38 float* detectionBoxes = GetOutputTensorData<float>(0,
m_Data);
39 float* detectionClasses = GetOutputTensorData<float>(1,
m_Data);
40 float* detectionScores = GetOutputTensorData<float>(2,
m_Data);
41 float* numDetections = GetOutputTensorData<float>(3,
m_Data);
44 detectionBoxesInfo, detectionClassesInfo,
47 detectionClasses, detectionScores, numDetections);
CPU Execution: Reference C++ kernels.
virtual void Execute() const override
const DetectionPostProcessQueueDescriptor m_Data
armnn::TensorInfo anchorsInfo({ 6, 4 }, armnn::DataType::Float32)
const TensorInfo & GetTensorInfo(const ITensorHandle *tensorHandle)
float32 helpers
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) 2020 ARM Limited.
RefDetectionPostProcessWorkload(const DetectionPostProcessQueueDescriptor &descriptor, const WorkloadInfo &info)
LayerDescriptor m_Parameters
#define ARMNN_SCOPED_PROFILING_EVENT(backendId, name)
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
armnn::TensorInfo scoresInfo({ 1, 6, 3 }, armnn::DataType::Float32)
Contains information about inputs and outputs to a layer.
std::vector< ITensorHandle * > m_Inputs
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 })