diff --git a/include/otbTensorflowMultisourceModelBase.h b/include/otbTensorflowMultisourceModelBase.h
index e0c23846fd45110efe30704acde79c35060e5310..8f4440730946d947f83fb92d960e027485be5ec0 100644
--- a/include/otbTensorflowMultisourceModelBase.h
+++ b/include/otbTensorflowMultisourceModelBase.h
@@ -72,10 +72,10 @@ public:
typedef typename TInputImage::RegionType RegionType;
/** Typedefs for parameters */
- typedef std::pair<std::string, tensorflow::Tensor> DictType;
+ typedef std::pair<std::string, tensorflow::Tensor> DictElementType;
typedef std::vector<std::string> StringList;
typedef std::vector<SizeType> SizeListType;
- typedef std::vector<DictType> DictListType;
+ typedef std::vector<DictElementType> DictType;
typedef std::vector<tensorflow::DataType> DataTypeListType;
typedef std::vector<tensorflow::TensorShapeProto> TensorShapeProtoList;
typedef std::vector<tensorflow::Tensor> TensorListType;
@@ -87,27 +87,28 @@ public:
tensorflow::Session * GetSession() { return m_Session; }
/** Model parameters */
- void PushBackInputBundle(std::string placeholder, SizeType receptiveField, ImagePointerType image);
+ void PushBackInputTensorBundle(std::string name, SizeType receptiveField, ImagePointerType image);
+ void PushBackOuputTensorBundle(std::string name, SizeType expressionField);
-// /** Input placeholders names */
-// itkSetMacro(InputPlaceholdersNames, StringList);
- itkGetMacro(InputPlaceholdersNames, StringList);
-//
-// /** Receptive field */
-// itkSetMacro(InputFOVSizes, SizeListType);
- itkGetMacro(InputFOVSizes, SizeListType);
+ /** Input placeholders names */
+ itkSetMacro(InputPlaceholders, StringList);
+ itkGetMacro(InputPlaceholders, StringList);
+
+ /** Receptive field */
+ itkSetMacro(InputReceptiveFields, SizeListType);
+ itkGetMacro(InputReceptiveFields, SizeListType);
/** Output tensors names */
- itkSetMacro(OutputTensorsNames, StringList);
- itkGetMacro(OutputTensorsNames, StringList);
+ itkSetMacro(OutputTensors, StringList);
+ itkGetMacro(OutputTensors, StringList);
/** Expression field */
- itkSetMacro(OutputFOESizes, SizeListType);
- itkGetMacro(OutputFOESizes, SizeListType);
+ itkSetMacro(OutputExpressionFields, SizeListType);
+ itkGetMacro(OutputExpressionFields, SizeListType);
/** User placeholders */
- void SetUserPlaceholders(DictListType dict) { m_UserPlaceholders = dict; }
- DictListType GetUserPlaceholders() { return m_UserPlaceholders; }
+ void SetUserPlaceholders(DictType dict) { m_UserPlaceholders = dict; }
+ DictType GetUserPlaceholders() { return m_UserPlaceholders; }
/** Target nodes names */
itkSetMacro(TargetNodesNames, StringList);
@@ -125,9 +126,9 @@ protected:
TensorflowMultisourceModelBase();
virtual ~TensorflowMultisourceModelBase() {};
- virtual std::stringstream GenerateDebugReport(DictListType & inputs, TensorListType & outputs);
+ virtual std::stringstream GenerateDebugReport(DictType & inputs);
- virtual void RunSession(DictListType & inputs, TensorListType & outputs);
+ virtual void RunSession(DictType & inputs, TensorListType & outputs);
private:
TensorflowMultisourceModelBase(const Self&); //purposely not implemented
@@ -138,11 +139,11 @@ private:
tensorflow::Session * m_Session; // The tensorflow session
// Model parameters
- StringList m_InputPlaceholdersNames; // Input placeholders names
- SizeListType m_InputFOVSizes; // Input tensors field of view (FOV) sizes
- SizeListType m_OutputFOESizes; // Output tensors field of expression (FOE) sizes
- DictListType m_UserPlaceholders; // User placeholders
- StringList m_OutputTensorsNames; // User tensors
+ StringList m_InputPlaceholders; // Input placeholders names
+ SizeListType m_InputReceptiveFields; // Input receptive fields
+ StringList m_OutputTensors; // Output tensors names
+ SizeListType m_OutputExpressionFields; // Output expression fields
+ DictType m_UserPlaceholders; // User placeholders
StringList m_TargetNodesNames; // User target tensors
// Read-only
diff --git a/include/otbTensorflowMultisourceModelBase.hxx b/include/otbTensorflowMultisourceModelBase.hxx
index 07b2cf71d5afdab187b494d3573a44dcd74c07d3..938c903544d8d5eed0fddf6596f0224ae019ca1f 100644
--- a/include/otbTensorflowMultisourceModelBase.hxx
+++ b/include/otbTensorflowMultisourceModelBase.hxx
@@ -20,22 +20,23 @@ template <class TInputImage, class TOutputImage>
TensorflowMultisourceModelBase<TInputImage, TOutputImage>
::TensorflowMultisourceModelBase()
{
+ m_Session = nullptr;
}
template <class TInputImage, class TOutputImage>
void
TensorflowMultisourceModelBase<TInputImage, TOutputImage>
-::PushBackInputBundle(std::string placeholder, SizeType receptiveField, ImagePointerType image)
+::PushBackInputTensorBundle(std::string placeholder, SizeType receptiveField, ImagePointerType image)
{
Superclass::PushBackInput(image);
- m_InputFOVSizes.push_back(receptiveField);
- m_InputPlaceholdersNames.push_back(placeholder);
+ m_InputReceptiveFields.push_back(receptiveField);
+ m_InputPlaceholders.push_back(placeholder);
}
template <class TInputImage, class TOutputImage>
std::stringstream
TensorflowMultisourceModelBase<TInputImage, TOutputImage>
-::GenerateDebugReport(DictListType & inputs, TensorListType & outputs)
+::GenerateDebugReport(DictType & inputs)
{
// Create a debug report
std::stringstream debugReport;
@@ -69,7 +70,7 @@ TensorflowMultisourceModelBase<TInputImage, TOutputImage>
template <class TInputImage, class TOutputImage>
void
TensorflowMultisourceModelBase<TInputImage, TOutputImage>
-::RunSession(DictListType & inputs, TensorListType & outputs)
+::RunSession(DictType & inputs, TensorListType & outputs)
{
// Add the user's placeholders
@@ -82,11 +83,11 @@ TensorflowMultisourceModelBase<TInputImage, TOutputImage>
// The session will initialize the outputs
// Run the session, evaluating our output tensors from the graph
- auto status = this->GetSession()->Run(inputs, m_OutputTensorsNames, m_TargetNodesNames, &outputs);
+ auto status = this->GetSession()->Run(inputs, m_OutputTensors, m_TargetNodesNames, &outputs);
if (!status.ok()) {
// Create a debug report
- std::stringstream debugReport = GenerateDebugReport(inputs, outputs);
+ std::stringstream debugReport = GenerateDebugReport(inputs);
// Throw an exception with the report
itkExceptionMacro("Can't run the tensorflow session !\n" <<
@@ -108,11 +109,11 @@ TensorflowMultisourceModelBase<TInputImage, TOutputImage>
// - patches sizes
// - input image
const unsigned int nbInputs = this->GetNumberOfInputs();
- if (nbInputs != m_InputFOVSizes.size() || nbInputs != m_InputPlaceholdersNames.size())
+ if (nbInputs != m_InputReceptiveFields.size() || nbInputs != m_InputPlaceholders.size())
{
itkExceptionMacro("Number of input images is " << nbInputs <<
- " but the number of input patches size is " << m_InputFOVSizes.size() <<
- " and the number of input tensors names is " << m_InputPlaceholdersNames.size());
+ " but the number of input patches size is " << m_InputReceptiveFields.size() <<
+ " and the number of input tensors names is " << m_InputPlaceholders.size());
}
//////////////////////////////////////////////////////////////////////////////////////////
@@ -120,8 +121,8 @@ TensorflowMultisourceModelBase<TInputImage, TOutputImage>
//////////////////////////////////////////////////////////////////////////////////////////
// Get input and output tensors datatypes and shapes
- tf::GetTensorAttributes(m_Graph, m_InputPlaceholdersNames, m_InputTensorsShapes, m_InputTensorsDataTypes);
- tf::GetTensorAttributes(m_Graph, m_OutputTensorsNames, m_OutputTensorsShapes, m_OutputTensorsDataTypes);
+ tf::GetTensorAttributes(m_Graph, m_InputPlaceholders, m_InputTensorsShapes, m_InputTensorsDataTypes);
+ tf::GetTensorAttributes(m_Graph, m_OutputTensors, m_OutputTensorsShapes, m_OutputTensorsDataTypes);
}
diff --git a/include/otbTensorflowMultisourceModelFilter.h b/include/otbTensorflowMultisourceModelFilter.h
index 833294ada5c05bf469c509aa58ea69ca04cfd1d4..fdc799a5cd69f86a77bc396f3f159f4ffde101e5 100644
--- a/include/otbTensorflowMultisourceModelFilter.h
+++ b/include/otbTensorflowMultisourceModelFilter.h
@@ -30,27 +30,26 @@ namespace otb
*
* The filter takes N input images and feed the TensorFlow model to produce
* one output image of desired TF op results.
- * Names of input/output placeholders/tensors must be specified using the
- * SetInputPlaceholdersNames/SetOutputTensorNames.
+ * Names of input placeholders and output tensors must be specified using the
+ * SetPlaceholders() and SetTensors() methods.
*
- * Example: we have a tensorflow model which runs the input images "x1" and "x2"
+ * Example: we have a TensorFlow model which runs the input images "x1" and "x2"
* and produces the output image "y".
- * "x1" and "x2" are two TF placeholders, we set InputTensorNames={"x1","x2"}
- * "y1" corresponds to one TF op output, we set OutputTensorNames={"y1"}
+ * "x1" and "x2" are two TF placeholders, we set InputPlaceholder={"x1","x2"}
+ * "y1" corresponds to one TF op output, we set OutputTensors={"y1"}
*
* The reference grid for the output image is the same as the first input image.
* This grid can be scaled by setting the OutputSpacingScale value.
* This can be used to run models which downsize the output image spacing
- * (typically fully convolutional model with strides) or to produce the result
+ * (e.g. fully convolutional model with strides) or to produce the result
* of a patch-based network at regular intervals.
*
- * For each input, input field of view (FOV) must be set.
+ * For each input (resp. output), receptive field (resp. expression field) must be set.
* If the number of values in the output tensors (produced by the model) don't
- * fit with the output image region, exception will be thrown.
+ * fit with the output image region, an exception will be thrown.
*
- *
- * The tensorflow Graph is passed using the SetGraph() method
- * The tensorflow Session is passed using the SetSession() method
+ * The TensorFlow Graph is passed using the SetGraph() method
+ * The TensorFlow Session is passed using the SetSession() method
*
* \ingroup OTBTensorflow
*/
@@ -94,6 +93,7 @@ public:
typedef typename itk::ImageRegionConstIterator<TInputImage> InputConstIteratorType;
/* Typedefs for parameters */
+ typedef typename Superclass::DictElementType DictElementType;
typedef typename Superclass::DictType DictType;
typedef typename Superclass::StringList StringList;
typedef typename Superclass::SizeListType SizeListType;
@@ -101,8 +101,6 @@ public:
typedef typename Superclass::TensorListType TensorListType;
typedef std::vector<float> ScaleListType;
- itkSetMacro(OutputFOESize, SizeType);
- itkGetMacro(OutputFOESize, SizeType);
itkSetMacro(OutputGridSize, SizeType);
itkGetMacro(OutputGridSize, SizeType);
itkSetMacro(ForceOutputGridSize, bool);
@@ -132,7 +130,6 @@ private:
TensorflowMultisourceModelFilter(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
- SizeType m_OutputFOESize; // Output tensors field of expression (FOE) sizes
SizeType m_OutputGridSize; // Output grid size
bool m_ForceOutputGridSize; // Force output grid size
bool m_FullyConvolutional; // Convolution mode
diff --git a/include/otbTensorflowMultisourceModelFilter.hxx b/include/otbTensorflowMultisourceModelFilter.hxx
index c7a547e240b2ccc8e60a0ced3d5c734b501537bd..e5fa16b9b2947bc91bd7adf337a971473ea8a313 100644
--- a/include/otbTensorflowMultisourceModelFilter.hxx
+++ b/include/otbTensorflowMultisourceModelFilter.hxx
@@ -216,7 +216,7 @@ TensorflowMultisourceModelFilter<TInputImage, TOutputImage>
// Update output image extent
PointType currentInputImageExtentInf, currentInputImageExtentSup;
- ImageToExtent(currentImage, currentInputImageExtentInf, currentInputImageExtentSup, this->GetInputFOVSizes()[imageIndex]);
+ ImageToExtent(currentImage, currentInputImageExtentInf, currentInputImageExtentSup, this->GetInputReceptiveFields()[imageIndex]);
for(unsigned int dim = 0; dim<ImageType::ImageDimension; ++dim)
{
extentInf[dim] = vnl_math_max(currentInputImageExtentInf[dim], extentInf[dim]);
@@ -236,7 +236,7 @@ TensorflowMultisourceModelFilter<TInputImage, TOutputImage>
if (!m_ForceOutputGridSize)
{
// Default is the output field of expression
- m_OutputGridSize = m_OutputFOESize;
+ m_OutputGridSize = this->GetOutputExpressionFields().at(0);
}
// Resize the largestPossibleRegion to be a multiple of the grid size
@@ -315,9 +315,9 @@ TensorflowMultisourceModelFilter<TInputImage, TOutputImage>
}
// Compute the FOV-scale*FOE radius to pad
- SizeType toPad(this->GetInputFOVSizes().at(i));
- toPad[0] -= 1 + (m_OutputFOESize[0] - 1) * m_OutputSpacingScale;
- toPad[1] -= 1 + (m_OutputFOESize[1] - 1) * m_OutputSpacingScale;
+ SizeType toPad(this->GetInputReceptiveFields().at(i));
+ toPad[0] -= 1 + (this->GetOutputExpressionFields().at(0)[0] - 1) * m_OutputSpacingScale;
+ toPad[1] -= 1 + (this->GetOutputExpressionFields().at(0)[1] - 1) * m_OutputSpacingScale;
// Pad with radius
SmartPad(inRegion, toPad);
@@ -365,7 +365,7 @@ TensorflowMultisourceModelFilter<TInputImage, TOutputImage>
const unsigned int nInputs = this->GetNumberOfInputs();
// Create input tensors list
- DictListType inputs;
+ DictType inputs;
// Populate input tensors
for (unsigned int i = 0 ; i < nInputs ; i++)
@@ -374,7 +374,7 @@ TensorflowMultisourceModelFilter<TInputImage, TOutputImage>
const ImagePointerType inputPtr = const_cast<TInputImage*>(this->GetInput(i));
// Patch size of tensor #i
- const SizeType inputPatchSize = this->GetInputFOVSizes().at(i);
+ const SizeType inputPatchSize = this->GetInputReceptiveFields().at(i);
// Input image requested region
const RegionType reqRegion = inputPtr->GetRequestedRegion();
@@ -395,7 +395,7 @@ TensorflowMultisourceModelFilter<TInputImage, TOutputImage>
tf::RecopyImageRegionToTensorWithCast<TInputImage>(inputPtr, reqRegion, inputTensor, 0);
// Input #1 : the tensor of patches (aka the batch)
- DictType input1 = { this->GetInputPlaceholdersNames()[i], inputTensor };
+ DictElementType input1 = { this->GetInputPlaceholdersNames()[i], inputTensor };
inputs.push_back(input1);
}
else
@@ -429,7 +429,7 @@ TensorflowMultisourceModelFilter<TInputImage, TOutputImage>
}
// Input #1 : the tensor of patches (aka the batch)
- DictType input1 = { this->GetInputPlaceholdersNames()[i], inputTensor };
+ DictElementType input1 = { this->GetInputPlaceholdersNames()[i], inputTensor };
inputs.push_back(input1);
} // mode is not full convolutional
diff --git a/include/otbTensorflowMultisourceModelLearningBase.h b/include/otbTensorflowMultisourceModelLearningBase.h
new file mode 100644
index 0000000000000000000000000000000000000000..d6feb24e83ca08eabb1e2566337511b5df0bb614
--- /dev/null
+++ b/include/otbTensorflowMultisourceModelLearningBase.h
@@ -0,0 +1,112 @@
+/*=========================================================================
+
+ Copyright (c) Remi Cresson (IRSTEA). All rights reserved.
+
+
+ This software is distributed WITHOUT ANY WARRANTY; without even
+ the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
+ PURPOSE. See the above copyright notices for more information.
+
+=========================================================================*/
+#ifndef otbTensorflowMultisourceModelLearningBase_h
+#define otbTensorflowMultisourceModelLearningBase_h
+
+#include "itkProcessObject.h"
+#include "itkNumericTraits.h"
+#include "itkSimpleDataObjectDecorator.h"
+
+// Base
+#include "otbTensorflowMultisourceModelBase.h"
+
+// Shuffle
+#include <random>
+#include <algorithm>
+#include <iterator>
+
+namespace otb
+{
+
+/**
+ * \class TensorflowMultisourceModelLearningBase
+ * \brief This filter is the base class for learning filters.
+ *
+ * \ingroup OTBTensorflow
+ */
+template <class TInputImage>
+class ITK_EXPORT TensorflowMultisourceModelLearningBase :
+public TensorflowMultisourceModelBase<TInputImage>
+{
+public:
+
+ /** Standard class typedefs. */
+ typedef TensorflowMultisourceModelLearningBase Self;
+ typedef TensorflowMultisourceModelBase<TInputImage> Superclass;
+ typedef itk::SmartPointer<Self> Pointer;
+ typedef itk::SmartPointer<const Self> ConstPointer;
+
+ /** Run-time type information (and related methods). */
+ itkTypeMacro(TensorflowMultisourceModelLearningBase, TensorflowMultisourceModelBase);
+
+ /** Images typedefs */
+ typedef typename Superclass::ImageType ImageType;
+ typedef typename Superclass::ImagePointerType ImagePointerType;
+ typedef typename Superclass::RegionType RegionType;
+ typedef typename Superclass::SizeType SizeType;
+ typedef typename Superclass::IndexType IndexType;
+
+ /* Typedefs for parameters */
+ typedef typename Superclass::DictType DictType;
+ typedef typename Superclass::DictElementType DictElementType;
+ typedef typename Superclass::StringList StringList;
+ typedef typename Superclass::SizeListType SizeListType;
+ typedef typename Superclass::TensorListType TensorListType;
+
+ /* Typedefs for index */
+ typedef typename ImageType::IndexValueType IndexValueType;
+ typedef std::vector<IndexValueType> IndexListType;
+
+ // Batch size
+ itkSetMacro(BatchSize, IndexValueType);
+ itkGetMacro(BatchSize, IndexValueType);
+
+ // Use streaming
+ itkSetMacro(UseStreaming, bool);
+ itkGetMacro(UseStreaming, bool);
+
+ // Get number of samples
+ itkGetMacro(NumberOfSamples, IndexValueType);
+
+protected:
+ TensorflowMultisourceModelLearningBase();
+ virtual ~TensorflowMultisourceModelLearningBase() {};
+
+ virtual void GenerateOutputInformation(void);
+
+ virtual void GenerateInputRequestedRegion();
+
+ virtual void GenerateData();
+
+ virtual void PopulateInputTensors(TensorListType & inputs, const IndexValueType & sampleStart,
+ const IndexValueType & batchSize, const IndexListType & order = IndexListType());
+
+ virtual void ProcessBatch(TensorListType & inputs, const IndexValueType & sampleStart,
+ const IndexValueType & batchSize) = 0;
+
+private:
+ TensorflowMultisourceModelLearningBase(const Self&); //purposely not implemented
+ void operator=(const Self&); //purposely not implemented
+
+ unsigned int m_BatchSize; // Batch size
+ bool m_UseStreaming; // Use streaming on/off
+
+ // Read only
+ IndexValueType m_NumberOfSamples; // Number of samples
+
+}; // end class
+
+
+} // end namespace otb
+
+#include "otbTensorflowMultisourceModelLearningBase.hxx"
+
+#endif
diff --git a/include/otbTensorflowMultisourceModelLearningBase.hxx b/include/otbTensorflowMultisourceModelLearningBase.hxx
new file mode 100644
index 0000000000000000000000000000000000000000..9c913cd2d3d6230a0356bec742ae749f333949f8
--- /dev/null
+++ b/include/otbTensorflowMultisourceModelLearningBase.hxx
@@ -0,0 +1,211 @@
+/*=========================================================================
+
+ Copyright (c) Remi Cresson (IRSTEA). All rights reserved.
+
+
+ This software is distributed WITHOUT ANY WARRANTY; without even
+ the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
+ PURPOSE. See the above copyright notices for more information.
+
+=========================================================================*/
+#ifndef otbTensorflowMultisourceModelLearningBase_txx
+#define otbTensorflowMultisourceModelLearningBase_txx
+
+#include "otbTensorflowMultisourceModelLearningBase.h"
+
+namespace otb
+{
+
+template <class TInputImage>
+TensorflowMultisourceModelLearningBase<TInputImage>
+::TensorflowMultisourceModelLearningBase(): m_BatchSize(100),
+ m_NumberOfSamples(0), m_UseStreaming(false)
+ {
+ }
+
+
+template <class TInputImage>
+void
+TensorflowMultisourceModelLearningBase<TInputImage>
+::GenerateOutputInformation()
+ {
+ Superclass::GenerateOutputInformation();
+
+ ImageType * outputPtr = this->GetOutput();
+ RegionType nullRegion;
+ nullRegion.GetModifiableSize().Fill(1);
+ outputPtr->SetNumberOfComponentsPerPixel(1);
+ outputPtr->SetLargestPossibleRegion( nullRegion );
+
+ // Count the number of samples
+ m_NumberOfSamples = 0;
+ for (unsigned int i = 0 ; i < this->GetNumberOfInputs() ; i++)
+ {
+ // Input image pointer
+ ImagePointerType inputPtr = const_cast<ImageType*>(this->GetInput(i));
+
+ // Make sure input is available
+ if ( inputPtr.IsNull() )
+ {
+ itkExceptionMacro(<< "Input " << i << " is null!");
+ }
+
+ // Update input information
+ inputPtr->UpdateOutputInformation();
+
+ // Patch size of tensor #i
+ const SizeType inputPatchSize = this->GetInputReceptiveFields().at(i);
+
+ // Input image requested region
+ const RegionType reqRegion = inputPtr->GetLargestPossibleRegion();
+
+ // Check size X
+ if (inputPatchSize[0] != reqRegion.GetSize(0))
+ itkExceptionMacro("Patch size for input " << i
+ << " is " << inputPatchSize
+ << " but input patches image size is " << reqRegion.GetSize());
+
+ // Check size Y
+ if (reqRegion.GetSize(1) % inputPatchSize[1] != 0)
+ itkExceptionMacro("Input patches image must have a number of rows which is "
+ << "a multiple of the patch size Y! Patches image has " << reqRegion.GetSize(1)
+ << " rows but patch size Y is " << inputPatchSize[1] << " for input " << i);
+
+ // Get the batch size
+ const tensorflow::uint64 currNumberOfSamples = reqRegion.GetSize(1) / inputPatchSize[1];
+
+ // Check the consistency with other inputs
+ if (m_NumberOfSamples == 0)
+ {
+ m_NumberOfSamples = currNumberOfSamples;
+ }
+ else if (m_NumberOfSamples != currNumberOfSamples)
+ {
+ itkGenericExceptionMacro("Previous batch size is " << m_NumberOfSamples
+ << " but input " << i
+ << " has a batch size of " << currNumberOfSamples );
+ }
+ } // next input
+ }
+
+template <class TInputImage>
+void
+TensorflowMultisourceModelLearningBase<TInputImage>
+::GenerateInputRequestedRegion()
+ {
+ Superclass::GenerateInputRequestedRegion();
+
+ // For each image, set no image region
+ for(unsigned int i = 0; i < this->GetNumberOfInputs(); ++i)
+ {
+ RegionType nullRegion;
+ ImageType * inputImage = static_cast<ImageType * >( Superclass::ProcessObject::GetInput(i) );
+
+ // If the streaming is enabled, we don't read the full image
+ if (m_UseStreaming)
+ {
+ inputImage->SetRequestedRegion(nullRegion);
+ }
+ else
+ {
+ inputImage->SetRequestedRegion(inputImage->GetLargestPossibleRegion());
+ }
+ } // next image
+ }
+
+/**
+ *
+ */
+template <class TInputImage>
+void
+TensorflowMultisourceModelLearningBase<TInputImage>
+::GenerateData()
+ {
+
+ // Batches loop
+ const IndexValueType nBatches = vcl_ceil(m_NumberOfSamples / m_BatchSize);
+ const IndexValueType rest = m_NumberOfSamples % m_BatchSize;
+
+ itk::ProgressReporter progress(this, 0, nBatches);
+
+ for (IndexValueType batch = 0 ; batch < nBatches ; batch++)
+ {
+
+ // Create input tensors list
+ TensorListType inputs;
+
+ // Batch start and size
+ const IndexValueType sampleStart = batch * m_BatchSize;
+ IndexValueType batchSize = m_BatchSize;
+ if (rest != 0)
+ {
+ batchSize = rest;
+ }
+
+ // Process the batch
+ ProcessBatch(inputs, sampleStart, batchSize);
+
+ progress.CompletedPixel();
+ } // Next batch
+
+ }
+
+template <class TInputImage>
+void
+TensorflowMultisourceModelLearningBase<TInputImage>
+::PopulateInputTensors(TensorListType & inputs, const IndexValueType & sampleStart,
+ const IndexValueType & batchSize, const IndexListType & order)
+ {
+ const bool reorder = order.size();
+
+ // Populate input tensors
+ for (unsigned int i = 0 ; i < this->GetNumberOfInputs() ; i++)
+ {
+ // Input image pointer
+ ImagePointerType inputPtr = const_cast<ImageType*>(this->GetInput(i));
+
+ // Patch size of tensor #i
+ const SizeType inputPatchSize = this->GetInputReceptiveFields().at(i);
+
+ // Create the tensor for the batch
+ const tensorflow::int64 sz_n = batchSize;
+ const tensorflow::int64 sz_y = inputPatchSize[1];
+ const tensorflow::int64 sz_x = inputPatchSize[0];
+ const tensorflow::int64 sz_c = inputPtr->GetNumberOfComponentsPerPixel();
+ const tensorflow::TensorShape inputTensorShape({sz_n, sz_y, sz_x, sz_c});
+ tensorflow::Tensor inputTensor(this->GetInputTensorsDataTypes()[i], inputTensorShape);
+
+ // Populate the tensor
+ for (tensorflow::uint64 elem = 0 ; elem < batchSize ; elem++)
+ {
+ const tensorflow::uint64 samplePos = sampleStart + elem;
+ IndexType start;
+ start[0] = 0;
+ if (reorder)
+ {
+ start[1] = order[samplePos] * sz_y;
+ }
+ else
+ {
+ start[1] = samplePos * sz_y;;
+ }
+ RegionType patchRegion(start, inputPatchSize);
+ if (m_UseStreaming)
+ {
+ // If streaming is enabled, we need to explicitly propagate requested region
+ tf::PropagateRequestedRegion<TInputImage>(inputPtr, patchRegion);
+ }
+ tf::RecopyImageRegionToTensorWithCast<TInputImage>(inputPtr, patchRegion, inputTensor, elem );
+ }
+
+ // Input #i : the tensor of patches (aka the batch)
+ DictElementType input1 = { this->GetInputPlaceholdersNames()[i], inputTensor };
+ inputs.push_back(input1);
+ } // next input tensor
+ }
+
+
+} // end namespace otb
+
+
+#endif
diff --git a/include/otbTensorflowMultisourceModelTrain.h b/include/otbTensorflowMultisourceModelTrain.h
index 8308f2ed5bbbb64b949163f33bea3a3b5eb1fa80..ec4ce349c6af76d36c6d2280c080b041d4b06e2d 100644
--- a/include/otbTensorflowMultisourceModelTrain.h
+++ b/include/otbTensorflowMultisourceModelTrain.h
@@ -16,7 +16,7 @@
#include "itkSimpleDataObjectDecorator.h"
// Base
-#include "otbTensorflowMultisourceModelBase.h"
+#include "otbTensorflowMultisourceModelLearningBase.h"
// Shuffle
#include <random>
@@ -31,67 +31,47 @@ namespace otb
* \brief This filter train a TensorFlow model over multiple input images.
*
* The filter takes N input images and feed the TensorFlow model.
- * Names of input placeholders must be specified using the
- * SetInputPlaceholdersNames method
*
- * TODO: Add an option to disable streaming
*
* \ingroup OTBTensorflow
*/
template <class TInputImage>
class ITK_EXPORT TensorflowMultisourceModelTrain :
-public TensorflowMultisourceModelBase<TInputImage>
+public TensorflowMultisourceModelLearningBase<TInputImage>
{
public:
/** Standard class typedefs. */
- typedef TensorflowMultisourceModelTrain Self;
- typedef TensorflowMultisourceModelBase<TInputImage> Superclass;
- typedef itk::SmartPointer<Self> Pointer;
- typedef itk::SmartPointer<const Self> ConstPointer;
+ typedef TensorflowMultisourceModelTrain Self;
+ typedef TensorflowMultisourceModelLearningBase<TInputImage> Superclass;
+ typedef itk::SmartPointer<Self> Pointer;
+ typedef itk::SmartPointer<const Self> ConstPointer;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Run-time type information (and related methods). */
- itkTypeMacro(TensorflowMultisourceModelTrain, TensorflowMultisourceModelBase);
-
- /** Images typedefs */
- typedef typename Superclass::ImageType ImageType;
- typedef typename Superclass::ImagePointerType ImagePointerType;
- typedef typename Superclass::RegionType RegionType;
- typedef typename Superclass::SizeType SizeType;
- typedef typename Superclass::IndexType IndexType;
-
- /* Typedefs for parameters */
- typedef typename Superclass::DictType DictType;
- typedef typename Superclass::StringList StringList;
- typedef typename Superclass::SizeListType SizeListType;
- typedef typename Superclass::DictListType DictListType;
- typedef typename Superclass::TensorListType TensorListType;
-
- itkSetMacro(BatchSize, unsigned int);
- itkGetMacro(BatchSize, unsigned int);
- itkGetMacro(NumberOfSamples, unsigned int);
-
- virtual void GenerateOutputInformation(void);
+ itkTypeMacro(TensorflowMultisourceModelTrain, TensorflowMultisourceModelLearningBase);
- virtual void GenerateInputRequestedRegion();
+ /** Superclass typedefs */
+ typedef typename Superclass::IndexValueType IndexValueType;
+ typedef typename Superclass::TensorListType TensorListType;
+ typedef typename Superclass::IndexListType IndexListType;
- virtual void GenerateData();
protected:
TensorflowMultisourceModelTrain();
virtual ~TensorflowMultisourceModelTrain() {};
+ void GenerateData();
+ void ProcessBatch(TensorListType & inputs, const IndexValueType & sampleStart,
+ const IndexValueType & batchSize);
+
private:
TensorflowMultisourceModelTrain(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
- unsigned int m_BatchSize; // Batch size
-
- // Read only
- unsigned int m_NumberOfSamples; // Number of samples
+ IndexListType m_RandomIndices; // Reordered indices
}; // end class
diff --git a/include/otbTensorflowMultisourceModelTrain.hxx b/include/otbTensorflowMultisourceModelTrain.hxx
index aa47237c30ba886c5bc7b9effa5028d9cdefde91..2ad029129f0c75bf940cd7b8badd025a98e564ac 100644
--- a/include/otbTensorflowMultisourceModelTrain.hxx
+++ b/include/otbTensorflowMultisourceModelTrain.hxx
@@ -20,183 +20,44 @@ template <class TInputImage>
TensorflowMultisourceModelTrain<TInputImage>
::TensorflowMultisourceModelTrain()
{
- m_BatchSize = 100;
- m_NumberOfSamples = 0;
}
-
template <class TInputImage>
void
TensorflowMultisourceModelTrain<TInputImage>
-::GenerateOutputInformation()
+::GenerateData()
{
- Superclass::GenerateOutputInformation();
-
- ImageType * outputPtr = this->GetOutput();
- RegionType nullRegion;
- nullRegion.GetModifiableSize().Fill(1);
- outputPtr->SetNumberOfComponentsPerPixel(1);
- outputPtr->SetLargestPossibleRegion( nullRegion );
-
- //////////////////////////////////////////////////////////////////////////////////////////
- // Check the number of samples
- //////////////////////////////////////////////////////////////////////////////////////////
-
- m_NumberOfSamples = 0;
- for (unsigned int i = 0 ; i < this->GetNumberOfInputs() ; i++)
- {
- // Input image pointer
- ImagePointerType inputPtr = const_cast<ImageType*>(this->GetInput(i));
-
- // Make sure input is available
- if ( inputPtr.IsNull() )
- {
- itkExceptionMacro(<< "Input " << i << " is null!");
- }
-
- // Update input information
- inputPtr->UpdateOutputInformation();
-
- // Patch size of tensor #i
- const SizeType inputPatchSize = this->GetInputFOVSizes().at(i);
-
- // Input image requested region
- const RegionType reqRegion = inputPtr->GetLargestPossibleRegion();
-
- // Check size X
- if (inputPatchSize[0] != reqRegion.GetSize(0))
- itkExceptionMacro("Patch size for input " << i << " is " << inputPatchSize <<
- " but input patches image size is " << reqRegion.GetSize());
-
- // Check size Y
- if (reqRegion.GetSize(1) % inputPatchSize[1] != 0)
- itkExceptionMacro("Input patches image must have a number of rows which is "
- "a multiple of the patch size Y! Patches image has " << reqRegion.GetSize(1) <<
- " rows but patch size Y is " << inputPatchSize[1] << " for input " << i);
-
- // Get the batch size
- const tensorflow::uint64 currNumberOfSamples = reqRegion.GetSize(1) / inputPatchSize[1];
-
- // Check the consistency with other inputs
- if (m_NumberOfSamples == 0)
- {
- m_NumberOfSamples = currNumberOfSamples;
- }
- else if (m_NumberOfSamples != currNumberOfSamples)
- {
- itkGenericExceptionMacro("Previous batch size is " << m_NumberOfSamples << " but input " << i
- << " has a batch size of " << currNumberOfSamples );
- }
- } // next input
- }
-template <class TInputImage>
-void
-TensorflowMultisourceModelTrain<TInputImage>
-::GenerateInputRequestedRegion()
- {
- Superclass::GenerateInputRequestedRegion();
-
- // For each image, set no image region
- for(unsigned int i = 0; i < this->GetNumberOfInputs(); ++i)
- {
- RegionType nullRegion;
- ImageType * inputImage = static_cast<ImageType * >( Superclass::ProcessObject::GetInput(i) );
-// TODO: streaming mode on/off
-// inputImage->SetRequestedRegion(nullRegion);
- inputImage->SetRequestedRegion(inputImage->GetLargestPossibleRegion());
- } // next image
+ // Initial sequence 1...N
+ m_RandomIndices.resize(this->GetNumberOfSamples());
+ std::iota (std::begin(m_RandomIndices), std::end(m_RandomIndices), 0);
+
+ // Shuffle the sequence
+ std::random_device rd;
+ std::mt19937 g(rd());
+ std::shuffle(m_RandomIndices.begin(), m_RandomIndices.end(), g);
+
+ // Call the generic method
+ Superclass::GenerateData();
+
}
-/**
- *
- */
template <class TInputImage>
void
TensorflowMultisourceModelTrain<TInputImage>
-::GenerateData()
+::ProcessBatch(TensorListType & inputs, const IndexValueType & sampleStart,
+ const IndexValueType & batchSize)
{
+ // Populate input tensors
+ PopulateInputTensor(inputs, sampleStart, batchSize, m_RandomIndices);
- // Random sequence
- std::vector<int> v(m_NumberOfSamples) ;
- std::iota (std::begin(v), std::end(v), 0);
-
- // Shuffle
- std::random_device rd;
- std::mt19937 g(rd());
- std::shuffle(v.begin(), v.end(), g);
-
- // Batches loop
- const tensorflow::uint64 nBatches = vcl_ceil(m_NumberOfSamples / m_BatchSize);
- const tensorflow::uint64 rest = m_NumberOfSamples % m_BatchSize;
- itk::ProgressReporter progress(this, 0, nBatches);
- for (tensorflow::uint64 batch = 0 ; batch < nBatches ; batch++)
- {
- // Update progress
- this->UpdateProgress((float) batch / (float) nBatches);
-
- // Create input tensors list
- DictListType inputs;
-
- // Batch start and size
- const tensorflow::uint64 sampleStart = batch * m_BatchSize;
- tensorflow::uint64 batchSize = m_BatchSize;
- if (rest != 0)
- {
- batchSize = rest;
- }
-
- // Populate input tensors
- for (unsigned int i = 0 ; i < this->GetNumberOfInputs() ; i++)
- {
- // Input image pointer
- ImagePointerType inputPtr = const_cast<ImageType*>(this->GetInput(i));
-
- // Patch size of tensor #i
- const SizeType inputPatchSize = this->GetInputFOVSizes().at(i);
-
- // Create the tensor for the batch
- const tensorflow::int64 sz_n = batchSize;
- const tensorflow::int64 sz_y = inputPatchSize[1];
- const tensorflow::int64 sz_x = inputPatchSize[0];
- const tensorflow::int64 sz_c = inputPtr->GetNumberOfComponentsPerPixel();
- const tensorflow::TensorShape inputTensorShape({sz_n, sz_y, sz_x, sz_c});
- tensorflow::Tensor inputTensor(this->GetInputTensorsDataTypes()[i], inputTensorShape);
-
- // Populate the tensor
- for (tensorflow::uint64 elem = 0 ; elem < batchSize ; elem++)
- {
- const tensorflow::uint64 samplePos = sampleStart + elem;
- const tensorflow::uint64 randPos = v[samplePos];
- IndexType start;
- start[0] = 0;
- start[1] = randPos * sz_y;
- RegionType patchRegion(start, inputPatchSize);
-// TODO: streaming mode on/off
-// tf::PropagateRequestedRegion<TInputImage>(inputPtr, patchRegion);
- tf::RecopyImageRegionToTensorWithCast<TInputImage>(inputPtr, patchRegion, inputTensor, elem );
- }
-
- // Input #i : the tensor of patches (aka the batch)
- DictType input1 = { this->GetInputPlaceholdersNames()[i], inputTensor };
- inputs.push_back(input1);
- } // next input tensor
-
- // Run the TF session here
- TensorListType outputs;
- this->RunSession(inputs, outputs);
-
- // Get output tensors
- for (auto& output: outputs)
- {
- std::cout << tf::PrintTensorInfos(output) << std::endl;
- }
-
- progress.CompletedPixel();
- } // Next batch
+ // Run the TF session here
+ TensorListType outputs;
+ this->RunSession(inputs, outputs);
}
+
} // end namespace otb
diff --git a/include/otbTensorflowMultisourceModelValidate.h b/include/otbTensorflowMultisourceModelValidate.h
index 868317f9344ba1567deaf71aecd7b18a2ccd635f..048ff70cdfd4319abeba653c0121940a05af6127 100644
--- a/include/otbTensorflowMultisourceModelValidate.h
+++ b/include/otbTensorflowMultisourceModelValidate.h
@@ -33,16 +33,12 @@ namespace otb
* \brief This filter validates a TensorFlow model over multiple input images.
*
* The filter takes N input images and feed the TensorFlow model.
- * Names of input placeholders must be specified using the
- * SetInputPlaceholdersNames method
- *
- * TODO: Add an option to disable streaming
*
* \ingroup OTBTensorflow
*/
template <class TInputImage>
class ITK_EXPORT TensorflowMultisourceModelValidate :
-public TensorflowMultisourceModelBase<TInputImage>
+public TensorflowMultisourceModelLearningBase<TInputImage>
{
public:
@@ -56,7 +52,7 @@ public:
itkNewMacro(Self);
/** Run-time type information (and related methods). */
- itkTypeMacro(TensorflowMultisourceModelValidate, TensorflowMultisourceModelBase);
+ itkTypeMacro(TensorflowMultisourceModelValidate, TensorflowMultisourceModelLearningBase);
/** Images typedefs */
typedef typename Superclass::ImageType ImageType;
@@ -70,8 +66,8 @@ public:
typedef typename Superclass::DictType DictType;
typedef typename Superclass::StringList StringList;
typedef typename Superclass::SizeListType SizeListType;
- typedef typename Superclass::DictListType DictListType;
typedef typename Superclass::TensorListType TensorListType;
+ typedef typename Superclass::IndexValueType IndexValueType;
/* Typedefs for validation */
typedef unsigned long CountValueType;
@@ -84,23 +80,11 @@ public:
typedef std::vector<ConfMatType> ConfMatListType;
typedef itk::ImageRegionConstIterator<ImageType> IteratorType;
- /* Set and Get the batch size
- itkSetMacro(BatchSize, unsigned int);
- itkGetMacro(BatchSize, unsigned int);
-
- /** Get the number of samples */
- itkGetMacro(NumberOfSamples, unsigned int);
-
- virtual void GenerateOutputInformation(void);
-
- virtual void GenerateInputRequestedRegion();
/** Set and Get the input references */
virtual void SetInputReferences(ImageListType input);
ImagePointerType GetInputReference(unsigned int index);
- virtual void GenerateData();
-
/** Get the confusion matrix */
const ConfMatType GetConfusionMatrix(unsigned int target);
@@ -111,15 +95,18 @@ protected:
TensorflowMultisourceModelValidate();
virtual ~TensorflowMultisourceModelValidate() {};
+ void GenerateOutputInformation(void);
+ void GenerateData();
+ void ProcessBatch(TensorListType & inputs, const IndexValueType & sampleStart,
+ const IndexValueType & batchSize);
+
private:
TensorflowMultisourceModelValidate(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
- unsigned int m_BatchSize; // Batch size
ImageListType m_References; // The references images
// Read only
- unsigned int m_NumberOfSamples; // Number of samples
ConfMatListType m_ConfusionMatrices; // Confusion matrix
MapOfClassesListType m_MapsOfClasses; // Maps of classes
diff --git a/include/otbTensorflowMultisourceModelValidate.hxx b/include/otbTensorflowMultisourceModelValidate.hxx
index b0ec5e2dd264aa5369cf6f7e4d364a7cbc9fbbdb..3f4fd9b91973eac710a7b9495664cdffef2e5887 100644
--- a/include/otbTensorflowMultisourceModelValidate.hxx
+++ b/include/otbTensorflowMultisourceModelValidate.hxx
@@ -20,8 +20,6 @@ template <class TInputImage>
TensorflowMultisourceModelValidate<TInputImage>
::TensorflowMultisourceModelValidate()
{
- m_BatchSize = 100;
- m_NumberOfSamples = 0;
}
@@ -32,63 +30,6 @@ TensorflowMultisourceModelValidate<TInputImage>
{
Superclass::GenerateOutputInformation();
- ImageType * outputPtr = this->GetOutput();
- RegionType nullRegion;
- nullRegion.GetModifiableSize().Fill(1);
- outputPtr->SetNumberOfComponentsPerPixel(1);
- outputPtr->SetLargestPossibleRegion( nullRegion );
-
- //////////////////////////////////////////////////////////////////////////////////////////
- // Check the number of samples
- //////////////////////////////////////////////////////////////////////////////////////////
-
- m_NumberOfSamples = 0;
- for (unsigned int i = 0 ; i < this->GetNumberOfInputs() ; i++)
- {
- // Input image pointer
- ImagePointerType inputPtr = const_cast<ImageType*>(this->GetInput(i));
-
- // Make sure input is available
- if ( inputPtr.IsNull() )
- {
- itkExceptionMacro(<< "Input " << i << " is null!");
- }
-
- // Update input information
- inputPtr->UpdateOutputInformation();
-
- // Patch size of tensor #i
- const SizeType inputPatchSize = this->GetInputFOVSizes().at(i);
-
- // Input image requested region
- const RegionType reqRegion = inputPtr->GetLargestPossibleRegion();
-
- // Check size X
- if (inputPatchSize[0] != reqRegion.GetSize(0))
- itkExceptionMacro("Patch size for input " << i << " is " << inputPatchSize <<
- " but input patches image size is " << reqRegion.GetSize());
-
- // Check size Y
- if (reqRegion.GetSize(1) % inputPatchSize[1] != 0)
- itkExceptionMacro("Input patches image must have a number of rows which is "
- "a multiple of the patch size Y! Patches image has " << reqRegion.GetSize(1) <<
- " rows but patch size Y is " << inputPatchSize[1] << " for input " << i);
-
- // Get the batch size
- const tensorflow::uint64 currNumberOfSamples = reqRegion.GetSize(1) / inputPatchSize[1];
-
- // Check the consistency with other inputs
- if (m_NumberOfSamples == 0)
- {
- m_NumberOfSamples = currNumberOfSamples;
- }
- else if (m_NumberOfSamples != currNumberOfSamples)
- {
- itkGenericExceptionMacro("Previous batch size is " << m_NumberOfSamples << " but input " << i
- << " has a batch size of " << currNumberOfSamples );
- }
- } // next input
-
//////////////////////////////////////////////////////////////////////////////////////////
// Check the references
//////////////////////////////////////////////////////////////////////////////////////////
@@ -98,7 +39,7 @@ TensorflowMultisourceModelValidate<TInputImage>
{
itkExceptionMacro("No reference is set");
}
- SizeListType outputEFSizes = this->GetOutputFOESizes();
+ SizeListType outputEFSizes = this->GetOutputExpressionFields();
if (nbOfRefs != outputEFSizes.size())
{
itkExceptionMacro("There is " << nbOfRefs << " but only " <<
@@ -115,32 +56,16 @@ TensorflowMultisourceModelValidate<TInputImage>
itkExceptionMacro("Reference image " << i << " width is " << refRegion.GetSize(0) <<
" but field of expression width is " << outputFOESize[0]);
}
- if (refRegion.GetSize(1) / outputFOESize[1] != m_NumberOfSamples)
+ if (refRegion.GetSize(1) / outputFOESize[1] != this->GetNumberOfSamples())
{
itkExceptionMacro("Reference image " << i << " height is " << refRegion.GetSize(1) <<
" but field of expression width is " << outputFOESize[1] <<
- " which is not consistent with the number of samples (" << m_NumberOfSamples << ")");
+ " which is not consistent with the number of samples (" << this->GetNumberOfSamples() << ")");
}
}
}
-template <class TInputImage>
-void
-TensorflowMultisourceModelValidate<TInputImage>
-::GenerateInputRequestedRegion()
- {
- Superclass::GenerateInputRequestedRegion();
-
- // For each image, set no image region
- for(unsigned int i = 0; i < this->GetNumberOfInputs(); ++i)
- {
- RegionType nullRegion;
- ImageType * inputImage = static_cast<ImageType * >( Superclass::ProcessObject::GetInput(i) );
- inputImage->SetRequestedRegion(nullRegion);
- } // next image
-
- }
/*
* Set the references images
@@ -195,127 +120,8 @@ TensorflowMultisourceModelValidate<TInputImage>
confMatMaps.push_back(mat);
}
- // Batches loop
- const tensorflow::uint64 nBatches = vcl_ceil(m_NumberOfSamples / m_BatchSize);
- const tensorflow::uint64 rest = m_NumberOfSamples % m_BatchSize;
- itk::ProgressReporter progress(this, 0, nBatches);
- for (tensorflow::uint64 batch = 0 ; batch < nBatches ; batch++)
- {
- // Update progress
- this->UpdateProgress((float) batch / (float) nBatches);
-
- // Sample start of this batch
- const tensorflow::uint64 sampleStart = batch * m_BatchSize;
- tensorflow::uint64 batchSize = m_BatchSize;
- if (rest != 0)
- {
- batchSize = rest;
- }
-
- // Create input tensors list
- DictListType inputs;
-
- // Populate input tensors
- for (unsigned int i = 0 ; i < this->GetNumberOfInputs() ; i++)
- {
- // Input image pointer
- ImagePointerType inputPtr = const_cast<ImageType*>(this->GetInput(i));
-
- // Patch size of tensor #i
- const SizeType inputPatchSize = this->GetInputFOVSizes().at(i);
-
- // Create the tensor for the batch
- const tensorflow::int64 sz_n = batchSize;
- const tensorflow::int64 sz_y = inputPatchSize[1];
- const tensorflow::int64 sz_x = inputPatchSize[0];
- const tensorflow::int64 sz_c = inputPtr->GetNumberOfComponentsPerPixel();
- const tensorflow::TensorShape inputTensorShape({sz_n, sz_y, sz_x, sz_c});
- tensorflow::Tensor inputTensor(this->GetInputTensorsDataTypes()[i], inputTensorShape);
-
- // Populate the tensor
- for (tensorflow::uint64 elem = 0 ; elem < batchSize ; elem++)
- {
- const tensorflow::uint64 samplePos = sampleStart + elem;
- IndexType start;
- start[0] = 0;
- start[1] = samplePos * sz_y;
- RegionType patchRegion(start, inputPatchSize);
- tf::PropagateRequestedRegion<TInputImage>(inputPtr, patchRegion);
- tf::RecopyImageRegionToTensorWithCast<TInputImage>(inputPtr, patchRegion, inputTensor, elem );
- }
-
- // Input #i : the tensor of patches (aka the batch)
- DictType input1 = { this->GetInputPlaceholdersNames()[i], inputTensor };
- inputs.push_back(input1);
- } // next input tensor
-
- // Run the TF session here
- TensorListType outputs;
- this->RunSession(inputs, outputs);
-
- // Perform the validation
- if (outputs.size() != m_References.size())
- {
- itkWarningMacro("There is " << outputs.size() << " outputs returned after session run, " <<
- "but only " << m_References.size() << " reference(s) set");
- }
- SizeListType outputEFSizes = this->GetOutputFOESizes();
- for (unsigned int refIdx = 0 ; refIdx < outputs.size() ; refIdx++)
- {
- // Recopy the chunk
- const SizeType outputFOESize = outputEFSizes[refIdx];
- IndexType cpyStart;
- cpyStart.Fill(0);
- IndexType refRegStart;
- refRegStart.Fill(0);
- refRegStart[1] = outputFOESize[1] * sampleStart;
- SizeType cpySize;
- cpySize[0] = outputFOESize[0];
- cpySize[1] = outputFOESize[1] * batchSize;
- RegionType cpyRegion(cpyStart, cpySize);
- RegionType refRegion(refRegStart, cpySize);
-
- // Allocate a temporary image
- ImagePointerType img = ImageType::New();
- img->SetRegions(cpyRegion);
- img->SetNumberOfComponentsPerPixel(1);
- img->Allocate();
-
- int co = 0;
- tf::CopyTensorToImageRegion<TInputImage>(outputs[refIdx], cpyRegion, img, cpyRegion, co);
-
- // Retrieve the reference image region
- tf::PropagateRequestedRegion<TInputImage>(m_References[refIdx], refRegion);
-
- // Update the confusion matrices
- IteratorType inIt(img, cpyRegion);
- IteratorType refIt(m_References[refIdx], refRegion);
- for (inIt.GoToBegin(), refIt.GoToBegin(); !inIt.IsAtEnd(); ++inIt, ++refIt)
- {
- const int classIn = static_cast<LabelValueType>(inIt.Get()[0]);
- const int classRef = static_cast<LabelValueType>(refIt.Get()[0]);
-
- if (confMatMaps[refIdx].count(classRef) == 0)
- {
- MapType newMap;
- newMap[classIn] = 1;
- confMatMaps[refIdx][classRef] = newMap;
- }
- else
- {
- if (confMatMaps[refIdx][classRef].count(classIn) == 0)
- {
- confMatMaps[refIdx][classRef][classIn] = 1;
- }
- else
- {
- confMatMaps[refIdx][classRef][classIn]++;
- }
- }
- }
- }
- progress.CompletedPixel();
- } // Next batch
+ // Run all the batches
+ Superclass::GenerateData();
// Compute confusion matrices
for (unsigned int i = 0 ; i < confMatMaps.size() ; i++)
@@ -353,6 +159,88 @@ TensorflowMultisourceModelValidate<TInputImage>
m_ConfusionMatrices.push_back(matrix);
m_MapsOfClasses.push_back(values);
+
+
+
+
+ }
+
+ }
+
+
+template <class TInputImage>
+void
+TensorflowMultisourceModelValidate<TInputImage>
+::ProcessBatch(TensorListType & inputs, const IndexValueType & sampleStart,
+ const IndexValueType & batchSize)
+ {
+ // Populate input tensors
+ PopulateInputTensor(inputs, sampleStart, batchSize);
+
+ // Run the TF session here
+ TensorListType outputs;
+ this->RunSession(inputs, outputs);
+
+ // Perform the validation
+ if (outputs.size() != m_References.size())
+ {
+ itkWarningMacro("There is " << outputs.size() << " outputs returned after session run, " <<
+ "but only " << m_References.size() << " reference(s) set");
+ }
+ SizeListType outputEFSizes = this->GetOutputExpressionFields();
+ for (unsigned int refIdx = 0 ; refIdx < outputs.size() ; refIdx++)
+ {
+ // Recopy the chunk
+ const SizeType outputFOESize = outputEFSizes[refIdx];
+ IndexType cpyStart;
+ cpyStart.Fill(0);
+ IndexType refRegStart;
+ refRegStart.Fill(0);
+ refRegStart[1] = outputFOESize[1] * sampleStart;
+ SizeType cpySize;
+ cpySize[0] = outputFOESize[0];
+ cpySize[1] = outputFOESize[1] * batchSize;
+ RegionType cpyRegion(cpyStart, cpySize);
+ RegionType refRegion(refRegStart, cpySize);
+
+ // Allocate a temporary image
+ ImagePointerType img = ImageType::New();
+ img->SetRegions(cpyRegion);
+ img->SetNumberOfComponentsPerPixel(1);
+ img->Allocate();
+
+ int co = 0;
+ tf::CopyTensorToImageRegion<TInputImage>(outputs[refIdx], cpyRegion, img, cpyRegion, co);
+
+ // Retrieve the reference image region
+ tf::PropagateRequestedRegion<TInputImage>(m_References[refIdx], refRegion);
+
+ // Update the confusion matrices
+ IteratorType inIt(img, cpyRegion);
+ IteratorType refIt(m_References[refIdx], refRegion);
+ for (inIt.GoToBegin(), refIt.GoToBegin(); !inIt.IsAtEnd(); ++inIt, ++refIt)
+ {
+ const int classIn = static_cast<LabelValueType>(inIt.Get()[0]);
+ const int classRef = static_cast<LabelValueType>(refIt.Get()[0]);
+
+ if (confMatMaps[refIdx].count(classRef) == 0)
+ {
+ MapType newMap;
+ newMap[classIn] = 1;
+ confMatMaps[refIdx][classRef] = newMap;
+ }
+ else
+ {
+ if (confMatMaps[refIdx][classRef].count(classIn) == 0)
+ {
+ confMatMaps[refIdx][classRef][classIn] = 1;
+ }
+ else
+ {
+ confMatMaps[refIdx][classRef][classIn]++;
+ }
+ }
+ }
}
}