`
Landmark detection (custom model and class-based) 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) 2018-08-25 06:51:46 +08:00			`string(41) "Unable to parse shape_predictor_file_path"`
Fixing tests, closes #14 2019-11-29 06:14:34 +08:00			`string(45) "Unable to open non-existent file for reading."`