Merge pull request #4 from matlab-deep-learning/bugfix/detectFacesOpt…

…ions/3

Adds support for Name Value pairs in detectFaces

.gitignore

@@ -0,0 +1 @@
+*.mltbx

README.md

@@ -47,7 +47,7 @@ detector = mtcnn.Detector();
 
 The detector object accepts the same optional arguments as the `mtcnn.detectFaces` function.
 
-Refer to the MATLAB toolbox documentation or [click here](docs/gettings_started.md) for a complete example.
+Refer to the MATLAB toolbox documentation or [click here](docs/getting_started.md) for a complete example.
 
 ## About
 

code/mtcnn/+mtcnn/detectFaces.m

@@ -1,4 +1,4 @@
-function [bboxes, scores, landmarks] = detectFaces(im)
+function [bboxes, scores, landmarks] = detectFaces(im, varargin)
 % detectFaces   Use a pretrained model to detect faces in an image.
 %
 %   Args:
@@ -34,6 +34,6 @@
 
 % Copyright 2019 The MathWorks, Inc.
 
-    detector = mtcnn.Detector();
+    detector = mtcnn.Detector(varargin{:});
     [bboxes, scores, landmarks] = detector.detect(im);
 end

code/mtcnn/Contents.m

@@ -1,5 +1,5 @@
 % MTCNN
-% Version 1.0 (R2019b) 02-December-2019
+% Version 1.0.1 (R2019b) 22-January-2020
 %
 % Files
 %   mtcnn.detectFaces   - Use a pretrained model to detect faces in an image.

mtcnn.prj

@@ -8,7 +8,7 @@
     <param.description>This repository implements deep learning based face detection and facial landmark localisation using Multi-Task Cascaded CNNs.
 For more details see the GitHub repository: https://github.com/matlab-deep-learning/mtcnn-face-detection</param.description>
     <param.screenshot>${PROJECT_ROOT}\doc\logo.png</param.screenshot>
-    <param.version>1.0</param.version>
+    <param.version>1.0.1</param.version>
     <param.output>${PROJECT_ROOT}\MTCNN Face Detection.mltbx</param.output>
     <param.products.name>
       <item>Computer Vision Toolbox</item>
@@ -55,7 +55,6 @@ For more details see the GitHub repository: https://github.com/matlab-deep-learn
     <param.additional.sw.mac.url />
     <param.additional.sw.linux.url />
     <unset>
-      <param.version />
       <param.output />
       <param.platforms />
       <param.exclude.filters />

test/+tests/DetectFacesTest.m

@@ -32,6 +32,21 @@ function testDefaultDetect(test)
             test.assertEqual(scores, test.Reference.scores, "RelTol", 1e-6);
             test.assertEqual(landmarks, test.Reference.landmarks, "RelTol", 1e-6);
         end
+
+        function testDetectWithOptions(test)
+            % We should be able to pass name value paris to detect faces
+            opts = {"MinSize", 20, ...
+                    "MaxSize", 100, ...
+                    "PyramidScale", 1.5, ...
+                    "ConfidenceThresholds", [0.6, 0.6, 0.6], ...
+                    "NmsThresholds", [0.6, 0.6, 0.6]};
+
+            [bboxes, scores, landmarks] = mtcnn.detectFaces(test.Image, opts{:});
+
+            test.assertEqual(size(bboxes), [6, 4]);
+            test.assertEqual(size(scores), [6, 1]);
+            test.assertEqual(size(landmarks), [6, 5, 2]); 
+        end
     end
 
 end