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Publishing 2019 R1.0.1 content
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6 files changed

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inference-engine/cmake/dependencies.cmake

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@@ -100,7 +100,7 @@ elseif(LINUX)
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ENVIRONMENT "TBBROOT")
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else(APPLE)
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RESOLVE_DEPENDENCY(TBB
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ARCHIVE_MAC "tbb2019_20190130_mac.tgz"
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ARCHIVE_MAC "tbb2019_20190414_mac.tgz"
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TARGET_PATH "${TEMP}/tbb"
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ENVIRONMENT "TBBROOT"
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VERSION_REGEX ".*_([a-z]*_([a-z0-9]+\\.)*[0-9]+).*")

inference-engine/cmake/features.cmake

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@@ -44,9 +44,15 @@ set (IE_DEBUG_POSTFIX_WIN "d")
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set (IE_RELEASE_POSTFIX_WIN "")
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set (IE_DEBUG_POSTFIX_LIN "")
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set (IE_RELEASE_POSTFIX_LIN "")
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set (IE_DEBUG_POSTFIX_MAC "d")
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set (IE_RELEASE_POSTFIX_MAC "")
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if (WIN32)
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set (IE_DEBUG_POSTFIX ${IE_DEBUG_POSTFIX_WIN})
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set (IE_RELEASE_POSTFIX ${IE_RELEASE_POSTFIX_WIN})
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elseif(APPLE)
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set (IE_DEBUG_POSTFIX ${IE_DEBUG_POSTFIX_MAC})
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set (IE_RELEASE_POSTFIX ${IE_RELEASE_POSTFIX_MAC})
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else()
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set (IE_DEBUG_POSTFIX ${IE_DEBUG_POSTFIX_LIN})
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set (IE_RELEASE_POSTFIX ${IE_RELEASE_POSTFIX_LIN})
@@ -94,6 +100,8 @@ ie_option (ENABLE_DEBUG_SYMBOLS "generates symbols for debugging" OFF)
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ie_option (ENABLE_PYTHON "enables ie python bridge build" OFF)
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ie_option (TREAT_WARNING_AS_ERROR "Treat build warnings as errors" ON)
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ie_option(ENABLE_CPPLINT "Enable cpplint checks during the build" OFF)
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ie_option(ENABLE_CPPLINT_REPORT "Build cpplint report instead of failing the build" OFF)
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inference-engine/cmake/share/InferenceEngineConfig.cmake.in

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@@ -108,6 +108,14 @@ else()
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FOUND_VAR INFERENCEENGINE_FOUND
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REQUIRED_VARS IE_RELEASE_LIBRARY IE_DEBUG_LIBRARY IE_INCLUDE_DIR
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FAIL_MESSAGE "Inference Engine cannot be found at ${_IE_ROOT_LIBRARY}. Please consult InferenceEgnineConfig.cmake module's help page.")
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elseif (APPLE)
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find_library(IE_RELEASE_LIBRARY inference_engine@IE_RELEASE_POSTFIX_MAC@ "${IE_LIB_DIR}")
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find_library(IE_DEBUG_LIBRARY inference_engine@IE_DEBUG_POSTFIX_MAC@ "${IE_LIB_DIR}")
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find_package_handle_standard_args( InferenceEngine
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FOUND_VAR INFERENCEENGINE_FOUND
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REQUIRED_VARS IE_RELEASE_LIBRARY IE_DEBUG_LIBRARY IE_INCLUDE_DIR
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FAIL_MESSAGE "Inference Engine cannot be found at ${_IE_ROOT_LIBRARY}. Please consult InferenceEgnineConfig.cmake module's help page.")
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else()
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find_library(IE_LIBRARY inference_engine@IE_RELEASE_POSTFIX_LIN@ "${IE_LIB_DIR}")
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find_package_handle_standard_args( InferenceEngine
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MAP_IMPORTED_CONFIG_RELEASE Release
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MAP_IMPORTED_CONFIG_RELWITHDEBINFO Release
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INTERFACE_INCLUDE_DIRECTORIES "${IE_INCLUDE_DIR}")
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elseif (APPLE)
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set_target_properties(IE::inference_engine PROPERTIES
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IMPORTED_LOCATION_RELEASE "${IE_RELEASE_LIBRARY}"
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IMPORTED_LOCATION_DEBUG "${IE_DEBUG_LIBRARY}"
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INTERFACE_INCLUDE_DIRECTORIES "${IE_INCLUDE_DIR}")
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target_link_libraries(IE::inference_engine INTERFACE ${CMAKE_DL_LIBS})
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else()
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set_target_properties(IE::inference_engine PROPERTIES
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IMPORTED_LOCATION "${IE_LIBRARY}"

inference-engine/samples/calibration_tool/README.md

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Inference Engine Calibration Tool calibrates a given FP32 model so that is can be run in low-precision 8-bit integer
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mode while keeping the input data of this model in the original precision.
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> **NOTE**: INT8 models are currently supported only by the CPU plugin. For the full list of supported configurations, see the [Supported Devices](./docs/IE_DG/supported_plugins/Supported_Devices.md) topic.
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> **NOTE**: By default, Inference Engine samples and demos expect input with BGR channels order. If you trained your model to work with RGB order, you need to manually rearrange the default channels order in the sample or demo application or reconvert your model using the Model Optimizer tool with `--reverse_input_channels` argument specified. For more information about the argument, refer to **When to Specify Input Shapes** section of [Converting a Model Using General Conversion Parameters](./docs/MO_DG/prepare_model/convert_model/Converting_Model_General.md).
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## Calibration Tool Options

inference-engine/samples/validation_app/README.md

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@@ -157,7 +157,7 @@ The correct way to use such dataset is to specify the path as `-i <path>/dataset
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### Dataset Format for Object Detection (VOC-like)
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Object Detection SSD models can be inferred on the original dataset that was used as a testing dataset during the model training.
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To prepare the VOC dataset, follow the steps below :
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To prepare the VOC dataset, follow the steps below:
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1. Download the pre-trained SSD-300 model from the SSD GitHub* repository at
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[https://github.com/weiliu89/caffe/tree/ssd](https://github.com/weiliu89/caffe/tree/ssd).
@@ -167,7 +167,7 @@ To prepare the VOC dataset, follow the steps below :
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$wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtest_06-Nov-2007.tar
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tar -xvf VOCtest_06-Nov-2007.tar
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```
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3. Convert the model with the [Model Optimizer](docs/MO_DG/prepare_model/convert_model/Convert_Model_From_Caffe.md).
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3. Convert the model with the [Model Optimizer](./docs/MO_DG/prepare_model/convert_model/Convert_Model_From_Caffe.md).
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4. Create a proper `.txt` class file from the original `labelmap_voc.prototxt`. The new file must be in
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the following format:

inference-engine/src/extension/CMakeLists.txt

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@@ -16,8 +16,11 @@ if (NOT(IE_MAIN_SOURCE_DIR))
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endif()
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endif()
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# treating warnings as errors
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if (WIN32)
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if (TREAT_WARNING_AS_ERROR)
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set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /WX") #treating warnings as errors
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endif ()
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if (${CMAKE_CXX_COMPILER_ID} STREQUAL MSVC)
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set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /wd4251 /wd4275 /wd4267") #disable some warnings
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endif()

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