Migrate Android Face Detection sample to DNN.

modules/dnn/src/dnn_read.cpp

@@ -62,7 +62,9 @@ Net readNet(const String& _framework, const std::vector<uchar>& bufferModel,
         const std::vector<uchar>& bufferConfig)
 {
     String framework = toLowerCase(_framework);
-    if (framework == "caffe")
+    if (framework == "onnx")
+        return readNetFromONNX(bufferModel);
+    else if (framework == "caffe")
         return readNetFromCaffe(bufferConfig, bufferModel);
     else if (framework == "tensorflow")
         return readNetFromTensorflow(bufferModel, bufferConfig);

modules/objdetect/include/opencv2/objdetect/face.hpp

@@ -71,7 +71,7 @@ public:
      */
     CV_WRAP virtual int detect(InputArray image, OutputArray faces) = 0;
 
-    /** @brief Creates an instance of this class with given parameters
+    /** @brief Creates an instance of face detector class with given parameters
      *
      *  @param model the path to the requested model
      *  @param config the path to the config file for compability, which is not requested for ONNX models
@@ -90,6 +90,29 @@ public:
                                               int top_k = 5000,
                                               int backend_id = 0,
                                               int target_id = 0);
+
+    /** @overload
+     *
+     *  @param framework Name of origin framework
+     *  @param bufferModel A buffer with a content of binary file with weights
+     *  @param bufferConfig A buffer with a content of text file contains network configuration
+     *  @param input_size the size of the input image
+     *  @param score_threshold the threshold to filter out bounding boxes of score smaller than the given value
+     *  @param nms_threshold the threshold to suppress bounding boxes of IoU bigger than the given value
+     *  @param top_k keep top K bboxes before NMS
+     *  @param backend_id the id of backend
+     *  @param target_id the id of target device
+     */
+    CV_WRAP static Ptr<FaceDetectorYN> create(const String& framework,
+                                              const std::vector<uchar>& bufferModel,
+                                              const std::vector<uchar>& bufferConfig,
+                                              const Size& input_size,
+                                              float score_threshold = 0.9f,
+                                              float nms_threshold = 0.3f,
+                                              int top_k = 5000,
+                                              int backend_id = 0,
+                                              int target_id = 0);
+
 };
 
 /** @brief DNN-based face recognizer

modules/objdetect/src/face_detect.cpp

@@ -48,6 +48,35 @@ public:
         topK = top_k;
     }
 
+    FaceDetectorYNImpl(const String& framework,
+                       const std::vector<uchar>& bufferModel,
+                       const std::vector<uchar>& bufferConfig,
+                       const Size& input_size,
+                       float score_threshold,
+                       float nms_threshold,
+                       int top_k,
+                       int backend_id,
+                       int target_id)
+                       :divisor(32),
+                       strides({8, 16, 32})
+    {
+        net = dnn::readNet(framework, bufferModel, bufferConfig);
+        CV_Assert(!net.empty());
+
+        net.setPreferableBackend(backend_id);
+        net.setPreferableTarget(target_id);
+
+        inputW = input_size.width;
+        inputH = input_size.height;
+
+        padW = (int((inputW - 1) / divisor) + 1) * divisor;
+        padH = (int((inputH - 1) / divisor) + 1) * divisor;
+
+        scoreThreshold = score_threshold;
+        nmsThreshold = nms_threshold;
+        topK = top_k;
+    }
+
     void setInputSize(const Size& input_size) override
     {
         inputW = input_size.width;
@@ -264,4 +293,22 @@ Ptr<FaceDetectorYN> FaceDetectorYN::create(const String& model,
 #endif
 }
 
+Ptr<FaceDetectorYN> FaceDetectorYN::create(const String& framework,
+                                           const std::vector<uchar>& bufferModel,
+                                           const std::vector<uchar>& bufferConfig,
+                                           const Size& input_size,
+                                           const float score_threshold,
+                                           const float nms_threshold,
+                                           const int top_k,
+                                           const int backend_id,
+                                           const int target_id)
+{
+#ifdef HAVE_OPENCV_DNN
+    return makePtr<FaceDetectorYNImpl>(framework, bufferModel, bufferConfig, input_size, score_threshold, nms_threshold, top_k, backend_id, target_id);
+#else
+    CV_UNUSED(model); CV_UNUSED(config); CV_UNUSED(input_size); CV_UNUSED(score_threshold); CV_UNUSED(nms_threshold); CV_UNUSED(top_k); CV_UNUSED(backend_id); CV_UNUSED(target_id);
+    CV_Error(cv::Error::StsNotImplemented, "cv::FaceDetectorYN requires enabled 'dnn' module.");
+#endif
+}
+
 } // namespace cv