ASL demo internal PR

.gitmodules

@@ -0,0 +1,3 @@
+[submodule "demos/thirdparty/gflags"]
+	path = demos/thirdparty/gflags
+	url = https://github.com/gflags/gflags/

CONTRIBUTING.md

@@ -13,7 +13,7 @@ Open Model Zoo also supports models already in the ONNX format.
 
 ## Pull Request Requirements
 
-To contribute to OMZ, create a pull request (PR) in this repository using the `develop` branch.
+To contribute to OMZ, create a pull request (PR) in this repository using the `master` branch.
 Pull requests are strictly formalized and are reviewed by the OMZ maintainers for consistence and legal compliance.
 
 Each PR contributing a model must contain:
@@ -86,10 +86,10 @@ Downloadable files. Each file is described by:
 
 * `name` - sets a file name after downloading
 * `size` - sets a file size
-* `sha256`  - sets a file hash sum
+* `sha384`  - sets a file hash sum
 * `source` - sets a direct link to a file *OR* describes a file access parameters
 
-> **TIP**: You can obtain a hash sum using the `sha256sum <file_name>` command on Linux\*.
+> **TIP**: You can obtain a hash sum using the `sha384sum <file_name>` command on Linux\*.
 
 If file is located on Google Drive\*, the `source` section must contain:
 - `$type: google_drive`
@@ -155,7 +155,7 @@ task_type: classification
 files:
   - name: tf-densenet121.tar.gz
     size: 30597420
-    sha256: b31ec840358f1d20e1c6364d05ce463cb0bc0480042e663ad54547189501852d
+    sha384: dcd6d36f6b07e0843ee35b1dce2c587204c8816d6ba25b7e1dbf2dc25fe2b51f49a2b9327579ce07904575f9325be8b6
     source:
       $type: google_drive
       id: 0B_fUSpodN0t0eW1sVk1aeWREaDA

ci/documentation_updater/documentation_updater.py

@@ -113,7 +113,7 @@ def get_models_from_configs(directory):
     model_configs = directory.glob('**/model.yml')
     for model in model_configs:
         with model.open("r", encoding="utf-8") as file:
-            models[model.parent.name] = (model, yaml.load(file))
+            models[model.parent.name] = (model, yaml.safe_load(file))
         if not models[model.parent.name][1]:
             logging.error("File {} is empty. It will be ignored.".format(model))
             del models[model.parent.name]

ci/prepare-openvino-content.py

@@ -93,7 +93,7 @@ def file_is_in_current_package(path):
     # copy appropriate files to each component
 
     for component_name, component_files in files_per_component.items():
-        component_output_dir = args.output_dir / component_name / 'deployment_tools/open_model_zoo'
+        component_output_dir = args.output_dir / component_name / 'extras/open_model_zoo'
         component_output_dir.mkdir(parents=True, exist_ok=True)
 
         subprocess.run(
@@ -109,18 +109,18 @@ def file_is_in_current_package(path):
         ['git', '-C', str(OMZ_ROOT), 'rev-parse', 'HEAD'])
     omz_commit = rev_parse_output.decode().rstrip('\n')
 
-    version_txt_path = args.output_dir / 'tools/deployment_tools/open_model_zoo/version.txt'
+    version_txt_path = args.output_dir / 'tools/extras/open_model_zoo/version.txt'
 
     with open(version_txt_path, 'w', newline=eol_chars) as version_txt_file:
         print(omz_commit, file=version_txt_file)
 
     # create compatibility symlinks
 
     compat_symlinks = [
-        ('deployment_tools/intel_models', 'open_model_zoo/models/intel'),
-        ('deployment_tools/open_model_zoo/intel_models', 'models/intel'),
-        ('deployment_tools/tools/model_downloader', '../open_model_zoo/tools/model_tools'),
-        ('deployment_tools/inference_engine/demos', '../open_model_zoo/demos'),
+        ('extras/intel_models', 'open_model_zoo/models/intel'),
+        ('extras/open_model_zoo/intel_models', 'models/intel'),
+        ('extras/tools/model_downloader', '../open_model_zoo/tools/model_tools'),
+        ('extras/inference_engine/demos', '../open_model_zoo/demos'),
     ]
 
     for link_source, link_target in compat_symlinks:

ci/requirements-downloader.txt

@@ -6,6 +6,8 @@ charset-normalizer==2.0.4
     # via requests
 idna==3.2
     # via requests
+pyrx==0.3.0
+    # via -r tools/model_tools/requirements.in
 pyyaml==5.4.1
     # via -r tools/model_tools/requirements.in
 requests==2.26.0

data/dataset_definitions.yml

@@ -2,7 +2,7 @@ datasets:
   - name: ms_coco_mask_rcnn
     annotation_conversion:
       converter: mscoco_mask_rcnn
-      annotation_file: instances_val2017.json
+      annotation_file: annotations/instances_val2017.json
       has_background: True
       sort_annotations: True
     annotation: mscoco_mask_rcnn.pickle
@@ -12,7 +12,7 @@ datasets:
   - name: ms_coco_mask_rcnn_short_80_classes
     annotation_conversion:
       converter: mscoco_mask_rcnn
-      annotation_file: instances_val2017_short.json
+      annotation_file: annotations/instances_val2017_short.json
       has_background: True
       sort_annotations: True
     annotation: mscoco_mask_rcnn_short_80.pickle
@@ -22,7 +22,7 @@ datasets:
   - name: ms_coco_mask_rcnn_short_80_classes_without_background
     annotation_conversion:
       converter: mscoco_mask_rcnn
-      annotation_file: instances_val2017.json
+      annotation_file: annotations/instances_val2017.json
       has_background: False
       sort_annotations: True
     annotation: mscoco_mask_rcnn_short_80_without_bkgr.pickle
@@ -32,7 +32,7 @@ datasets:
   - name: ms_coco_mask_rcnn_short_91_classes
     annotation_conversion:
       converter: mscoco_mask_rcnn
-      annotation_file: instances_val2017_short.json
+      annotation_file: annotations/instances_val2017_short.json
       has_background: True
       sort_annotations: True
       use_full_label_map: True
@@ -57,7 +57,7 @@ datasets:
   - name: ms_coco_detection_91_classes
     annotation_conversion:
       converter: mscoco_detection
-      annotation_file: instances_val2017.json
+      annotation_file: annotations/instances_val2017.json
       has_background: True
       sort_annotations: True
       use_full_label_map: True
@@ -83,7 +83,7 @@ datasets:
     data_source: val2017
     annotation_conversion:
       converter: mscoco_detection
-      annotation_file: instances_val2017.json
+      annotation_file: annotations/instances_val2017.json
       has_background: False
       sort_annotations: True
       use_full_label_map: False
@@ -94,18 +94,18 @@ datasets:
     data_source: val2017
     annotation_conversion:
       converter: mscoco_detection
-      annotation_file: instances_val2017.json
+      annotation_file: annotations/instances_val2017.json
       has_background: True
       sort_annotations: True
       use_full_label_map: False
     annotation: mscoco_det_80_bkgr.pickle
     dataset_meta: mscoco_det_80_bkgr.json
 
   - name: ms_coco_detection_90_class_without_background
-    data_source: MSCOCO/val2017
+    data_source: val2017
     annotation_conversion:
       converter: mscoco_detection
-      annotation_file: MSCOCO/annotations/instances_val2017.json
+      annotation_file: annotations/instances_val2017.json
       has_background: False
       sort_annotations: True
       use_full_label_map: True
@@ -116,7 +116,7 @@ datasets:
     data_source: val2017
     annotation_conversion:
       converter: mscoco_keypoints
-      annotation_file: person_keypoints_val2017.json
+      annotation_file: annotations/person_keypoints_val2017.json
       sort_key: image_size
     annotation: mscoco_keypoints.pickle
     dataset_meta: mscoco_keypoints.json
@@ -129,7 +129,7 @@ datasets:
     data_source: val2017
     annotation_conversion:
       converter: mscoco_keypoints
-      annotation_file: person_keypoints_val2017.json
+      annotation_file: annotations/person_keypoints_val2017.json
       remove_empty_images: True
       sort_annotations: True
       sort_key: image_size
@@ -144,7 +144,7 @@ datasets:
     data_source: val2017
     annotation_conversion:
       converter: mscoco_keypoints
-      annotation_file: person_keypoints_val2017.json
+      annotation_file: annotations/person_keypoints_val2017.json
       remove_empty_images: False
       sort_annotations: True
       sort_key: image_size
@@ -289,6 +289,17 @@ datasets:
     postprocessing:
       - type: normalize_landmarks_points
 
+  - name: facial_landmarks_98_db
+    data_source: 98_landmarks
+    annotation_conversion:
+      converter: coco_facial_landmarks
+      annotation_file: 98_landmarks/lms_test.json
+    preprocessing:
+      - type: resize
+        size: 64
+    postprocessing:
+      - type: normalize_landmarks_points
+
   - name: emotions_recognition
     data_source: VOCdevkit/VOC2012/JPEGImages
     annotation_conversion:
@@ -388,7 +399,7 @@ datasets:
     data_source: val2017
     annotation_conversion:
       converter: mscoco_detection
-      annotation_file: person_keypoints_val2017.json
+      annotation_file: annotations/person_keypoints_val2017.json
       has_background: True
       sort_annotations: True
       use_full_label_map: True
@@ -399,7 +410,7 @@ datasets:
     data_source: val2017
     annotation_conversion:
       converter: mscoco_detection
-      annotation_file: person_keypoints_val2017.json
+      annotation_file: annotations/person_keypoints_val2017.json
       has_background: True
       sort_annotations: True
       use_full_label_map: True
@@ -946,7 +957,7 @@ datasets:
     data_source: val2017
     annotation_conversion:
       converter: mscoco_single_keypoints
-      annotation_file: person_keypoints_val2017.json
+      annotation_file: annotations/person_keypoints_val2017.json
     annotation: mscoco_single_keypoints.pickle
     dataset_meta: mscoco_single_keypoints.json
     metrics:
@@ -1399,3 +1410,11 @@ datasets:
       data_dir: wavernn_io/rnn
       input_suffix: in
       reference_suffix: out
+
+  - name: LIVE_1
+    data_source: LIVE_1
+    annotation_conversion:
+      converter: image_processing
+      data_dir: LIVE_1
+      input_suffix: .bmp
+      target_suffix: .bmp

data/datasets.md

@@ -56,8 +56,9 @@ To download COCO dataset, you need to follow the steps below:
 To use this dataset with OMZ tools, make sure `<DATASET_DIR>` contains the following:
 
 * `val2017` - directory containing the COCO 2017 validation images
-* `instances_val2017.json` - annotation file which used for object detection and instance segmentation tasks
-* `person_keypoints_val2017.json` - annotation file which used for human pose estimation tasks
+* `annotations` - directory containing the COCO 2017 annotation files
+  * `instances_val2017.json` - annotation file which used for object detection and instance segmentation tasks
+  * `person_keypoints_val2017.json` - annotation file which used for human pose estimation tasks
 
 ### Datasets in dataset_definitions.yml
 * `ms_coco_mask_rcnn` used for evaluation models trained on COCO dataset for object detection and instance segmentation tasks. Background label + label map with 80 public available object categories are used. Annotations are saved in order of ascending image ID.

demos/3d_segmentation_demo/python/README.md

@@ -6,7 +6,7 @@ This topic demonstrates how to run the 3D Segmentation Demo, which segments 3D i
 
 On startup, the demo reads command-line parameters and loads a network and images to the Inference Engine plugin.
 
-> **NOTE**: By default, Open Model Zoo 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 demo application or reconvert your model using the Model Optimizer tool with the `--reverse_input_channels` argument specified. For more information about the argument, refer to **When to Reverse Input Channels** section of [Converting a Model Using General Conversion Parameters](https://docs.openvinotoolkit.org/latest/_docs_MO_DG_prepare_model_convert_model_Converting_Model_General.html).
+> **NOTE**: By default, Open Model Zoo 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 demo application or reconvert your model using the Model Optimizer tool with the `--reverse_input_channels` argument specified. For more information about the argument, refer to **When to Reverse Input Channels** section of [Converting a Model Using General Conversion Parameters](https://docs.openvino.ai/latest/openvino_docs_MO_DG_prepare_model_convert_model_Converting_Model.html#general-conversion-parameters).
 
 ## Preparing to Run
 

demos/CMakeLists.txt

@@ -73,15 +73,15 @@ set(CMAKE_CXX_STANDARD 11)
 set(CMAKE_CXX_STANDARD_REQUIRED ON)
 set(CMAKE_POSITION_INDEPENDENT_CODE ON)
 
-function(add_samples_to_build)
-    # check each passed sample subdirectory
+function(add_demos_to_build)
+    # check each passed demo subdirectory
     foreach(dir ${ARGN})
         if(IS_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/${dir})
             # check if a subdirectory contains CMakeLists.txt. In this case we can build it.
             file(GLOB sub_dirs ${CMAKE_CURRENT_SOURCE_DIR}/${dir}/*)
             foreach(sub_dir ${sub_dirs})
                 if(EXISTS "${sub_dir}/CMakeLists.txt")
-                    # check if specified sample/demo is found.
+                    # check if specified demo is found.
                     if(BUILD_SAMPLE_NAME)
                         list(FIND BUILD_SAMPLE_NAME ${dir} index)
                     endif()
@@ -103,36 +103,42 @@ include(CMakeParseArguments)
 #     SOURCES <source files>
 #     [HEADERS <header files>]
 #     [INCLUDE_DIRECTORIES <include dir>]
+#     [OPENCV_VERSION_REQUIRED <X.Y.Z>]
 #     [DEPENDENCIES <dependencies>])
 macro(add_demo)
-    set(oneValueArgs NAME)
+    set(oneValueArgs NAME OPENCV_VERSION_REQUIRED)
     set(multiValueArgs SOURCES HEADERS DEPENDENCIES INCLUDE_DIRECTORIES)
-    cmake_parse_arguments(IE_SAMPLE "${options}" "${oneValueArgs}"
+    cmake_parse_arguments(OMZ_DEMO "${options}" "${oneValueArgs}"
                           "${multiValueArgs}" ${ARGN})
 
+    if(OMZ_DEMO_OPENCV_VERSION_REQUIRED AND OpenCV_VERSION VERSION_LESS OMZ_DEMO_OPENCV_VERSION_REQUIRED)
+        message(WARNING "${OMZ_DEMO_NAME} is disabled; required OpenCV version ${OMZ_DEMO_OPENCV_VERSION_REQUIRED}, provided ${OpenCV_VERSION}")
+        return()
+    endif()
+
     # Create named folders for the sources within the .vcproj
     # Empty name lists them directly under the .vcproj
-    source_group("src" FILES ${IE_SAMPLE_SOURCES})
-    if(IE_SAMPLE_HEADERS)
-        source_group("include" FILES ${IE_SAMPLE_HEADERS})
+    source_group("src" FILES ${OMZ_DEMO_SOURCES})
+    if(OMZ_DEMO_HEADERS)
+        source_group("include" FILES ${OMZ_DEMO_HEADERS})
     endif()
 
     # Create executable file from sources
-    add_executable(${IE_SAMPLE_NAME} ${IE_SAMPLE_SOURCES} ${IE_SAMPLE_HEADERS})
+    add_executable(${OMZ_DEMO_NAME} ${OMZ_DEMO_SOURCES} ${OMZ_DEMO_HEADERS})
 
     if(WIN32)
-        set_target_properties(${IE_SAMPLE_NAME} PROPERTIES COMPILE_PDB_NAME ${IE_SAMPLE_NAME})
+        set_target_properties(${OMZ_DEMO_NAME} PROPERTIES COMPILE_PDB_NAME ${OMZ_DEMO_NAME})
     endif()
 
-    if(IE_SAMPLE_INCLUDE_DIRECTORIES)
-        target_include_directories(${IE_SAMPLE_NAME} PRIVATE ${IE_SAMPLE_INCLUDE_DIRECTORIES})
+    if(OMZ_DEMO_INCLUDE_DIRECTORIES)
+        target_include_directories(${OMZ_DEMO_NAME} PRIVATE ${OMZ_DEMO_INCLUDE_DIRECTORIES})
     endif()
 
-    target_link_libraries(${IE_SAMPLE_NAME} PRIVATE ${OpenCV_LIBRARIES} ${InferenceEngine_LIBRARIES}
-                                                    ${IE_SAMPLE_DEPENDENCIES} ngraph::ngraph utils gflags)
+    target_link_libraries(${OMZ_DEMO_NAME} PRIVATE ${OpenCV_LIBRARIES} ${InferenceEngine_LIBRARIES}
+                                                    ${OMZ_DEMO_DEPENDENCIES} ngraph::ngraph utils gflags)
 
     if(UNIX)
-        target_link_libraries(${IE_SAMPLE_NAME} PRIVATE pthread)
+        target_link_libraries(${OMZ_DEMO_NAME} PRIVATE pthread)
     endif()
 endmacro()
 
@@ -142,13 +148,14 @@ find_package(ngraph REQUIRED)
 
 add_subdirectory(thirdparty/gflags)
 add_subdirectory(common/cpp)
+add_subdirectory(common/cpp_gapi)
 add_subdirectory(multi_channel_common/cpp)
 
 # collect all samples subdirectories
 file(GLOB samples_dirs RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} *)
 # skip building of unnecessary subdirectories
 list(REMOVE_ITEM samples_dirs common thirdparty multi_channel_common)
-add_samples_to_build(${samples_dirs})
+add_demos_to_build(${samples_dirs})
 
 if(ENABLE_PYTHON)
     find_package(PythonInterp 3.6 REQUIRED)