32 std::vector<ITensorHandle*> outputs)
const 45 auto boxEncodings = MakeDecoder<float>(boxEncodingsInfo, inputs[0]->Map());
49 float* detectionBoxes =
reinterpret_cast<float*
>(outputs[0]->Map());
50 float* detectionClasses =
reinterpret_cast<float*
>(outputs[1]->Map());
51 float* detectionScores =
reinterpret_cast<float*
>(outputs[2]->Map());
52 float* numDetections =
reinterpret_cast<float*
>(outputs[3]->Map());
55 detectionBoxesInfo, detectionClassesInfo,
58 detectionClasses, detectionScores, numDetections);
CPU Execution: Reference C++ kernels.
void Execute() const override
armnn::TensorInfo anchorsInfo({ 6, 4 }, armnn::DataType::Float32)
void ExecuteAsync(WorkingMemDescriptor &workingMemDescriptor) override
std::vector< float > boxEncodings({ 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, -1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f })
Copyright (c) 2021 ARM Limited and Contributors.
RefDetectionPostProcessWorkload(const DetectionPostProcessQueueDescriptor &descriptor, const WorkloadInfo &info)
LayerDescriptor m_Parameters
#define ARMNN_SCOPED_PROFILING_EVENT(backendId, name)
std::vector< ITensorHandle * > m_Inputs
DetectionPostProcessQueueDescriptor m_Data
std::vector< float > scores({ 0.0f, 0.9f, 0.8f, 0.0f, 0.75f, 0.72f, 0.0f, 0.6f, 0.5f, 0.0f, 0.93f, 0.95f, 0.0f, 0.5f, 0.4f, 0.0f, 0.3f, 0.2f })
std::vector< ITensorHandle * > m_Outputs
std::vector< ITensorHandle * > m_Outputs
armnn::TensorInfo scoresInfo({ 1, 6, 3 }, armnn::DataType::Float32)
Contains information about inputs and outputs to a layer.
std::vector< ITensorHandle * > m_Inputs
const TensorInfo & GetTensorInfo(const ITensorHandle *tensorHandle)
float32 helpers
std::vector< float > anchors({ 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 10.5f, 1.0f, 1.0f, 0.5f, 10.5f, 1.0f, 1.0f, 0.5f, 100.5f, 1.0f, 1.0f })