COMPMID-1808: Add Detection Output Layer to the GraphAPI
COMPMID-1710: Integrate Detection ouput in MobilenetSSD graph example
Change-Id: I384d1eb492ef14ece58f2023ad7bbc16f834450b
Reviewed-on: https://review.mlplatform.org/356
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez <pablo.tello@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/arm_compute/graph/GraphBuilder.h b/arm_compute/graph/GraphBuilder.h
index 33a13f1..cb905e7 100644
--- a/arm_compute/graph/GraphBuilder.h
+++ b/arm_compute/graph/GraphBuilder.h
@@ -201,6 +201,18 @@
* @return Node ID of the created node, EmptyNodeID in case of error
*/
static NodeID add_elementwise_node(Graph &g, NodeParams params, NodeIdxPair input0, NodeIdxPair input1, EltwiseOperation operation);
+ /** Adds a detection output layer node to the graph
+ *
+ * @param[in] g Graph to add the node to
+ * @param[in] params Common node parameters
+ * @param[in] input_loc Location input to the detection output layer node as a NodeID-Index pair
+ * @param[in] input_conf Confidence input to the detection output layer node as a NodeID-Index pair
+ * @param[in] input_priorbox PriorBox input to the detection output layer node as a NodeID-Index pair
+ * @param[in] detect_info Detection output layer parameters
+ *
+ * @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, DetectionOutputLayerInfo detect_info);
/** 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 2df2574..573d642 100644
--- a/arm_compute/graph/INodeVisitor.h
+++ b/arm_compute/graph/INodeVisitor.h
@@ -71,6 +71,11 @@
* @param[in] n Node to visit.
*/
virtual void visit(DepthwiseConvolutionLayerNode &n) = 0;
+ /** Visit DetectionOutputLayerNode.
+ *
+ * @param[in] n Node to visit.
+ */
+ virtual void visit(DetectionOutputLayerNode &n) = 0;
/** Visit EltwiseLayerNode.
*
* @param[in] n Node to visit.
@@ -170,6 +175,10 @@
{
default_visit();
}
+ virtual void visit(DetectionOutputLayerNode &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 d633091..e33c984 100644
--- a/arm_compute/graph/TypePrinter.h
+++ b/arm_compute/graph/TypePrinter.h
@@ -83,6 +83,9 @@
case NodeType::DeconvolutionLayer:
os << "DeconvolutionLayer";
break;
+ case NodeType::DetectionOutputLayer:
+ os << "DetectionOutputLayer";
+ break;
case NodeType::DepthwiseConvolutionLayer:
os << "DepthwiseConvolutionLayer";
break;
diff --git a/arm_compute/graph/Types.h b/arm_compute/graph/Types.h
index b6803c8..60fe0a8 100644
--- a/arm_compute/graph/Types.h
+++ b/arm_compute/graph/Types.h
@@ -45,6 +45,7 @@
using arm_compute::PermutationVector;
using arm_compute::ActivationLayerInfo;
+using arm_compute::DetectionOutputLayerInfo;
using arm_compute::NormType;
using arm_compute::NormalizationLayerInfo;
using arm_compute::FullyConnectedLayerInfo;
@@ -133,6 +134,7 @@
ConvolutionLayer,
DeconvolutionLayer,
DepthwiseConvolutionLayer,
+ DetectionOutputLayer,
EltwiseLayer,
FlattenLayer,
FullyConnectedLayer,
diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h
index 3e71e39..96adffe 100644
--- a/arm_compute/graph/backends/FunctionHelpers.h
+++ b/arm_compute/graph/backends/FunctionHelpers.h
@@ -489,6 +489,51 @@
return func;
}
+/** Create a backend detection output layer function
+ *
+ * @tparam DetectionOutputLayer Function Backend detection output function
+ * @tparam TargetInfo Target-specific information
+ *
+ * @param[in] node Node to create the backend function for
+ *
+ * @return Backend detection output layer function
+ */
+template <typename DetectionOutputLayerFunction, typename TargetInfo>
+std::unique_ptr<IFunction> create_detection_output_layer(DetectionOutputLayerNode &node)
+{
+ validate_node<TargetInfo>(node, 3 /* expected inputs */, 1 /* 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 *output = get_backing_tensor<TargetInfo>(node.output(0));
+ const DetectionOutputLayerInfo detect_info = node.detection_output_info();
+
+ ARM_COMPUTE_ERROR_ON(input0 == nullptr);
+ ARM_COMPUTE_ERROR_ON(input1 == nullptr);
+ ARM_COMPUTE_ERROR_ON(input2 == nullptr);
+ ARM_COMPUTE_ERROR_ON(output == nullptr);
+
+ // Create and configure function
+ auto func = support::cpp14::make_unique<DetectionOutputLayerFunction>();
+ func->configure(input0, input1, input2, output, 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()
+ << " Output shape: " << output->info()->tensor_shape()
+ << " DetectionOutputLayer 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 75e2363..f1e5361 100644
--- a/arm_compute/graph/backends/ValidateHelpers.h
+++ b/arm_compute/graph/backends/ValidateHelpers.h
@@ -203,6 +203,30 @@
return status;
}
+/** Validates a detection output layer node
+ *
+ * @tparam DetectionOutputLayer DetectionOutput layer type
+ *
+ * @param[in] node Node to validate
+ *
+ * @return Status
+ */
+template <typename DetectionOutputLayer>
+Status validate_detection_output_layer(DetectionOutputLayerNode &node)
+{
+ ARM_COMPUTE_LOG_GRAPH_VERBOSE("Validating DetectionOutputLayer 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() != 1);
+
+ // 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 *output = get_backing_tensor_info(node.output(0));
+ const DetectionOutputLayerInfo detect_info = node.detection_output_info();
+
+ return DetectionOutputLayer::validate(input0, input1, input2, output, 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 d070331..72353a2 100644
--- a/arm_compute/graph/frontend/Layers.h
+++ b/arm_compute/graph/frontend/Layers.h
@@ -458,7 +458,35 @@
int _depth_multiplier;
const QuantizationInfo _quant_info;
};
+/** DetectionOutput Layer */
+class DetectionOutputLayer final : public ILayer
+{
+public:
+ /** Construct a detection output layer.
+ *
+ * @param[in] sub_stream_conf Confidence graph sub-stream.
+ * @param[in] sub_stream_prior PriorBox graph sub-stream.
+ * @param[in] detect_info DetectionOutput parameters.
+ */
+ DetectionOutputLayer(SubStream &&sub_stream_conf, SubStream &&sub_stream_prior, DetectionOutputLayerInfo detect_info)
+ : _ss_conf(std::move(sub_stream_conf)), _ss_prior(std::move(sub_stream_prior)), _detect_info(detect_info)
+ {
+ }
+ NodeID create_layer(IStream &s) override
+ {
+ NodeParams common_params = { name(), s.hints().target_hint };
+ NodeIdxPair input_loc = { s.tail_node(), 0 };
+ NodeIdxPair input_conf = { _ss_conf.tail_node(), 0 };
+ NodeIdxPair input_priorbox = { _ss_prior.tail_node(), 0 };
+ return GraphBuilder::add_detection_output_node(s.graph(), common_params, input_loc, input_conf, input_priorbox, _detect_info);
+ }
+
+private:
+ SubStream _ss_conf;
+ SubStream _ss_prior;
+ DetectionOutputLayerInfo _detect_info;
+};
/** Dummy Layer */
class DummyLayer final : public ILayer
{
diff --git a/arm_compute/graph/nodes/DetectionOutputLayerNode.h b/arm_compute/graph/nodes/DetectionOutputLayerNode.h
new file mode 100644
index 0000000..da1b051
--- /dev/null
+++ b/arm_compute/graph/nodes/DetectionOutputLayerNode.h
@@ -0,0 +1,70 @@
+/*
+ * Copyright (c) 2018 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_OUTPUT_LAYER_NODE_H__
+#define __ARM_COMPUTE_GRAPH_DETECTION_OUTPUT_LAYER_NODE_H__
+
+#include "arm_compute/graph/INode.h"
+
+namespace arm_compute
+{
+namespace graph
+{
+/** DetectionOutput Layer node */
+class DetectionOutputLayerNode final : public INode
+{
+public:
+ /** Constructor
+ *
+ * @param[in] detection_info DetectionOutput Layer information
+ */
+ DetectionOutputLayerNode(DetectionOutputLayerInfo detection_info);
+ /** DetectionOutput metadata accessor
+ *
+ * @return DetectionOutput Layer info
+ */
+ DetectionOutputLayerInfo detection_output_info() const;
+ /** Computes detection output output descriptor
+ *
+ * @param[in] input_descriptor Input descriptor
+ * @param[in] info DetectionOutput operation attributes
+ *
+ * @return Output descriptor
+ */
+ static TensorDescriptor compute_output_descriptor(const TensorDescriptor &input_descriptor, const DetectionOutputLayerInfo &info);
+
+ // 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:
+ DetectionOutputLayerInfo _info;
+
+ // Each detection contains a bounding box, given by its coordinates xmin, ymin, xmax, ymax, associated at the respective image, label and a confidence
+ static const int detection_size = 7;
+};
+} // namespace graph
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_GRAPH_DETECTION_OUTPUT_LAYER_NODE_H__ */
diff --git a/arm_compute/graph/nodes/Nodes.h b/arm_compute/graph/nodes/Nodes.h
index 5c7599f..c85c4dc 100644
--- a/arm_compute/graph/nodes/Nodes.h
+++ b/arm_compute/graph/nodes/Nodes.h
@@ -33,6 +33,7 @@
#include "arm_compute/graph/nodes/ConvolutionLayerNode.h"
#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/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 f956b54..542c129 100644
--- a/arm_compute/graph/nodes/NodesFwd.h
+++ b/arm_compute/graph/nodes/NodesFwd.h
@@ -39,6 +39,7 @@
class ConvolutionLayerNode;
class DeconvolutionLayerNode;
class DepthwiseConvolutionLayerNode;
+class DetectionOutputLayerNode;
class DummyNode;
class EltwiseLayerNode;
class FlattenLayerNode;
diff --git a/examples/graph_ssd_mobilenet.cpp b/examples/graph_ssd_mobilenet.cpp
index 95a4dcc..676c5e9 100644
--- a/examples/graph_ssd_mobilenet.cpp
+++ b/examples/graph_ssd_mobilenet.cpp
@@ -39,12 +39,9 @@
GraphSSDMobilenetExample()
: cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "MobileNetSSD")
{
- mbox_loc_opt = cmd_parser.add_option<SimpleOption<std::string>>("mbox_loc_opt", "");
- mbox_loc_opt->set_help("Filename containing the reference values for the graph branch mbox_loc_opt.");
- mbox_conf_flatten_opt = cmd_parser.add_option<SimpleOption<std::string>>("mbox_conf_flatten", "");
- mbox_conf_flatten_opt->set_help("Filename containing the reference values for the graph branch mbox_conf_flatten.");
- mbox_priorbox_opt = cmd_parser.add_option<SimpleOption<std::string>>("mbox_priorbox", "");
- mbox_priorbox_opt->set_help("Filename containing the reference values for the graph branch mbox_priorbox.");
+ // Add topk option
+ keep_topk_opt = cmd_parser.add_option<SimpleOption<int>>("topk", 100);
+ keep_topk_opt->set_help("Top k detections results per image.");
}
GraphSSDMobilenetExample(const GraphSSDMobilenetExample &) = delete;
GraphSSDMobilenetExample &operator=(const GraphSSDMobilenetExample &) = delete;
@@ -162,8 +159,6 @@
mbox_loc << ConcatLayer(std::move(conv_11_mbox_loc), std::move(conv_13_mbox_loc), conv_14_2_mbox_loc, std::move(conv_15_2_mbox_loc),
std::move(conv_16_2_mbox_loc), std::move(conv_17_2_mbox_loc));
- mbox_loc << OutputLayer(get_npy_output_accessor(mbox_loc_opt->value(), TensorShape(7668U), DataType::F32));
-
//mbox_conf
SubStream conv_11_mbox_conf(conv_11);
conv_11_mbox_conf << get_node_C(conv_11, data_path, "conv11_mbox_conf", 63, PadStrideInfo(1, 1, 0, 0));
@@ -190,8 +185,6 @@
mbox_conf << SoftmaxLayer().set_name("mbox_conf/softmax");
mbox_conf << FlattenLayer().set_name("mbox_conf/flat");
- mbox_conf << OutputLayer(get_npy_output_accessor(mbox_conf_flatten_opt->value(), TensorShape(40257U), DataType::F32));
-
const std::vector<float> priorbox_variances = { 0.1f, 0.1f, 0.2f, 0.2f };
const float priorbox_offset = 0.5f;
const std::vector<float> priorbox_aspect_ratios = { 2.f, 3.f };
@@ -235,7 +228,19 @@
std::move(conv_11_mbox_priorbox), std::move(conv_13_mbox_priorbox), std::move(conv_14_2_mbox_priorbox),
std::move(conv_15_2_mbox_priorbox), std::move(conv_16_2_mbox_priorbox), std::move(conv_17_2_mbox_priorbox));
- mbox_priorbox << OutputLayer(get_npy_output_accessor(mbox_priorbox_opt->value(), TensorShape(7668U, 2U, 1U), DataType::F32));
+ const int num_classes = 21;
+ const bool share_location = true;
+ const DetectionOutputLayerCodeType detection_type = DetectionOutputLayerCodeType::CENTER_SIZE;
+ const int keep_top_k = keep_topk_opt->value();
+ const float nms_threshold = 0.45f;
+ const int label_id_background = 0;
+ const float conf_thrs = 0.25f;
+ const int top_k = 100;
+
+ SubStream detection_ouput(mbox_loc);
+ detection_ouput << DetectionOutputLayer(std::move(mbox_conf), std::move(mbox_priorbox),
+ DetectionOutputLayerInfo(num_classes, share_location, detection_type, keep_top_k, nms_threshold, top_k, label_id_background, conf_thrs));
+ detection_ouput << OutputLayer(get_detection_output_accessor(common_params, { tensor_shape }));
// Finalize graph
GraphConfig config;
@@ -256,13 +261,9 @@
private:
CommandLineParser cmd_parser;
CommonGraphOptions common_opts;
-
- SimpleOption<std::string> *mbox_loc_opt{ nullptr };
- SimpleOption<std::string> *mbox_conf_flatten_opt{ nullptr };
- SimpleOption<std::string> *mbox_priorbox_opt{ nullptr };
-
- CommonGraphParams common_params;
- Stream graph;
+ SimpleOption<int> *keep_topk_opt{ nullptr };
+ CommonGraphParams common_params;
+ Stream graph;
ConcatLayer get_node_A(IStream &master_graph, const std::string &data_path, std::string &¶m_path,
unsigned int conv_filt,
diff --git a/src/graph/GraphBuilder.cpp b/src/graph/GraphBuilder.cpp
index 3fc258d..d09002d 100644
--- a/src/graph/GraphBuilder.cpp
+++ b/src/graph/GraphBuilder.cpp
@@ -362,6 +362,22 @@
return conv_nid;
}
+NodeID GraphBuilder::add_detection_output_node(Graph &g, NodeParams params, NodeIdxPair input_loc, NodeIdxPair input_conf, NodeIdxPair input_priorbox, DetectionOutputLayerInfo detect_info)
+{
+ CHECK_NODEIDX_PAIR(input_loc, g);
+ CHECK_NODEIDX_PAIR(input_conf, g);
+ CHECK_NODEIDX_PAIR(input_priorbox, g);
+
+ // Create detection_output node and connect
+ NodeID detect_nid = g.add_node<DetectionOutputLayerNode>(detect_info);
+ g.add_connection(input_loc.node_id, input_loc.index, detect_nid, 0);
+ g.add_connection(input_conf.node_id, input_conf.index, detect_nid, 1);
+ g.add_connection(input_priorbox.node_id, input_priorbox.index, detect_nid, 2);
+
+ set_node_params(g, detect_nid, params);
+
+ return detect_nid;
+}
NodeID GraphBuilder::add_dummy_node(Graph &g, NodeParams params, NodeIdxPair input, TensorShape shape)
{
diff --git a/src/graph/backends/CL/CLFunctionsFactory.cpp b/src/graph/backends/CL/CLFunctionsFactory.cpp
index c37a137..5b329c0 100644
--- a/src/graph/backends/CL/CLFunctionsFactory.cpp
+++ b/src/graph/backends/CL/CLFunctionsFactory.cpp
@@ -27,6 +27,7 @@
#include "arm_compute/graph/Graph.h"
#include "arm_compute/graph/backends/FunctionHelpers.h"
#include "arm_compute/runtime/CL/CLFunctions.h"
+#include "arm_compute/runtime/CPP/CPPFunctions.h"
using namespace arm_compute::utils::cast;
@@ -68,6 +69,94 @@
using Subtraction = CLArithmeticSubtraction;
using Multiplication = CLPixelWiseMultiplication;
};
+// TODO (isagot01): Remove once we support heterogeneous scheduling at function level
+/** Wrapper for the CPP Function in the OpenCL backend **/
+class CPPWrapperFunction : public IFunction
+{
+public:
+ /* Default constructor */
+ CPPWrapperFunction()
+ : _tensors(), _func(nullptr)
+ {
+ }
+
+ void run() override
+ {
+ for(auto &tensor : _tensors)
+ {
+ tensor->map(CLScheduler::get().queue());
+ }
+ _func->run();
+
+ for(auto &tensor : _tensors)
+ {
+ tensor->unmap(CLScheduler::get().queue());
+ }
+ }
+
+ void register_tensor(ICLTensor *tensor)
+ {
+ _tensors.push_back(tensor);
+ }
+
+ void register_function(std::unique_ptr<IFunction> function)
+ {
+ _func = std::move(function);
+ }
+
+private:
+ std::vector<arm_compute::ICLTensor *> _tensors;
+ std::unique_ptr<IFunction> _func;
+};
+
+namespace detail
+{
+// Specialized functions
+template <>
+std::unique_ptr<IFunction> create_detection_output_layer<CPPDetectionOutputLayer, CLTargetInfo>(DetectionOutputLayerNode &node)
+{
+ validate_node<CLTargetInfo>(node, 3 /* expected inputs */, 1 /* expected outputs */);
+
+ // Extract IO and info
+ CLTargetInfo::TensorType *input0 = get_backing_tensor<CLTargetInfo>(node.input(0));
+ CLTargetInfo::TensorType *input1 = get_backing_tensor<CLTargetInfo>(node.input(1));
+ CLTargetInfo::TensorType *input2 = get_backing_tensor<CLTargetInfo>(node.input(2));
+ CLTargetInfo::TensorType *output = get_backing_tensor<CLTargetInfo>(node.output(0));
+ const DetectionOutputLayerInfo detect_info = node.detection_output_info();
+
+ ARM_COMPUTE_ERROR_ON(input0 == nullptr);
+ ARM_COMPUTE_ERROR_ON(input1 == nullptr);
+ ARM_COMPUTE_ERROR_ON(input2 == nullptr);
+ ARM_COMPUTE_ERROR_ON(output == nullptr);
+
+ // Create and configure function
+ auto func = support::cpp14::make_unique<CPPDetectionOutputLayer>();
+ func->configure(input0, input1, input2, output, detect_info);
+
+ // Log info
+ ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated "
+ << node.name()
+ << " Type: " << node.type()
+ << " Target: " << CLTargetInfo::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()
+ << " Output shape: " << output->info()->tensor_shape()
+ << " DetectionOutputLayer info: " << detect_info
+ << std::endl);
+
+ auto wrap_function = support::cpp14::make_unique<CPPWrapperFunction>();
+ ;
+ wrap_function->register_function(std::move(func));
+ wrap_function->register_tensor(input0);
+ wrap_function->register_tensor(input1);
+ wrap_function->register_tensor(input2);
+ wrap_function->register_tensor(output);
+
+ return std::move(wrap_function);
+}
+} // namespace detail
std::unique_ptr<IFunction> CLFunctionFactory::create(INode *node, GraphContext &ctx)
{
@@ -95,6 +184,8 @@
return detail::create_concatenate_layer<CLConcatenateLayer, CLTargetInfo>(*polymorphic_downcast<ConcatenateLayerNode *>(node));
case NodeType::DepthwiseConvolutionLayer:
return detail::create_depthwise_convolution_layer<CLDepthwiseConvolutionLayerFunctions, CLTargetInfo>(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node));
+ case NodeType::DetectionOutputLayer:
+ return detail::create_detection_output_layer<CPPDetectionOutputLayer, CLTargetInfo>(*polymorphic_downcast<DetectionOutputLayerNode *>(node));
case NodeType::EltwiseLayer:
return detail::create_eltwise_layer<CLEltwiseFunctions, CLTargetInfo>(*polymorphic_downcast<EltwiseLayerNode *>(node));
case NodeType::FlattenLayer:
diff --git a/src/graph/backends/CL/CLNodeValidator.cpp b/src/graph/backends/CL/CLNodeValidator.cpp
index a070973..85ac1f5 100644
--- a/src/graph/backends/CL/CLNodeValidator.cpp
+++ b/src/graph/backends/CL/CLNodeValidator.cpp
@@ -28,6 +28,7 @@
#include "arm_compute/core/utils/misc/Cast.h"
#include "arm_compute/runtime/CL/CLFunctions.h"
+#include "arm_compute/runtime/CPP/CPPFunctions.h"
using namespace arm_compute::utils::cast;
@@ -59,6 +60,8 @@
case NodeType::DepthwiseConvolutionLayer:
return detail::validate_depthwise_convolution_layer<CLDepthwiseConvolutionLayer,
CLDepthwiseConvolutionLayer3x3>(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node));
+ case NodeType::DetectionOutputLayer:
+ return detail::validate_detection_output_layer<CPPDetectionOutputLayer>(*polymorphic_downcast<DetectionOutputLayerNode *>(node));
case NodeType::GenerateProposalsLayer:
return detail::validate_generate_proposals_layer<CLGenerateProposalsLayer>(*polymorphic_downcast<GenerateProposalsLayerNode *>(node));
case NodeType::NormalizePlanarYUVLayer:
diff --git a/src/graph/backends/GLES/GCNodeValidator.cpp b/src/graph/backends/GLES/GCNodeValidator.cpp
index fe69c7a..95bb44f 100644
--- a/src/graph/backends/GLES/GCNodeValidator.cpp
+++ b/src/graph/backends/GLES/GCNodeValidator.cpp
@@ -111,6 +111,8 @@
return validate_convolution_layer(*polymorphic_downcast<ConvolutionLayerNode *>(node));
case NodeType::DepthwiseConvolutionLayer:
return validate_depthwise_convolution_layer(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node));
+ case NodeType::DetectionOutputLayer:
+ return ARM_COMPUTE_CREATE_ERROR(arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported operation : DetectionOutputLayer");
case NodeType::FlattenLayer:
return ARM_COMPUTE_CREATE_ERROR(arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported operation : FlattenLayer");
case NodeType::GenerateProposalsLayer:
diff --git a/src/graph/backends/NEON/NEFunctionFactory.cpp b/src/graph/backends/NEON/NEFunctionFactory.cpp
index ca8d485..dc987dd 100644
--- a/src/graph/backends/NEON/NEFunctionFactory.cpp
+++ b/src/graph/backends/NEON/NEFunctionFactory.cpp
@@ -31,6 +31,7 @@
#include "arm_compute/graph/backends/FunctionHelpers.h"
#include "arm_compute/graph/backends/Utils.h"
#include "arm_compute/graph/nodes/Nodes.h"
+#include "arm_compute/runtime/CPP/CPPFunctions.h"
#include "arm_compute/runtime/NEON/NEFunctions.h"
#include "support/ToolchainSupport.h"
@@ -77,7 +78,7 @@
namespace detail
{
-// Specialize functions
+// Specialized functions
template <>
std::unique_ptr<IFunction> create_convolution_layer<NEConvolutionLayerFunctions, NETargetInfo>(ConvolutionLayerNode &node,
GraphContext &ctx)
@@ -201,6 +202,8 @@
return detail::create_concatenate_layer<NEConcatenateLayer, NETargetInfo>(*polymorphic_downcast<ConcatenateLayerNode *>(node));
case NodeType::DepthwiseConvolutionLayer:
return detail::create_depthwise_convolution_layer<NEDepthwiseConvolutionLayerFunctions, NETargetInfo>(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node));
+ case NodeType::DetectionOutputLayer:
+ return detail::create_detection_output_layer<CPPDetectionOutputLayer, NETargetInfo>(*polymorphic_downcast<DetectionOutputLayerNode *>(node));
case NodeType::EltwiseLayer:
return detail::create_eltwise_layer<NEEltwiseFunctions, NETargetInfo>(*polymorphic_downcast<EltwiseLayerNode *>(node));
case NodeType::FlattenLayer:
diff --git a/src/graph/backends/NEON/NENodeValidator.cpp b/src/graph/backends/NEON/NENodeValidator.cpp
index a2abc83..db6af5e 100644
--- a/src/graph/backends/NEON/NENodeValidator.cpp
+++ b/src/graph/backends/NEON/NENodeValidator.cpp
@@ -27,6 +27,7 @@
#include "arm_compute/graph/nodes/Nodes.h"
#include "arm_compute/core/utils/misc/Cast.h"
+#include "arm_compute/runtime/CPP/CPPFunctions.h"
#include "arm_compute/runtime/NEON/NEFunctions.h"
using namespace arm_compute::utils::cast;
@@ -59,6 +60,8 @@
case NodeType::DepthwiseConvolutionLayer:
return detail::validate_depthwise_convolution_layer<NEDepthwiseConvolutionLayer,
NEDepthwiseConvolutionLayer3x3>(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node));
+ case NodeType::DetectionOutputLayer:
+ return detail::validate_detection_output_layer<CPPDetectionOutputLayer>(*polymorphic_downcast<DetectionOutputLayerNode *>(node));
case NodeType::GenerateProposalsLayer:
return ARM_COMPUTE_CREATE_ERROR(arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported operation : GenerateProposalsLayer");
case NodeType::NormalizePlanarYUVLayer:
diff --git a/src/graph/nodes/DetectionOutputLayerNode.cpp b/src/graph/nodes/DetectionOutputLayerNode.cpp
new file mode 100644
index 0000000..c2d9f24
--- /dev/null
+++ b/src/graph/nodes/DetectionOutputLayerNode.cpp
@@ -0,0 +1,92 @@
+/*
+ * Copyright (c) 2018 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.
+ */
+#include "arm_compute/graph/nodes/DetectionOutputLayerNode.h"
+
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/graph/Graph.h"
+#include "arm_compute/graph/INodeVisitor.h"
+#include "arm_compute/graph/Utils.h"
+
+namespace arm_compute
+{
+namespace graph
+{
+DetectionOutputLayerNode::DetectionOutputLayerNode(DetectionOutputLayerInfo detection_info)
+ : _info(detection_info)
+{
+ _input_edges.resize(3, EmptyEdgeID);
+ _outputs.resize(1, NullTensorID);
+}
+
+DetectionOutputLayerInfo DetectionOutputLayerNode::detection_output_info() const
+{
+ return _info;
+}
+
+TensorDescriptor DetectionOutputLayerNode::compute_output_descriptor(const TensorDescriptor &input_descriptor,
+ const DetectionOutputLayerInfo &info)
+{
+ const unsigned int max_size = info.keep_top_k() * ((input_descriptor.shape.num_dimensions() > 1) ? input_descriptor.shape[1] : 1);
+
+ TensorDescriptor output_descriptor = input_descriptor;
+ output_descriptor.shape.set(0, detection_size);
+ output_descriptor.shape.set(1, max_size);
+
+ return output_descriptor;
+}
+
+bool DetectionOutputLayerNode::forward_descriptors()
+{
+ if((input_id(0) != NullTensorID) && (input_id(1) != NullTensorID) && (input_id(2) != NullTensorID) && (output_id(0) != NullTensorID))
+ {
+ Tensor *dst = output(0);
+ ARM_COMPUTE_ERROR_ON(dst == nullptr);
+ dst->desc() = configure_output(0);
+ return true;
+ }
+ return false;
+}
+
+TensorDescriptor DetectionOutputLayerNode::configure_output(size_t idx) const
+{
+ ARM_COMPUTE_UNUSED(idx);
+ ARM_COMPUTE_ERROR_ON(idx >= _outputs.size());
+
+ const Tensor *input0 = input(0);
+ ARM_COMPUTE_ERROR_ON(input0 == nullptr);
+
+ return compute_output_descriptor(input0->desc(), _info);
+}
+
+NodeType DetectionOutputLayerNode::type() const
+{
+ return NodeType::DetectionOutputLayer;
+}
+
+void DetectionOutputLayerNode::accept(INodeVisitor &v)
+{
+ v.visit(*this);
+}
+} // namespace graph
+} // namespace arm_compute
diff --git a/utils/GraphUtils.cpp b/utils/GraphUtils.cpp
index 2f1df7a..ab2c753 100644
--- a/utils/GraphUtils.cpp
+++ b/utils/GraphUtils.cpp
@@ -420,6 +420,77 @@
_output_stream << "Accuracy : " << accuracy << std::endl;
}
+DetectionOutputAccessor::DetectionOutputAccessor(const std::string &labels_path, std::vector<TensorShape> &imgs_tensor_shapes, std::ostream &output_stream)
+ : _labels(), _tensor_shapes(std::move(imgs_tensor_shapes)), _output_stream(output_stream)
+{
+ _labels.clear();
+
+ std::ifstream ifs;
+
+ try
+ {
+ ifs.exceptions(std::ifstream::badbit);
+ ifs.open(labels_path, std::ios::in | std::ios::binary);
+
+ for(std::string line; !std::getline(ifs, line).fail();)
+ {
+ _labels.emplace_back(line);
+ }
+ }
+ catch(const std::ifstream::failure &e)
+ {
+ ARM_COMPUTE_ERROR("Accessing %s: %s", labels_path.c_str(), e.what());
+ }
+}
+
+template <typename T>
+void DetectionOutputAccessor::access_predictions_tensor(ITensor &tensor)
+{
+ const size_t num_detection = tensor.info()->valid_region().shape.y();
+ const auto output_prt = reinterpret_cast<T *>(tensor.buffer() + tensor.info()->offset_first_element_in_bytes());
+
+ if(num_detection > 0)
+ {
+ _output_stream << "---------------------- Detections ----------------------" << std::endl
+ << std::endl;
+
+ _output_stream << std::left << std::setprecision(4) << std::setw(8) << "Image | " << std::setw(8) << "Label | " << std::setw(12) << "Confidence | "
+ << "[ xmin, ymin, xmax, ymax ]" << std::endl;
+
+ for(size_t i = 0; i < num_detection; ++i)
+ {
+ auto im = static_cast<const int>(output_prt[i * 7]);
+ _output_stream << std::setw(8) << im << std::setw(8)
+ << _labels[output_prt[i * 7 + 1]] << std::setw(12) << output_prt[i * 7 + 2]
+ << " [" << (output_prt[i * 7 + 3] * _tensor_shapes[im].x())
+ << ", " << (output_prt[i * 7 + 4] * _tensor_shapes[im].y())
+ << ", " << (output_prt[i * 7 + 5] * _tensor_shapes[im].x())
+ << ", " << (output_prt[i * 7 + 6] * _tensor_shapes[im].y())
+ << "]" << std::endl;
+ }
+ }
+ else
+ {
+ _output_stream << "No detection found." << std::endl;
+ }
+}
+
+bool DetectionOutputAccessor::access_tensor(ITensor &tensor)
+{
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&tensor, 1, DataType::F32);
+
+ switch(tensor.info()->data_type())
+ {
+ case DataType::F32:
+ access_predictions_tensor<float>(tensor);
+ break;
+ default:
+ ARM_COMPUTE_ERROR("NOT SUPPORTED!");
+ }
+
+ return false;
+}
+
TopNPredictionsAccessor::TopNPredictionsAccessor(const std::string &labels_path, size_t top_n, std::ostream &output_stream)
: _labels(), _output_stream(output_stream), _top_n(top_n)
{
diff --git a/utils/GraphUtils.h b/utils/GraphUtils.h
index d7f24af..131378e 100644
--- a/utils/GraphUtils.h
+++ b/utils/GraphUtils.h
@@ -283,6 +283,36 @@
size_t _positive_samples_top5;
};
+/** Detection output accessor class */
+class DetectionOutputAccessor final : public graph::ITensorAccessor
+{
+public:
+ /** Constructor
+ *
+ * @param[in] labels_path Path to labels text file.
+ * @param[in] imgs_tensor_shapes Network input images tensor shapes.
+ * @param[out] output_stream (Optional) Output stream
+ */
+ DetectionOutputAccessor(const std::string &labels_path, std::vector<TensorShape> &imgs_tensor_shapes, std::ostream &output_stream = std::cout);
+ /** Allow instances of this class to be move constructed */
+ DetectionOutputAccessor(DetectionOutputAccessor &&) = default;
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ DetectionOutputAccessor(const DetectionOutputAccessor &) = delete;
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ DetectionOutputAccessor &operator=(const DetectionOutputAccessor &) = delete;
+
+ // Inherited methods overriden:
+ bool access_tensor(ITensor &tensor) override;
+
+private:
+ template <typename T>
+ void access_predictions_tensor(ITensor &tensor);
+
+ std::vector<std::string> _labels;
+ std::vector<TensorShape> _tensor_shapes;
+ std::ostream &_output_stream;
+};
+
/** Result accessor class */
class TopNPredictionsAccessor final : public graph::ITensorAccessor
{
@@ -472,6 +502,39 @@
return arm_compute::support::cpp14::make_unique<TopNPredictionsAccessor>(graph_parameters.labels, top_n, output_stream);
}
}
+/** Generates appropriate output accessor according to the specified graph parameters
+ *
+ * @note If the output accessor is requested to validate the graph then ValidationOutputAccessor is generated
+ * else if output_accessor_file is empty will generate a DummyAccessor else will generate a TopNPredictionsAccessor
+ *
+ * @param[in] graph_parameters Graph parameters
+ * @param[in] tensor_shapes Network input images tensor shapes.
+ * @param[in] is_validation (Optional) Validation flag (default = false)
+ * @param[out] output_stream (Optional) Output stream (default = std::cout)
+ *
+ * @return An appropriate tensor accessor
+ */
+inline std::unique_ptr<graph::ITensorAccessor> get_detection_output_accessor(const arm_compute::utils::CommonGraphParams &graph_parameters,
+ std::vector<TensorShape> tensor_shapes,
+ bool is_validation = false,
+ std::ostream &output_stream = std::cout)
+{
+ if(!graph_parameters.validation_file.empty())
+ {
+ return arm_compute::support::cpp14::make_unique<ValidationOutputAccessor>(graph_parameters.validation_file,
+ output_stream,
+ graph_parameters.validation_range_start,
+ graph_parameters.validation_range_end);
+ }
+ else if(graph_parameters.labels.empty())
+ {
+ return arm_compute::support::cpp14::make_unique<DummyAccessor>(0);
+ }
+ else
+ {
+ return arm_compute::support::cpp14::make_unique<DetectionOutputAccessor>(graph_parameters.labels, tensor_shapes, output_stream);
+ }
+}
/** Generates appropriate npy output accessor according to the specified npy_path
*
* @note If npy_path is empty will generate a DummyAccessor else will generate a NpyAccessor