Merge remote-tracking branch 'upstream/master' into ak/model_api_2.0

Author: akorobeinikov

CONTRIBUTING.md

@@ -214,7 +214,7 @@ This example uses validation configuration file for [DenseNet-121](models/public
 models:
   - name: densenet-121-tf
     launchers:
-      - framework: dlsdk
+      - framework: openvino
         adapter: classification
 
     datasets:

ci/dependencies.yml

@@ -1,6 +1,6 @@
-opencv_linux: '2022.1.0.dev20220131'
-opencv_windows: '2022.1.0.dev20220131'
-openvino_linux: '2022.1.0.dev20220131'
-openvino_windows: '2022.1.0.dev20220131'
-wheel_linux: '2022.1.0.dev20220131-6386'
-wheel_windows: '2022.1.0.dev20220131-6386'
+opencv_linux: '20220210_0636-4.5.5_043'
+opencv_windows: '20220210_0636-4.5.5_043'
+openvino_linux: '2022.1.0.577'
+openvino_windows: '2022.1.0.577'
+wheel_linux: '2022.1.0.dev20220209-6562'
+wheel_windows: '2022.1.0.dev20220209-6562'

demos/action_recognition_demo/python/action_recognition_demo.py

@@ -88,7 +88,7 @@ def main():
     core = Core()
 
     if 'MYRIAD' in args.device:
-        myriad_config = {'VPU_HW_STAGES_OPTIMIZATION': 'YES'}
+        myriad_config = {'MYRIAD_ENABLE_HW_ACCELERATION': 'YES'}
         core.set_config(myriad_config, 'MYRIAD')
 
     decoder_target_device = 'CPU'

demos/background_subtraction_demo/cpp_gapi/main.cpp

@@ -6,6 +6,7 @@
 #include <utils/args_helper.hpp>
 #include <utils_gapi/stream_source.hpp>
 #include <utils/config_factory.h>
+#include <utils/ocv_common.hpp>
 
 #include <opencv2/gapi/streaming/cap.hpp>
 #include <opencv2/gapi/imgproc.hpp>
@@ -160,20 +161,13 @@ int main(int argc, char *argv[]) {
         cv::Size graphSize{static_cast<int>(frame_size.width / 4), 60};
         Presenter presenter(FLAGS_u, frame_size.height - graphSize.height - 10, graphSize);
 
-        /** Save output result **/
-        cv::VideoWriter videoWriter;
-        if (!FLAGS_o.empty() && !videoWriter.open(FLAGS_o, cv::VideoWriter::fourcc('M', 'J', 'P', 'G'),
-                                                  cap->fps(), frame_size)) {
-            throw std::runtime_error("Can't open video writer");
-        }
+        LazyVideoWriter videoWriter{FLAGS_o, cap->fps(), FLAGS_limit};
 
         bool isStart = true;
-        uint64_t curr_frame_num = 0;
         const auto startTime = std::chrono::steady_clock::now();
         pipeline.start();
 
         while(pipeline.pull(cv::gout(output))) {
-            ++curr_frame_num;
             presenter.drawGraphs(output);
             if (isStart) {
                 metrics.update(startTime, output, { 10, 22 }, cv::FONT_HERSHEY_COMPLEX,
@@ -185,10 +179,7 @@ int main(int argc, char *argv[]) {
                     0.65, { 200, 10, 10 }, 2, PerformanceMetrics::MetricTypes::FPS);
             }
 
-            if (videoWriter.isOpened() &&
-                (FLAGS_limit <= 0 || curr_frame_num <= FLAGS_limit)) {
-                videoWriter.write(output);
-            }
+            videoWriter.write(output);
 
             if (!FLAGS_no_show) {
                 cv::imshow(windowName, output);

demos/background_subtraction_demo/python/background_subtraction_demo.py

@@ -70,7 +70,7 @@ def build_argparser():
                       help='Optional. Background blur strength (by default with value 0 is not applied).')
     args.add_argument('--layout', type=str, default=None,
                       help='Optional. Model inputs layouts. '
-                           'Format "NCHW" or "<input1>:<layout1>,<input2>:<layout2>" in case of more than one input.'
+                           'Format "[<layout>]" or "<input1>[<layout1>],<input2>[<layout2>]" in case of more than one input.'
                            'To define layout you should use only capital letters')
 
     infer_args = parser.add_argument_group('Inference options')

demos/classification_benchmark_demo/cpp/README.md

@@ -45,6 +45,7 @@ omz_converter --list models.lst
 * googlenet-v1
 * googlenet-v1-tf
 * googlenet-v2
+* googlenet-v2-tf
 * googlenet-v3
 * googlenet-v3-pytorch
 * googlenet-v4-tf
@@ -59,6 +60,8 @@ omz_converter --list models.lst
 * mobilenet-v2-1.0-224
 * mobilenet-v2-1.4-224
 * mobilenet-v2-pytorch
+* mobilenet-v3-large-1.0-224-tf
+* mobilenet-v3-small-1.0-224-tf
 * nfnet-f0
 * octave-resnet-26-0.25
 * regnetx-3.2gf
@@ -67,6 +70,7 @@ omz_converter --list models.lst
 * repvgg-b3
 * resnest-50-pytorch
 * resnet-18-pytorch
+* resnet-34-pytorch
 * resnet-50-pytorch
 * resnet-50-tf
 * resnet18-xnor-binary-onnx-0001

demos/classification_benchmark_demo/cpp/models.lst

@@ -9,6 +9,7 @@ efficientnet-b0-pytorch
 googlenet-v1
 googlenet-v1-tf
 googlenet-v2
+googlenet-v2-tf
 googlenet-v3
 googlenet-v3-pytorch
 googlenet-v4-tf
@@ -23,6 +24,8 @@ mobilenet-v2
 mobilenet-v2-1.0-224
 mobilenet-v2-1.4-224
 mobilenet-v2-pytorch
+mobilenet-v3-large-1.0-224-tf
+mobilenet-v3-small-1.0-224-tf
 nfnet-f0
 octave-resnet-26-0.25
 regnetx-3.2gf
@@ -31,6 +34,7 @@ repvgg-b1
 repvgg-b3
 resnest-50-pytorch
 resnet-18-pytorch
+resnet-34-pytorch
 resnet-50-pytorch
 resnet-50-tf
 resnet18-xnor-binary-onnx-0001

demos/classification_demo/python/README.md

@@ -43,6 +43,7 @@ omz_converter --list models.lst
 * googlenet-v1
 * googlenet-v1-tf
 * googlenet-v2
+* googlenet-v2-tf
 * googlenet-v3
 * googlenet-v3-pytorch
 * googlenet-v4-tf
@@ -57,6 +58,8 @@ omz_converter --list models.lst
 * mobilenet-v2-1.0-224
 * mobilenet-v2-1.4-224
 * mobilenet-v2-pytorch
+* mobilenet-v3-large-1.0-224-tf
+* mobilenet-v3-small-1.0-224-tf
 * nfnet-f0
 * octave-resnet-26-0.25
 * regnetx-3.2gf
@@ -65,6 +68,7 @@ omz_converter --list models.lst
 * repvgg-b3
 * resnest-50-pytorch
 * resnet-18-pytorch
+* resnet-34-pytorch
 * resnet-50-pytorch
 * resnet-50-tf
 * resnet18-xnor-binary-onnx-0001

demos/classification_demo/python/models.lst

@@ -11,6 +11,7 @@ efficientnet-v2-s
 googlenet-v1
 googlenet-v1-tf
 googlenet-v2
+googlenet-v2-tf
 googlenet-v3
 googlenet-v3-pytorch
 googlenet-v4-tf
@@ -25,6 +26,8 @@ mobilenet-v2
 mobilenet-v2-1.0-224
 mobilenet-v2-1.4-224
 mobilenet-v2-pytorch
+mobilenet-v3-large-1.0-224-tf
+mobilenet-v3-small-1.0-224-tf
 nfnet-f0
 octave-resnet-26-0.25
 regnetx-3.2gf
@@ -33,6 +36,7 @@ repvgg-b1
 repvgg-b3
 resnest-50-pytorch
 resnet-18-pytorch
+resnet-34-pytorch
 resnet-50-pytorch
 resnet-50-tf
 resnet18-xnor-binary-onnx-0001

demos/common/cpp/utils/include/utils/common.hpp

@@ -296,11 +296,11 @@ void logCompiledModelInfo(
         for (const auto& device : devices) {
             try {
                 slog::info << "\tDevice: " << device << slog::endl;
-                std::string nstreams = compiledModel.get_property(device + "_THROUGHPUT_STREAMS").as<std::string>();
+                int32_t nstreams = compiledModel.get_property(ov::streams::num);
                 slog::info << "\t\tNumber of streams: " << nstreams << slog::endl;
                 if (device == "CPU") {
-                    std::string nthreads = compiledModel.get_property("CPU_THREADS_NUM").as<std::string>();
-                    slog::info << "\t\tNumber of threads: " << (nthreads == "0" ? "AUTO" : nthreads) << slog::endl;
+                    int32_t nthreads = compiledModel.get_property(ov::inference_num_threads);
+                    slog::info << "\t\tNumber of threads: " << (nthreads == 0 ? "AUTO" : std::to_string(nthreads)) << slog::endl;
                 }
             }
             catch (const ov::Exception&) {}
@@ -317,23 +317,23 @@ void logBasicModelInfo(const std::shared_ptr<ov::Model>& model) {
     ov::OutputVector outputs = model->outputs();
 
     slog::info << "inputs: " << slog::endl;
-    for (const ov::Output<ov::Node> input : inputs)
-    {
+    for (const ov::Output<ov::Node>& input : inputs) {
         const std::string name = input.get_any_name();
         const ov::element::Type type = input.get_element_type();
         const ov::PartialShape shape = input.get_partial_shape();
+        const ov::Layout layout = ov::layout::get_layout(input);
 
-        slog::info << name << ", " << type << ", " << shape << slog::endl;
+        slog::info << name << ", " << type << ", " << shape << ", " << layout.to_string() << slog::endl;
     }
 
     slog::info << "outputs: " << slog::endl;
-    for (const ov::Output<ov::Node> output : outputs)
-    {
+    for (const ov::Output<ov::Node>& output : outputs) {
         const std::string name = output.get_any_name();
         const ov::element::Type type = output.get_element_type();
         const ov::PartialShape shape = output.get_partial_shape();
+        const ov::Layout layout = ov::layout::get_layout(output);
 
-        slog::info << name << ", " << type << ", " << shape << slog::endl;
+        slog::info << name << ", " << type << ", " << shape << ", " << layout.to_string() << slog::endl;
     }
 
     return;