COMPMID-1849: Implement CPPDetectionPostProcessLayer

* Add DetectionPostProcessLayer
* Add DetectionPostProcessLayer at the graph

Change-Id: I7e56f6cffc26f112d26dfe74853085bb8ec7d849
Signed-off-by: Isabella Gottardi <isabella.gottardi@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1639
Reviewed-by: Giuseppe Rossini <giuseppe.rossini@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

14 files changed, 450 insertions, 8 deletions

diff --git a/arm_compute/core/Types.h b/arm_compute/core/Types.h
index 2c17f273a5..6df74e7b88 100644
--- a/arm_compute/core/Types.h
+++ b/arm_compute/core/Types.h
@@ -34,6 +34,7 @@
 #include <cmath>
 #include <cstddef>
 #include <cstdint>
+#include <map>
 #include <string>
 #include <utility>
 
@@ -943,6 +944,11 @@ private:
     std::array<float, 2> _steps;
 };
 
+// Bounding Box [xmin, ymin, xmax, ymax]
+using BBox = std::array<float, 4>;
+// LabelBBox used for map label and bounding box
+using LabelBBox = std::map<int, std::vector<BBox>>;
+
 /** Available Detection Output code types */
 enum class DetectionOutputLayerCodeType
 {
@@ -1071,6 +1077,116 @@ private:
     int                          _num_loc_classes;
 };
 
+/** Detection Output layer info */
+class DetectionPostProcessLayerInfo final
+{
+public:
+    /** Default Constructor */
+    DetectionPostProcessLayerInfo()
+        : _max_detections(),
+          _max_classes_per_detection(),
+          _nms_score_threshold(),
+          _iou_threshold(),
+          _num_classes(),
+          _scales_values(),
+          _use_regular_nms(),
+          _detection_per_class()
+    {
+    }
+    /** Constructor
+     *
+     * @param[in] max_detections            Number of total detection.
+     * @param[in] max_classes_per_detection Number of total classes to be kept after NMS step. Used in the Fast Non-Max-Suppression
+     * @param[in] nms_score_threshold       Threshold to be used in NMS
+     * @param[in] iou_threshold             Threshold to be used during the intersection over union.
+     * @param[in] num_classes               Number of classes.
+     * @param[in] scales_values             Scales values used for decode center size boxes.
+     * @param[in] use_regular_nms           (Optional) Boolean to determinate if use regular or fast nms.
+     * @param[in] detection_per_class       (Optional) Number of detection per class. Used in the Regular Non-Max-Suppression
+     */
+    DetectionPostProcessLayerInfo(unsigned int max_detections, unsigned int max_classes_per_detection, float nms_score_threshold, float iou_threshold, unsigned int num_classes,
+                                  std::array<float, 4> scales_values, bool use_regular_nms = false, unsigned int detection_per_class = 100)
+        : _max_detections(max_detections),
+          _max_classes_per_detection(max_classes_per_detection),
+          _nms_score_threshold(nms_score_threshold),
+          _iou_threshold(iou_threshold),
+          _num_classes(num_classes),
+          _scales_values(scales_values),
+          _use_regular_nms(use_regular_nms),
+          _detection_per_class(detection_per_class)
+    {
+    }
+    /** Get max detections. */
+    unsigned int max_detections() const
+    {
+        return _max_detections;
+    }
+    /** Get max_classes per detection. Used in the Fast Non-Max-Suppression.*/
+    unsigned int max_classes_per_detection() const
+    {
+        return _max_classes_per_detection;
+    }
+    /** Get detection per class. Used in the Regular Non-Max-Suppression */
+    unsigned int detection_per_class() const
+    {
+        return _detection_per_class;
+    }
+    /** Get nms threshold. */
+    float nms_score_threshold() const
+    {
+        return _nms_score_threshold;
+    }
+    /** Get intersection over union threshold. */
+    float iou_threshold() const
+    {
+        return _iou_threshold;
+    }
+    /** Get num classes. */
+    unsigned int num_classes() const
+    {
+        return _num_classes;
+    }
+    /** Get if use regular nms. */
+    bool use_regular_nms() const
+    {
+        return _use_regular_nms;
+    }
+    /** Get y scale value. */
+    float scale_value_y() const
+    {
+        // Saved as [y,x,h,w]
+        return _scales_values[0];
+    }
+    /** Get x scale value. */
+    float scale_value_x() const
+    {
+        // Saved as [y,x,h,w]
+        return _scales_values[1];
+    }
+    /** Get h scale value. */
+    float scale_value_h() const
+    {
+        // Saved as [y,x,h,w]
+        return _scales_values[2];
+    }
+    /** Get w scale value. */
+    float scale_value_w() const
+    {
+        // Saved as [y,x,h,w]
+        return _scales_values[3];
+    }
+
+private:
+    unsigned int _max_detections;
+    unsigned int _max_classes_per_detection;
+    float        _nms_score_threshold;
+    float        _iou_threshold;
+    unsigned int _num_classes;
+    std::array<float, 4> _scales_values;
+    bool         _use_regular_nms;
+    unsigned int _detection_per_class;
+};
+
 /** Pooling Layer Information class */
 class PoolingLayerInfo
 {
diff --git a/arm_compute/graph/GraphBuilder.h b/arm_compute/graph/GraphBuilder.h
index e1049ca938..dc41ed5367 100644
--- a/arm_compute/graph/GraphBuilder.h
+++ b/arm_compute/graph/GraphBuilder.h
@@ -217,6 +217,21 @@ public:
      * @return Node ID of the created node, EmptyNodeID in case of error
      */
     static NodeID add_detection_output_node(Graph &g, NodeParams params, NodeIdxPair input_loc, NodeIdxPair input_conf, NodeIdxPair input_priorbox, const DetectionOutputLayerInfo &detect_info);
+    /** Adds a detection post process layer node to the graph
+     *
+     * @param[in] g                      Graph to add the node to
+     * @param[in] params                 Common node parameters
+     * @param[in] input_box_encoding     Boxes input to the detection output layer node as a NodeID-Index pair
+     * @param[in] input_class_prediction Class prediction input to the detection output layer node as a NodeID-Index pair
+     * @param[in] detect_info            Detection output layer parameters
+     * @param[in] anchors_accessor       (Optional) Const Node ID that contains the anchor values
+     * @param[in] anchor_quant_info      (Optional) Anchor quantization info
+     *
+     * @return Node ID of the created node, EmptyNodeID in case of error
+     */
+    static NodeID add_detection_post_process_node(Graph &g, NodeParams params, NodeIdxPair input_box_encoding, NodeIdxPair input_class_prediction,
+                                                  const DetectionPostProcessLayerInfo &detect_info, ITensorAccessorUPtr anchors_accessor = nullptr,
+                                                  const QuantizationInfo &anchor_quant_info = QuantizationInfo());
     /** Adds a Dummy node to the graph
      *
      * @note this node if for debugging purposes. Just alters the shape of the graph pipeline as requested.
diff --git a/arm_compute/graph/INodeVisitor.h b/arm_compute/graph/INodeVisitor.h
index 5c5b777ac9..f97906d02a 100644
--- a/arm_compute/graph/INodeVisitor.h
+++ b/arm_compute/graph/INodeVisitor.h
@@ -76,6 +76,11 @@ public:
      * @param[in] n Node to visit.
      */
     virtual void visit(DetectionOutputLayerNode &n) = 0;
+    /** Visit DetectionPostProcessLayerNode.
+     *
+     * @param[in] n Node to visit.
+     */
+    virtual void visit(DetectionPostProcessLayerNode &n) = 0;
     /** Visit EltwiseLayerNode.
      *
      * @param[in] n Node to visit.
@@ -199,6 +204,10 @@ public:
     {
         default_visit();
     }
+    virtual void visit(DetectionPostProcessLayerNode &n) override
+    {
+        default_visit();
+    }
     virtual void visit(DepthwiseConvolutionLayerNode &n) override
     {
         default_visit();
diff --git a/arm_compute/graph/TypePrinter.h b/arm_compute/graph/TypePrinter.h
index 9da0e6157c..e4188125b9 100644
--- a/arm_compute/graph/TypePrinter.h
+++ b/arm_compute/graph/TypePrinter.h
@@ -86,6 +86,9 @@ inline ::std::ostream &operator<<(::std::ostream &os, const NodeType &node_type)
         case NodeType::DetectionOutputLayer:
             os << "DetectionOutputLayer";
             break;
+        case NodeType::DetectionPostProcessLayer:
+            os << "DetectionPostProcessLayer";
+            break;
         case NodeType::DepthwiseConvolutionLayer:
             os << "DepthwiseConvolutionLayer";
             break;
diff --git a/arm_compute/graph/Types.h b/arm_compute/graph/Types.h
index 9f962425b3..8b97708a63 100644
--- a/arm_compute/graph/Types.h
+++ b/arm_compute/graph/Types.h
@@ -48,6 +48,7 @@ using arm_compute::PermutationVector;
 
 using arm_compute::ActivationLayerInfo;
 using arm_compute::DetectionOutputLayerInfo;
+using arm_compute::DetectionPostProcessLayerInfo;
 using arm_compute::NormType;
 using arm_compute::NormalizationLayerInfo;
 using arm_compute::FullyConnectedLayerInfo;
@@ -137,6 +138,7 @@ enum class NodeType
     DeconvolutionLayer,
     DepthwiseConvolutionLayer,
     DetectionOutputLayer,
+    DetectionPostProcessLayer,
     EltwiseLayer,
     FlattenLayer,
     FullyConnectedLayer,
diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h
index ed5b35c0d1..dd833061a9 100644
--- a/arm_compute/graph/backends/FunctionHelpers.h
+++ b/arm_compute/graph/backends/FunctionHelpers.h
@@ -644,6 +644,62 @@ std::unique_ptr<IFunction> create_detection_output_layer(DetectionOutputLayerNod
 
     return std::move(func);
 }
+
+/** Create a backend detection post process layer function
+ *
+ * @tparam DetectionPostProcessLayerFunction Backend detection output function
+ * @tparam TargetInfo                        Target-specific information
+ *
+ * @param[in] node Node to create the backend function for
+ *
+ * @return Backend detection post process layer function
+ */
+template <typename DetectionPostProcessLayerFunction, typename TargetInfo>
+std::unique_ptr<IFunction> create_detection_post_process_layer(DetectionPostProcessLayerNode &node)
+{
+    validate_node<TargetInfo>(node, 3 /* expected inputs */, 4 /* expected outputs */);
+
+    // Extract IO and info
+    typename TargetInfo::TensorType    *input0      = get_backing_tensor<TargetInfo>(node.input(0));
+    typename TargetInfo::TensorType    *input1      = get_backing_tensor<TargetInfo>(node.input(1));
+    typename TargetInfo::TensorType    *input2      = get_backing_tensor<TargetInfo>(node.input(2));
+    typename TargetInfo::TensorType    *output0     = get_backing_tensor<TargetInfo>(node.output(0));
+    typename TargetInfo::TensorType    *output1     = get_backing_tensor<TargetInfo>(node.output(1));
+    typename TargetInfo::TensorType    *output2     = get_backing_tensor<TargetInfo>(node.output(2));
+    typename TargetInfo::TensorType    *output3     = get_backing_tensor<TargetInfo>(node.output(3));
+    const DetectionPostProcessLayerInfo detect_info = node.detection_post_process_info();
+
+    ARM_COMPUTE_ERROR_ON(input0 == nullptr);
+    ARM_COMPUTE_ERROR_ON(input1 == nullptr);
+    ARM_COMPUTE_ERROR_ON(input2 == nullptr);
+    ARM_COMPUTE_ERROR_ON(output0 == nullptr);
+    ARM_COMPUTE_ERROR_ON(output1 == nullptr);
+    ARM_COMPUTE_ERROR_ON(output2 == nullptr);
+    ARM_COMPUTE_ERROR_ON(output3 == nullptr);
+
+    // Create and configure function
+    auto func = support::cpp14::make_unique<DetectionPostProcessLayerFunction>();
+    func->configure(input0, input1, input2, output0, output1, output2, output3, detect_info);
+
+    // Log info
+    ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated "
+                               << node.name()
+                               << " Type: " << node.type()
+                               << " Target: " << TargetInfo::TargetType
+                               << " Data Type: " << input0->info()->data_type()
+                               << " Input0 shape: " << input0->info()->tensor_shape()
+                               << " Input1 shape: " << input1->info()->tensor_shape()
+                               << " Input2 shape: " << input2->info()->tensor_shape()
+                               << " Output0 shape: " << output0->info()->tensor_shape()
+                               << " Output1 shape: " << output1->info()->tensor_shape()
+                               << " Output2 shape: " << output2->info()->tensor_shape()
+                               << " Output3 shape: " << output3->info()->tensor_shape()
+                               << " DetectionPostProcessLayer info: " << detect_info
+                               << std::endl);
+
+    return std::move(func);
+}
+
 /** Create a backend element-wise operation layer function
  *
  * @tparam EltwiseFunctions Backend element-wise function
diff --git a/arm_compute/graph/backends/ValidateHelpers.h b/arm_compute/graph/backends/ValidateHelpers.h
index 3a5686336b..13de273bdf 100644
--- a/arm_compute/graph/backends/ValidateHelpers.h
+++ b/arm_compute/graph/backends/ValidateHelpers.h
@@ -228,6 +228,33 @@ Status validate_detection_output_layer(DetectionOutputLayerNode &node)
 
     return DetectionOutputLayer::validate(input0, input1, input2, output, detect_info);
 }
+/** Validates a detection post process layer node
+ *
+ * @tparam DetectionPostProcessLayer DetectionOutput layer type
+ *
+ * @param[in] node Node to validate
+ *
+ * @return Status
+ */
+template <typename DetectionPostProcessLayer>
+Status validate_detection_post_process_layer(DetectionPostProcessLayerNode &node)
+{
+    ARM_COMPUTE_LOG_GRAPH_VERBOSE("Validating DetectionPostProcessLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl);
+    ARM_COMPUTE_RETURN_ERROR_ON(node.num_inputs() != 3);
+    ARM_COMPUTE_RETURN_ERROR_ON(node.num_outputs() != 4);
+
+    // Extract IO and info
+    arm_compute::ITensorInfo           *input0      = get_backing_tensor_info(node.input(0));
+    arm_compute::ITensorInfo           *input1      = get_backing_tensor_info(node.input(1));
+    arm_compute::ITensorInfo           *input2      = get_backing_tensor_info(node.input(2));
+    arm_compute::ITensorInfo           *output0     = get_backing_tensor_info(node.output(0));
+    arm_compute::ITensorInfo           *output1     = get_backing_tensor_info(node.output(1));
+    arm_compute::ITensorInfo           *output2     = get_backing_tensor_info(node.output(2));
+    arm_compute::ITensorInfo           *output3     = get_backing_tensor_info(node.output(3));
+    const DetectionPostProcessLayerInfo detect_info = node.detection_post_process_info();
+
+    return DetectionPostProcessLayer::validate(input0, input1, input2, output0, output1, output2, output3, detect_info);
+}
 
 /** Validates a Generate Proposals layer node
  *
diff --git a/arm_compute/graph/frontend/Layers.h b/arm_compute/graph/frontend/Layers.h
index 3fc4af46d5..27a0cd3026 100644
--- a/arm_compute/graph/frontend/Layers.h
+++ b/arm_compute/graph/frontend/Layers.h
@@ -493,6 +493,39 @@ private:
     SubStream                _ss_prior;
     DetectionOutputLayerInfo _detect_info;
 };
+/** DetectionOutputPostProcess Layer */
+class DetectionPostProcessLayer final : public ILayer
+{
+public:
+    /** Construct a detection output layer.
+     *
+     * @param[in] sub_stream_class_prediction Class prediction graph sub-stream.
+     * @param[in] detect_info                 DetectionOutput parameters.
+     * @param[in] anchors                     Accessor to get anchors tensor data from.
+     * @param[in] out_quant_info              (Optional) Output quantization info
+     */
+    DetectionPostProcessLayer(SubStream &&sub_stream_class_prediction, DetectionPostProcessLayerInfo detect_info, ITensorAccessorUPtr anchors,
+                              const QuantizationInfo out_quant_info = QuantizationInfo())
+        : _sub_stream_class_prediction(std::move(sub_stream_class_prediction)), _detect_info(detect_info), _anchors(std::move(anchors)), _out_quant_info(std::move(out_quant_info))
+    {
+    }
+
+    NodeID create_layer(IStream &s) override
+    {
+        ARM_COMPUTE_ERROR_ON(_anchors == nullptr);
+
+        NodeParams  common_params          = { name(), s.hints().target_hint };
+        NodeIdxPair input_box_encoding     = { s.tail_node(), 0 };
+        NodeIdxPair input_class_prediction = { _sub_stream_class_prediction.tail_node(), 0 };
+        return GraphBuilder::add_detection_post_process_node(s.graph(), common_params, input_box_encoding, input_class_prediction, _detect_info, std::move(_anchors), std::move(_out_quant_info));
+    }
+
+private:
+    SubStream                     _sub_stream_class_prediction;
+    DetectionPostProcessLayerInfo _detect_info;
+    ITensorAccessorUPtr           _anchors;
+    const QuantizationInfo        _out_quant_info;
+};
 /** Dummy Layer */
 class DummyLayer final : public ILayer
 {
diff --git a/arm_compute/graph/nodes/DetectionPostProcessLayerNode.h b/arm_compute/graph/nodes/DetectionPostProcessLayerNode.h
new file mode 100644
index 0000000000..76b1d8ce98
--- /dev/null
+++ b/arm_compute/graph/nodes/DetectionPostProcessLayerNode.h
@@ -0,0 +1,62 @@
+/*
+ * Copyright (c) 2019 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef __ARM_COMPUTE_GRAPH_DETECTION_POST_PROCESS_LAYER_NODE_H__
+#define __ARM_COMPUTE_GRAPH_DETECTION_POST_PROCESS_LAYER_NODE_H__
+
+#include "arm_compute/graph/INode.h"
+
+namespace arm_compute
+{
+namespace graph
+{
+/** DetectionPostProcess Layer node */
+class DetectionPostProcessLayerNode final : public INode
+{
+public:
+    /** Constructor
+     *
+     * @param[in] detection_info DetectionPostProcess Layer information
+     */
+    DetectionPostProcessLayerNode(DetectionPostProcessLayerInfo detection_info);
+    /** DetectionPostProcess metadata accessor
+     *
+     * @return DetectionPostProcess Layer info
+     */
+    DetectionPostProcessLayerInfo detection_post_process_info() const;
+
+    // Inherited overridden methods:
+    NodeType         type() const override;
+    bool             forward_descriptors() override;
+    TensorDescriptor configure_output(size_t idx) const override;
+    void accept(INodeVisitor &v) override;
+
+private:
+    DetectionPostProcessLayerInfo _info;
+
+    static const int kNumCoordBox = 4;
+    static const int kBatchSize   = 1;
+};
+} // namespace graph
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_GRAPH_DETECTION_POST_PROCESS_LAYER_NODE_H__ */
\ No newline at end of file
diff --git a/arm_compute/graph/nodes/Nodes.h b/arm_compute/graph/nodes/Nodes.h
index 52e2f88528..1586270093 100644
--- a/arm_compute/graph/nodes/Nodes.h
+++ b/arm_compute/graph/nodes/Nodes.h
@@ -34,6 +34,7 @@
 #include "arm_compute/graph/nodes/DeconvolutionLayerNode.h"
 #include "arm_compute/graph/nodes/DepthwiseConvolutionLayerNode.h"
 #include "arm_compute/graph/nodes/DetectionOutputLayerNode.h"
+#include "arm_compute/graph/nodes/DetectionPostProcessLayerNode.h"
 #include "arm_compute/graph/nodes/DummyNode.h"
 #include "arm_compute/graph/nodes/EltwiseLayerNode.h"
 #include "arm_compute/graph/nodes/FlattenLayerNode.h"
diff --git a/arm_compute/graph/nodes/NodesFwd.h b/arm_compute/graph/nodes/NodesFwd.h
index 2c89679902..53f2a6a1b5 100644
--- a/arm_compute/graph/nodes/NodesFwd.h
+++ b/arm_compute/graph/nodes/NodesFwd.h
@@ -40,6 +40,7 @@ class ConvolutionLayerNode;
 class DeconvolutionLayerNode;
 class DepthwiseConvolutionLayerNode;
 class DetectionOutputLayerNode;
+class DetectionPostProcessLayerNode;
 class DummyNode;
 class EltwiseLayerNode;
 class FlattenLayerNode;
diff --git a/arm_compute/runtime/CPP/CPPFunctions.h b/arm_compute/runtime/CPP/CPPFunctions.h
index 1dff03f349..743929fae8 100644
--- a/arm_compute/runtime/CPP/CPPFunctions.h
+++ b/arm_compute/runtime/CPP/CPPFunctions.h
@@ -27,6 +27,7 @@
 /* Header regrouping all the CPP functions */
 #include "arm_compute/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.h"
 #include "arm_compute/runtime/CPP/functions/CPPDetectionOutputLayer.h"
+#include "arm_compute/runtime/CPP/functions/CPPDetectionPostProcessLayer.h"
 #include "arm_compute/runtime/CPP/functions/CPPNonMaximumSuppression.h"
 #include "arm_compute/runtime/CPP/functions/CPPPermute.h"
 #include "arm_compute/runtime/CPP/functions/CPPTopKV.h"
diff --git a/arm_compute/runtime/CPP/functions/CPPDetectionOutputLayer.h b/arm_compute/runtime/CPP/functions/CPPDetectionOutputLayer.h
index 71be8a0ad8..4e1b8f2a74 100644
--- a/arm_compute/runtime/CPP/functions/CPPDetectionOutputLayer.h
+++ b/arm_compute/runtime/CPP/functions/CPPDetectionOutputLayer.h
@@ -28,17 +28,10 @@
 
 #include "arm_compute/core/Types.h"
 
-#include <map>
-
 namespace arm_compute
 {
 class ITensor;
 
-// Normalized Bounding Box [xmin, ymin, xmax, ymax]
-using NormalizedBBox = std::array<float, 4>;
-// LabelBBox used for map label and bounding box
-using LabelBBox = std::map<int, std::vector<NormalizedBBox>>;
-
 /** CPP Function to generate the detection output based on location and confidence
  * predictions by doing non maximum suppression.
  *
@@ -91,7 +84,7 @@ private:
 
     std::vector<LabelBBox> _all_location_predictions;
     std::vector<std::map<int, std::vector<float>>> _all_confidence_scores;
-    std::vector<NormalizedBBox> _all_prior_bboxes;
+    std::vector<BBox> _all_prior_bboxes;
     std::vector<std::array<float, 4>> _all_prior_variances;
     std::vector<LabelBBox> _all_decode_bboxes;
     std::vector<std::map<int, std::vector<int>>> _all_indices;
diff --git a/arm_compute/runtime/CPP/functions/CPPDetectionPostProcessLayer.h b/arm_compute/runtime/CPP/functions/CPPDetectionPostProcessLayer.h
new file mode 100644
index 0000000000..c13def67c7
--- /dev/null
+++ b/arm_compute/runtime/CPP/functions/CPPDetectionPostProcessLayer.h
@@ -0,0 +1,123 @@
+/*
+ * Copyright (c) 2019 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef __ARM_COMPUTE_CPP_DETECTION_POSTPROCESS_H__
+#define __ARM_COMPUTE_CPP_DETECTION_POSTPROCESS_H__
+
+#include "arm_compute/runtime/CPP/ICPPSimpleFunction.h"
+
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/CPP/functions/CPPNonMaximumSuppression.h"
+#include "arm_compute/runtime/IMemoryManager.h"
+#include "arm_compute/runtime/MemoryGroup.h"
+#include "arm_compute/runtime/Tensor.h"
+
+#include <map>
+
+namespace arm_compute
+{
+class ITensor;
+
+/** CPP Function to generate the detection output based on center size encoded boxes, class prediction and anchors
+ *  by doing non maximum suppression.
+ *
+ * @note Intended for use with MultiBox detection method.
+ */
+class CPPDetectionPostProcessLayer : public IFunction
+{
+public:
+    /** Constructor */
+    CPPDetectionPostProcessLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    CPPDetectionPostProcessLayer(const CPPDetectionPostProcessLayer &) = delete;
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    CPPDetectionPostProcessLayer &operator=(const CPPDetectionPostProcessLayer &) = delete;
+    /** Configure the detection output layer CPP function
+     *
+     * @param[in]  input_box_encoding The bounding box input tensor. Data types supported: F32, QASYMM8.
+     * @param[in]  input_score        The class prediction input tensor. Data types supported: Same as @p input_box_encoding.
+     * @param[in]  input_anchors      The anchors input tensor. Data types supported: Same as @p input_box_encoding.
+     * @param[out] output_boxes       The boxes output tensor. Data types supported: F32.
+     * @param[out] output_classes     The classes output tensor. Data types supported: Same as @p output_boxes.
+     * @param[out] output_scores      The scores output tensor. Data types supported: Same as @p output_boxes.
+     * @param[out] num_detection      The number of output detection. Data types supported: Same as @p output_boxes.
+     * @param[in]  info               (Optional) DetectionPostProcessLayerInfo information.
+     *
+     * @note Output contains all the detections. Of those, only the ones selected by the valid region are valid.
+     */
+    void configure(const ITensor *input_box_encoding, const ITensor *input_score, const ITensor *input_anchors,
+                   ITensor *output_boxes, ITensor *output_classes, ITensor *output_scores, ITensor *num_detection, DetectionPostProcessLayerInfo info = DetectionPostProcessLayerInfo());
+    /** Static function to check if given info will lead to a valid configuration of @ref CPPDetectionPostProcessLayer
+     *
+     * @param[in]  input_box_encoding The bounding box input tensor info. Data types supported: F32, QASYMM8.
+     * @param[in]  input_class_score  The class prediction input tensor info. Data types supported: F32, QASYMM8.
+     * @param[in]  input_anchors      The anchors input tensor. Data types supported: F32, QASYMM8.
+     * @param[out] output_boxes       The output tensor. Data types supported: F32.
+     * @param[out] output_classes     The output tensor. Data types supported: Same as @p output_boxes.
+     * @param[out] output_scores      The output tensor. Data types supported: Same as @p output_boxes.
+     * @param[out] num_detection      The number of output detection. Data types supported: Same as @p output_boxes.
+     * @param[in]  info               (Optional) DetectionPostProcessLayerInfo information.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input_box_encoding, const ITensorInfo *input_class_score, const ITensorInfo *input_anchors,
+                           ITensorInfo *output_boxes, ITensorInfo *output_classes, ITensorInfo *output_scores, ITensorInfo *num_detection,
+                           DetectionPostProcessLayerInfo info = DetectionPostProcessLayerInfo());
+    // Inherited methods overridden:
+    void run() override;
+
+private:
+    MemoryGroup                   _memory_group;
+    CPPNonMaximumSuppression      _nms;
+    const ITensor                *_input_box_encoding;
+    const ITensor                *_input_scores;
+    const ITensor                *_input_anchors;
+    ITensor                      *_output_boxes;
+    ITensor                      *_output_classes;
+    ITensor                      *_output_scores;
+    ITensor                      *_num_detection;
+    DetectionPostProcessLayerInfo _info;
+
+    const unsigned int _kBatchSize   = 1;
+    const unsigned int _kNumCoordBox = 4;
+    unsigned int       _num_boxes;
+    unsigned int       _num_classes_with_background;
+    unsigned int       _num_max_detected_boxes;
+
+    Tensor         _decoded_boxes;
+    Tensor         _decoded_scores;
+    Tensor         _selected_indices;
+    Tensor         _class_scores;
+    const ITensor *_input_scores_to_use;
+
+    // Intermediate results
+    std::vector<int>          _result_idx_boxes_after_nms;
+    std::vector<int>          _result_classes_after_nms;
+    std::vector<float>        _result_scores_after_nms;
+    std::vector<unsigned int> _sorted_indices;
+
+    // Temporary values
+    std::vector<float> _box_scores;
+};
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_CPP_DETECTION_POSTPROCESS_H__ */