diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index 2cc931445263f8ba33e2037c597a95e5470010be..5f86f2dcc9f2264ac126ade05c48b5a122fd918b 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -1,7 +1,5 @@
-image: $CI_REGISTRY_IMAGE:$CI_COMMIT_REF_NAME
-
variables:
- OTBTF_VERSION: 4.0.0
+ OTBTF_VERSION: 4.1.0
OTB_BUILD: /src/otb/build/OTB/build # Local OTB build directory
OTBTF_SRC: /src/otbtf # Local OTBTF source directory
OTB_TEST_DIR: $OTB_BUILD/Testing/Temporary # OTB testing directory
@@ -19,7 +17,10 @@ variables:
DOCKERHUB_BASE: mdl4eo/otbtf
DOCKERHUB_IMAGE_BASE: ${DOCKERHUB_BASE}:${OTBTF_VERSION}
CPU_BASE_IMG: ubuntu:22.04
- GPU_BASE_IMG: nvidia/cuda:12.0.1-cudnn8-devel-ubuntu22.04
+ GPU_BASE_IMG: nvidia/cuda:12.1.1-cudnn8-devel-ubuntu22.04
+
+image: $BRANCH_IMAGE
+
workflow:
rules:
- if: $CI_MERGE_REQUEST_ID || $CI_COMMIT_REF_NAME =~ /master/ # Execute jobs in merge request context, or commit in master branch
@@ -217,6 +218,11 @@ rio:
- sudo pip install rasterio
- python -m pytest --junitxml=$ARTIFACT_TEST_DIR/report_rio.xml $OTBTF_SRC/test/rio_test.py
+nodata:
+ extends: .applications_test_base
+ script:
+ - python -m pytest --junitxml=$ARTIFACT_TEST_DIR/report_nodata.xml $OTBTF_SRC/test/nodata_test.py
+
deploy_cpu-dev-testing:
stage: Update dev image
extends: .docker_build_base
@@ -265,6 +271,7 @@ deploy_gpu:
IMAGE_GPUDEV: $CI_REGISTRY_PUBIMG-gpu-dev
IMAGE_GPUOPT: $CI_REGISTRY_PUBIMG-gpu-opt
IMAGE_GPUOPTDEV: $CI_REGISTRY_PUBIMG-gpu-opt-dev
+ IMAGE_GPUOPTDEVTRT: $CI_REGISTRY_PUBIMG-gpu-opt-dev-trt
DOCKERHUB_GPU: $DOCKERHUB_IMAGE_BASE-gpu
DOCKERHUB_GPUDEV: $DOCKERHUB_IMAGE_BASE-gpu-dev
script:
@@ -274,6 +281,9 @@ deploy_gpu:
# gpu-opt-dev
- docker build --build-arg BZL_OPTIONS="--remote_cache=$BAZELCACHE" --tag $IMAGE_GPUOPTDEV --build-arg BASE_IMG=$GPU_BASE_IMG --build-arg KEEP_SRC_OTB=true .
- docker push $IMAGE_GPUOPTDEV
+ # gpu-opt-dev-trt
+ - docker build --build-arg BZL_OPTIONS="--remote_cache=$BAZELCACHE" --tag $IMAGE_GPUOPTDEV --build-arg BASE_IMG="cuda:11.8.0-cudnn8-devel-ubuntu22.04" --build-arg KEEP_SRC_OTB=true --build-arg TENSORRT="8.5.1-1+cuda11.8" .
+ - docker push $IMAGE_GPUOPTDEVTRT
# gpu-basic
- docker build --build-arg BZL_OPTIONS="--remote_cache=$BAZELCACHE" --tag $IMAGE_GPU --build-arg BASE_IMG=$GPU_BASE_IMG --build-arg BZL_CONFIGS="" .
- docker push $IMAGE_GPU
diff --git a/Dockerfile b/Dockerfile
index a612da257648a30ca2cec7ed44578e950d1b1607..711dc4ba30a70f8985df23d861894921d12b1982 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -44,6 +44,7 @@ RUN git config --global advice.detachedHead false
### TF
ARG TF=v2.12.0
+ARG TENSORRT
# Install bazelisk (will read .bazelversion and download the right bazel binary - latest by default)
RUN wget -qO /opt/otbtf/bin/bazelisk https://github.com/bazelbuild/bazelisk/releases/latest/download/bazelisk-linux-amd64 \
@@ -202,4 +203,5 @@ ENV PATH="/home/otbuser/.local/bin:$PATH"
RUN python -c "import tensorflow"
RUN python -c "import otbtf, tricks"
RUN python -c "import otbApplication as otb; otb.Registry.CreateApplication('ImageClassifierFromDeepFeatures')"
-RUN python -c "from osgeo import gdal"
\ No newline at end of file
+RUN python -c "from osgeo import gdal"
+
diff --git a/RELEASE_NOTES.txt b/RELEASE_NOTES.txt
index fd30467cc836e5b3d75cbedbc891ad9527215697..24d3f247a840518290bd43fee05d7466de743054 100644
--- a/RELEASE_NOTES.txt
+++ b/RELEASE_NOTES.txt
@@ -1,3 +1,9 @@
+Version 4.1.0 (23 may 2023)
+----------------------------------------------------------------
+* Add no-data values support for inference in TensorflowModelServe application
+* Update base docker image for NVIDIA GPU builds (CUDA 12.1.1)
+* Fix CuDNN version detection in `build-env-tf.sh`
+
Version 4.0.0 (5 apr 2023)
----------------------------------------------------------------
* Big improvement of the documentation:
diff --git a/app/otbTensorflowModelServe.cxx b/app/otbTensorflowModelServe.cxx
index 47a8c95730443c0c3345933d71f63a1bcbcb556d..59969e36f4b90a3e473c3328844d78778a5aa940 100644
--- a/app/otbTensorflowModelServe.cxx
+++ b/app/otbTensorflowModelServe.cxx
@@ -70,11 +70,14 @@ public:
InputImageSource m_ImageSource;
SizeType m_PatchSize;
std::string m_Placeholder;
+ float m_NodataValue;
+ bool m_HasNodata;
// Parameters keys
std::string m_KeyIn; // Key of input image list
- std::string m_KeyPszX; // Key for samples sizes X
- std::string m_KeyPszY; // Key for samples sizes Y
+ std::string m_KeyPszX; // Key for receptive field size in X
+ std::string m_KeyPszY; // Key for receptive field size in Y
+ std::string m_KeyND; // Key for no-data value
std::string m_KeyPHName; // Key for placeholder name in the tensorflow model
};
@@ -93,7 +96,8 @@ public:
ss_key_in, ss_desc_in,
ss_key_dims_x, ss_desc_dims_x,
ss_key_dims_y, ss_desc_dims_y,
- ss_key_ph, ss_desc_ph;
+ ss_key_ph, ss_desc_ph,
+ ss_key_nd, ss_desc_nd;
// Parameter group key/description
ss_key_group << "source" << inputNumber;
@@ -104,12 +108,14 @@ public:
ss_key_dims_x << ss_key_group.str() << ".rfieldx";
ss_key_dims_y << ss_key_group.str() << ".rfieldy";
ss_key_ph << ss_key_group.str() << ".placeholder";
+ ss_key_nd << ss_key_group.str() << ".nodata";
// Parameter group descriptions
ss_desc_in << "Input image (or list to stack) for source #" << inputNumber;
ss_desc_dims_x << "Input receptive field (width) for source #" << inputNumber;
ss_desc_dims_y << "Input receptive field (height) for source #" << inputNumber;
ss_desc_ph << "Name of the input placeholder for source #" << inputNumber;
+ ss_desc_nd << "No-data value for pixels of source #" << inputNumber;
// Populate group
AddParameter(ParameterType_Group, ss_key_group.str(), ss_desc_group.str());
@@ -122,6 +128,8 @@ public:
SetDefaultParameterInt (ss_key_dims_y.str(), 1);
AddParameter(ParameterType_String, ss_key_ph.str(), ss_desc_ph.str());
MandatoryOff (ss_key_ph.str());
+ AddParameter(ParameterType_Float, ss_key_nd.str(), ss_desc_nd.str());
+ MandatoryOff (ss_key_nd.str());
// Add a new bundle
ProcessObjectsBundle bundle;
@@ -129,6 +137,7 @@ public:
bundle.m_KeyPszX = ss_key_dims_x.str();
bundle.m_KeyPszY = ss_key_dims_y.str();
bundle.m_KeyPHName = ss_key_ph.str();
+ bundle.m_KeyND = ss_key_nd.str();
m_Bundles.push_back(bundle);
@@ -183,7 +192,12 @@ public:
SetDefaultParameterFloat ("output.spcscale", 1.0);
SetParameterDescription ("output.spcscale", "The output image size/scale and spacing*scale where size and spacing corresponds to the first input");
AddParameter(ParameterType_StringList, "output.names", "Names of the output tensors");
- MandatoryOff ("output.names");
+ MandatoryOff ("output.names");
+
+ // Output background value
+ AddParameter(ParameterType_Float, "output.bv", "Output background value");
+ SetDefaultParameterFloat ("output.bv", 0.0);
+ SetParameterDescription ("output.bv", "The value used when one input has only no-data values in its receptive field");
// Output Field of Expression
AddParameter(ParameterType_Int, "output.efieldx", "The output expression field (width)");
@@ -236,10 +250,14 @@ public:
bundle.m_Placeholder = GetParameterAsString(bundle.m_KeyPHName);
bundle.m_PatchSize[0] = GetParameterInt(bundle.m_KeyPszX);
bundle.m_PatchSize[1] = GetParameterInt(bundle.m_KeyPszY);
+ bundle.m_HasNodata = HasValue(bundle.m_KeyND);
+ bundle.m_NodataValue = (bundle.m_HasNodata == true) ? GetParameterFloat(bundle.m_KeyND) : 0;
otbAppLogINFO("Source info :");
otbAppLogINFO("Receptive field : " << bundle.m_PatchSize );
otbAppLogINFO("Placeholder name : " << bundle.m_Placeholder);
+ if (bundle.m_HasNodata == true)
+ otbAppLogINFO("No-data value : " << bundle.m_NodataValue);
}
}
@@ -274,7 +292,7 @@ public:
// Input sources
for (auto& bundle: m_Bundles)
{
- m_TFFilter->PushBackInputTensorBundle(bundle.m_Placeholder, bundle.m_PatchSize, bundle.m_ImageSource.Get());
+ m_TFFilter->PushBackInputTensorBundle(bundle.m_Placeholder, bundle.m_PatchSize, bundle.m_ImageSource.Get(), bundle.m_HasNodata, bundle.m_NodataValue);
}
// Fully convolutional mode on/off
@@ -284,6 +302,11 @@ public:
m_TFFilter->SetFullyConvolutional(true);
}
+ // Output background value
+ const float outBV = GetParameterFloat("output.bv");
+ otbAppLogINFO("Setting background value to " << outBV);
+ m_TFFilter->SetOutputBackgroundValue(outBV);
+
// Output field of expression
FloatVectorImageType::SizeType foe;
foe[0] = GetParameterInt("output.efieldx");
diff --git a/doc/app_inference.md b/doc/app_inference.md
index d50a7c03235c6fa2ff3feed3b0dafb3a72e08d32..63557d996c1b27852366beada371f0dfad4743b3 100644
--- a/doc/app_inference.md
+++ b/doc/app_inference.md
@@ -23,14 +23,14 @@ known:
The **scale factor** describes the physical change of spacing of the outputs,
-typically introduced in the model by non unitary strides in pooling or
+typically introduced in the model by non-unitary strides in pooling or
convolution operators.
For each output, it is expressed relatively to one single input of the model
called the *reference input source*.
Additionally, the names of the *target nodes* must be known (e.g. optimizers
for Tensorflow API v1).
Also, the names of *user placeholders*, typically scalars inputs that are
-used to control some parameters of the model, must be know.
+used to control some parameters of the model, must be known.
The **receptive field** corresponds to the input volume that "sees" the deep
net.
The **expression field** corresponds to the output volume that the deep net
@@ -58,15 +58,20 @@ computation of one single tile of pixels.
So, this application takes in input one or multiple _input sources_ (the number
of _input sources_ can be changed by setting the `OTB_TF_NSOURCES` to the
desired number) and produce one output of the specified tensors.
-The user is responsible of giving the **receptive field** and **name** of
+The user is responsible for giving the **receptive field** and **name** of
_input placeholders_, as well as the **expression field**, **scale factor** and
**name** of _output tensors_.
The first _input source_ (`source1.il`) corresponds to the _reference input
source_.
As explained, the **scale factor** provided for the
_output tensors_ is related to this _reference input source_.
-The user can ask for multiple _output tensors_, that will be stack along the
+The user can ask for multiple _output tensors_, that will be stacked along the
channel dimension of the output raster.
+Since OTBTF 4.1, a no-data value can be provided for each input source (e.g.
+`source1.nodata`). When all elements of an input are equals to the no-data
+value in the processed chunk of image, the local inference process is skipped,
+and the output pixel is filled with the value provided by the `output.bv`
+parameter.
!!! Warning
diff --git a/include/otbTensorflowMultisourceModelBase.h b/include/otbTensorflowMultisourceModelBase.h
index 6c943d1f1e777f8f7d26fc6be7f529b34535b5c7..f452cc2269571c95d17276988136a5cc27ce685d 100644
--- a/include/otbTensorflowMultisourceModelBase.h
+++ b/include/otbTensorflowMultisourceModelBase.h
@@ -96,6 +96,8 @@ public:
typedef std::pair<std::string, tensorflow::Tensor> DictElementType;
typedef std::vector<std::string> StringList;
typedef std::vector<SizeType> SizeListType;
+ typedef std::vector<bool> BoolListType;
+ typedef std::vector<InternalPixelType> ValueListType;
typedef std::vector<DictElementType> DictType;
typedef std::vector<tensorflow::DataType> DataTypeListType;
typedef std::vector<tensorflow::TensorShapeProto> TensorShapeProtoList;
@@ -119,7 +121,13 @@ public:
/** Model parameters */
void
- PushBackInputTensorBundle(std::string name, SizeType receptiveField, ImagePointerType image);
+ PushBackInputTensorBundle(
+ std::string name,
+ SizeType
+ receptiveField,
+ ImagePointerType image,
+ bool useNodata = false,
+ InternalPixelType nodataValue = 0);
void
PushBackOuputTensorBundle(std::string name, SizeType expressionField);
@@ -131,6 +139,14 @@ public:
itkSetMacro(InputReceptiveFields, SizeListType);
itkGetMacro(InputReceptiveFields, SizeListType);
+ /** Use no-data */
+ itkSetMacro(InputUseNodata, BoolListType);
+ itkGetMacro(InputUseNodata, BoolListType);
+
+ /** No-data value */
+ itkSetMacro(InputNodataValues, ValueListType);
+ itkGetMacro(InputNodataValues, ValueListType);
+
/** Output tensors names */
itkSetMacro(OutputTensors, StringList);
itkGetMacro(OutputTensors, StringList);
@@ -172,8 +188,11 @@ protected:
GenerateDebugReport(DictType & inputs);
virtual void
- RunSession(DictType & inputs, TensorListType & outputs);
+ RunSession(DictType & inputs, TensorListType & outputs, bool & nodata);
+ virtual void
+ RunSession(DictType & inputs, TensorListType & outputs);
+
private:
TensorflowMultisourceModelBase(const Self &); // purposely not implemented
void
@@ -183,12 +202,14 @@ private:
tensorflow::SavedModelBundle * m_SavedModel; // The TensorFlow model
// Model parameters
- 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 nodes target
+ StringList m_InputPlaceholders; // Input placeholders names
+ SizeListType m_InputReceptiveFields; // Input receptive fields
+ ValueListType m_InputNodataValues; // Input no-data values
+ BoolListType m_InputUseNodata; // Input no-data used
+ StringList m_OutputTensors; // Output tensors names
+ SizeListType m_OutputExpressionFields; // Output expression fields
+ DictType m_UserPlaceholders; // User placeholders
+ StringList m_TargetNodesNames; // User nodes target
// Internal, read-only
DataTypeListType m_InputConstantsDataTypes; // Input constants datatype
diff --git a/include/otbTensorflowMultisourceModelBase.hxx b/include/otbTensorflowMultisourceModelBase.hxx
index ba4612627381d01991dbd5c5d050e8c197c1f851..d9d6d7c69db553a8439fcf3a3939a1b910a62b93 100644
--- a/include/otbTensorflowMultisourceModelBase.hxx
+++ b/include/otbTensorflowMultisourceModelBase.hxx
@@ -55,13 +55,18 @@ TensorflowMultisourceModelBase<TInputImage, TOutputImage>::GetSignatureDef()
template <class TInputImage, class TOutputImage>
void
-TensorflowMultisourceModelBase<TInputImage, TOutputImage>::PushBackInputTensorBundle(std::string placeholder,
- SizeType receptiveField,
- ImagePointerType image)
+TensorflowMultisourceModelBase<TInputImage, TOutputImage>::PushBackInputTensorBundle(
+ std::string placeholder,
+ SizeType receptiveField,
+ ImagePointerType image,
+ bool useNodata,
+ InternalPixelType nodataValue)
{
Superclass::PushBackInput(image);
m_InputReceptiveFields.push_back(receptiveField);
m_InputPlaceholders.push_back(placeholder);
+ m_InputUseNodata.push_back(useNodata);
+ m_InputNodataValues.push_back(nodataValue);
}
template <class TInputImage, class TOutputImage>
@@ -96,10 +101,9 @@ TensorflowMultisourceModelBase<TInputImage, TOutputImage>::GenerateDebugReport(D
return debugReport;
}
-
template <class TInputImage, class TOutputImage>
void
-TensorflowMultisourceModelBase<TInputImage, TOutputImage>::RunSession(DictType & inputs, TensorListType & outputs)
+TensorflowMultisourceModelBase<TInputImage, TOutputImage>::RunSession(DictType & inputs, TensorListType & outputs, bool & nodata)
{
// Run the TF session here
@@ -119,10 +123,28 @@ TensorflowMultisourceModelBase<TInputImage, TOutputImage>::RunSession(DictType &
}
// Add input tensors
+ // During this step we also check for nodata values
+ nodata = false;
k = 0;
for (auto & dict : inputs)
{
- inputs_new.emplace_back(m_InputLayers[k], dict.second);
+ auto inputTensor = dict.second;
+ inputs_new.emplace_back(m_InputLayers[k], inputTensor);
+ if (m_InputUseNodata[k] == true)
+ {
+ const auto nodataValue = m_InputNodataValues[k];
+ const tensorflow::int64 nElmT = inputTensor.NumElements();
+ tensorflow::int64 ndCount = 0;
+ auto array = inputTensor.flat<InternalPixelType>();
+ for (tensorflow::int64 i = 0 ; i < nElmT ; i++)
+ if (array(i) == nodataValue)
+ ndCount++;
+ if (ndCount == nElmT)
+ {
+ nodata = true;
+ return;
+ }
+ }
k += 1;
}
@@ -140,11 +162,19 @@ TensorflowMultisourceModelBase<TInputImage, TOutputImage>::RunSession(DictType &
<< "Tensorflow error message:\n"
<< status.ToString()
<< "\n"
- "OTB Filter debug message:\n"
+ "OTB Filter debug message:\n"
<< debugReport.str());
}
}
+template <class TInputImage, class TOutputImage>
+void
+TensorflowMultisourceModelBase<TInputImage, TOutputImage>::RunSession(DictType & inputs, TensorListType & outputs)
+{
+ bool nodata;
+ this->RunSession(inputs, outputs, nodata);
+}
+
template <class TInputImage, class TOutputImage>
void
TensorflowMultisourceModelBase<TInputImage, TOutputImage>::GenerateOutputInformation()
@@ -162,6 +192,18 @@ TensorflowMultisourceModelBase<TInputImage, TOutputImage>::GenerateOutputInforma
<< " and the number of input tensors names is " << m_InputPlaceholders.size());
}
+ // Check that no-data values size is consistent with the inputs
+ // If no value is specified, set a vector of the same size as the inputs
+ if (m_InputNodataValues.size() == 0 && m_InputUseNodata.size() == 0)
+ {
+ m_InputUseNodata = BoolListType(nbInputs, false);
+ m_InputNodataValues = ValueListType(nbInputs, 0.0);
+ }
+ if (nbInputs != m_InputNodataValues.size() || nbInputs != m_InputUseNodata.size())
+ {
+ itkExceptionMacro("Number of input images is " << nbInputs << " but the number of no-data values is not consistent");
+ }
+
//////////////////////////////////////////////////////////////////////////////////////////
// Get tensors information
//////////////////////////////////////////////////////////////////////////////////////////
diff --git a/include/otbTensorflowMultisourceModelFilter.h b/include/otbTensorflowMultisourceModelFilter.h
index bdf9a02d0b00e9dbc228f3a0401ac8dab4c49e32..ce855b2858605187d09a75eb8c93f9eaa9f841b1 100644
--- a/include/otbTensorflowMultisourceModelFilter.h
+++ b/include/otbTensorflowMultisourceModelFilter.h
@@ -132,6 +132,8 @@ public:
itkGetMacro(FullyConvolutional, bool);
itkSetMacro(OutputSpacingScale, float);
itkGetMacro(OutputSpacingScale, float);
+ itkSetMacro(OutputBackgroundValue, OutputInternalPixelType);
+ itkGetMacro(OutputBackgroundValue, OutputInternalPixelType);
protected:
TensorflowMultisourceModelFilter();
@@ -162,17 +164,18 @@ private:
void
operator=(const Self &); // purposely not implemented
- SizeType m_OutputGridSize; // Output grid size
- bool m_ForceOutputGridSize; // Force output grid size
- bool m_FullyConvolutional; // Convolution mode
- float m_OutputSpacingScale; // scaling of the output spacings
+ SizeType m_OutputGridSize; // Output grid size
+ bool m_ForceOutputGridSize; // Force output grid size
+ bool m_FullyConvolutional; // Convolution mode
+ float m_OutputSpacingScale; // scaling of the output spacings
+ OutputInternalPixelType m_OutputBackgroundValue; // Output background value
// Internal
- SpacingType m_OutputSpacing; // Output image spacing
- PointType m_OutputOrigin; // Output image origin
- SizeType m_OutputSize; // Output image size
- PixelType m_NullPixel; // Pixel filled with zeros
-
+ SpacingType m_OutputSpacing; // Output image spacing
+ PointType m_OutputOrigin; // Output image origin
+ SizeType m_OutputSize; // Output image size
+ PixelType m_NullPixel; // Pixel filled with zeros
+
}; // end class
diff --git a/include/otbTensorflowMultisourceModelFilter.hxx b/include/otbTensorflowMultisourceModelFilter.hxx
index 3cbb53d92857466d617e5547940c8e42a0ce971e..0f32334ce18c3ef4ad25e8a30ab9a5e614973728 100644
--- a/include/otbTensorflowMultisourceModelFilter.hxx
+++ b/include/otbTensorflowMultisourceModelFilter.hxx
@@ -302,7 +302,7 @@ TensorflowMultisourceModelFilter<TInputImage, TOutputImage>::GenerateOutputInfor
// Set null pixel
m_NullPixel.SetSize(outputPtr->GetNumberOfComponentsPerPixel());
- m_NullPixel.Fill(0);
+ m_NullPixel.Fill(m_OutputBackgroundValue);
//////////////////////////////////////////////////////////////////////////////////////////
// Set the tiling layout hint in metadata
@@ -470,31 +470,35 @@ TensorflowMultisourceModelFilter<TInputImage, TOutputImage>::GenerateData()
// Run session
// TODO: see if we print some info about inputs/outputs of the model e.g. m_OutputTensors
TensorListType outputs;
- this->RunSession(inputs, outputs);
+ bool nodata;
+ this->RunSession(inputs, outputs, nodata);
// Fill the output buffer with zero value
outputPtr->SetBufferedRegion(outputReqRegion);
outputPtr->Allocate();
outputPtr->FillBuffer(m_NullPixel);
- // Get output tensors
- int bandOffset = 0;
- for (unsigned int i = 0; i < outputs.size(); i++)
+ if (nodata == false)
{
- // The offset (i.e. the starting index of the channel for the output tensor) is updated
- // during this call
- // TODO: implement a generic strategy enabling expression field copy in patch-based mode (see
- // tf::CopyTensorToImageRegion)
- try
+ // Get output tensors
+ int bandOffset = 0;
+ for (unsigned int i = 0; i < outputs.size(); i++)
{
- tf::CopyTensorToImageRegion<TOutputImage>(
- outputs[i], outputAlignedReqRegion, outputPtr, outputReqRegion, bandOffset);
- }
- catch (itk::ExceptionObject & err)
- {
- std::stringstream debugMsg = this->GenerateDebugReport(inputs);
- itkExceptionMacro("Error occurred during tensor to image conversion.\n"
- << "Context: " << debugMsg.str() << "Error:" << err);
+ // The offset (i.e. the starting index of the channel for the output tensor) is updated
+ // during this call
+ // TODO: implement a generic strategy enabling expression field copy in patch-based mode (see
+ // tf::CopyTensorToImageRegion)
+ try
+ {
+ tf::CopyTensorToImageRegion<TOutputImage>(
+ outputs[i], outputAlignedReqRegion, outputPtr, outputReqRegion, bandOffset);
+ }
+ catch (itk::ExceptionObject & err)
+ {
+ std::stringstream debugMsg = this->GenerateDebugReport(inputs);
+ itkExceptionMacro("Error occurred during tensor to image conversion.\n"
+ << "Context: " << debugMsg.str() << "Error:" << err);
+ }
}
}
}
diff --git a/setup.py b/setup.py
index 958be96a107e5d9a145e5b0ad5b47776820f0204..1feeff9c270b86fa03cb7c43ca00956cac4de97f 100644
--- a/setup.py
+++ b/setup.py
@@ -6,7 +6,7 @@ with open("README.md", "r", encoding="utf-8") as fh:
setuptools.setup(
name="otbtf",
- version="4.0.0",
+ version="4.1.0",
author="Remi Cresson",
author_email="remi.cresson@inrae.fr",
description="OTBTF: Orfeo ToolBox meets TensorFlow",
diff --git a/test/data/nd_out.tif b/test/data/nd_out.tif
new file mode 100644
index 0000000000000000000000000000000000000000..4997afd6842ca1613b530316d797d790647ea2ba
--- /dev/null
+++ b/test/data/nd_out.tif
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ec7c74cf9da7d187390078e554098350b33307b06ce6738b7b635fb068d78b84
+size 1411
diff --git a/test/nodata_test.py b/test/nodata_test.py
new file mode 100644
index 0000000000000000000000000000000000000000..c3892153401d26f000b82da59547dcbc8c890ea7
--- /dev/null
+++ b/test/nodata_test.py
@@ -0,0 +1,76 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+import otbApplication
+import pytest
+import tensorflow as tf
+import unittest
+
+import otbtf
+from test_utils import resolve_paths, compare
+
+
+class NodataInferenceTest(unittest.TestCase):
+
+ def test_infersimple(self):
+ """
+ In this test, we create a synthetic image:
+ f(x, y) = x * y if x > y else 0
+
+ Then we use an input no-data value (`source1.nodata 0`) and a
+ background value for the output (`output.bv 1024`).
+
+ We use the l2_norm SavedModel, forcing otbtf to use a tiling scheme
+ of 4x4. If the test succeeds, the output pixels in 4x4 areas where
+ there is at least one no-data pixel (i.e. 0), should be filled with
+ the `bv` value (i.e. 1024).
+
+ """
+ sm_dir = resolve_paths("$TMPDIR/l2_norm_savedmodel")
+
+ # Create model
+ x = tf.keras.Input(shape=[None, None, None], name="x")
+ y = tf.norm(x, axis=-1)
+ model = tf.keras.Model(inputs={"x": x}, outputs={"y": y})
+ model.save(sm_dir)
+
+ # Input image: f(x, y) = x * y if x > y else 0
+ bmx = otbApplication.Registry.CreateApplication("BandMathX")
+ bmx.SetParameterString("exp", "{idxX>idxY?idxX*idxY:0}")
+ bmx.SetParameterStringList(
+ "il", [resolve_paths("$DATADIR/xs_subset.tif")]
+ )
+ bmx.Execute()
+
+ infer = otbApplication.Registry.CreateApplication(
+ "TensorflowModelServe"
+ )
+ infer.SetParameterString("model.dir", sm_dir)
+ infer.SetParameterString("model.fullyconv", "on")
+ infer.AddImageToParameterInputImageList(
+ "source1.il", bmx.GetParameterOutputImage("out")
+ )
+ infer.SetParameterFloat("source1.nodata", 0.0)
+ for param in [
+ "source1.rfieldx",
+ "source1.rfieldy",
+ "output.efieldx",
+ "output.efieldy",
+ "optim.tilesizex",
+ "optim.tilesizey",
+ ]:
+ infer.SetParameterInt(param, 4)
+
+ infer.SetParameterFloat("output.bv", 1024)
+ infer.SetParameterString("out", resolve_paths("$TMPDIR/nd_out.tif"))
+ infer.ExecuteAndWriteOutput()
+
+ self.assertTrue(
+ compare(
+ raster1=resolve_paths("$TMPDIR/nd_out.tif"),
+ raster2=resolve_paths("$DATADIR/nd_out.tif"),
+ )
+ )
+
+
+if __name__ == '__main__':
+ unittest.main()
diff --git a/tools/docker/build-env-tf.sh b/tools/docker/build-env-tf.sh
index ff5c569210f66540df2872f73db0facd756dfd6e..4eb7c7ff56e4ba0e998715f4fe3ffb3314098845 100644
--- a/tools/docker/build-env-tf.sh
+++ b/tools/docker/build-env-tf.sh
@@ -34,6 +34,16 @@ export TF_NEED_ROCM=0
export TF_NEED_CUDA=0
export CUDA_TOOLKIT_PATH=$(find /usr/local -maxdepth 1 -type d -name 'cuda-*')
if [ ! -z $CUDA_TOOLKIT_PATH ] ; then
+ if [ ! -z $TENSORRT ]; then
+ echo "Building tensorflow with TensorRT support"
+ apt install \
+ libnvinfer8=$TENSORRT \
+ libnvinfer-dev=$TENSORRT \
+ libnvinfer-plugin8=$TENSORRT \
+ libnvinfer-plugin-dev=$TENSORRT
+ export TF_TENSORRT_VERSION=$(cat $(find /usr/ -type f -name NvInferVersion.h) | grep '#define NV_TENSORRT_MAJOR' | cut -f3 -d' ')
+ export TF_NEED_TENSORRT=1
+ fi
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$CUDA_TOOLKIT_PATH/lib64:$CUDA_TOOLKIT_PATH/lib64/stubs"
export TF_CUDA_VERSION=$(echo $CUDA_TOOLKIT_PATH | sed -r 's/.*\/cuda-(.*)/\1/')
export TF_CUDA_COMPUTE_CAPABILITIES="5.2,6.1,7.0,7.5,8.6"
@@ -41,6 +51,6 @@ if [ ! -z $CUDA_TOOLKIT_PATH ] ; then
export TF_CUDA_CLANG=0
export TF_NEED_TENSORRT=0
export CUDNN_INSTALL_PATH="/usr/"
- export TF_CUDNN_VERSION=$(sed -n 's/^#define CUDNN_MAJOR\s*\(.*\).*/\1/p' $CUDNN_INSTALL_PATH/include/cudnn.h)
+ export TF_CUDNN_VERSION=$(sed -n 's/^#define CUDNN_MAJOR\s*\(.*\).*/\1/p' $CUDNN_INSTALL_PATH/include/cudnn_version.h)
export TF_NCCL_VERSION=2
fi