Merge pull request #3104 from ivikhrev/ov2.0-cpp-model-api

OV2.0 c++ modelAPI demos

Author: Wovchena

demos/background_subtraction_demo/cpp_gapi/main.cpp

@@ -122,15 +122,15 @@ int main(int argc, char *argv[]) {
         });
 
         /** Configure network **/
-        auto config = ConfigFactory::getUserConfig(FLAGS_d, "", "", FLAGS_nireq,
+        auto config = ConfigFactory::getUserConfig(FLAGS_d, FLAGS_nireq,
                                                    FLAGS_nstreams, FLAGS_nthreads);
         const auto net = cv::gapi::ie::Params<cv::gapi::Generic> {
             model->getName(),
             FLAGS_m,                           // path to topology IR
             fileNameNoExt(FLAGS_m) + ".bin",   // path to weights
             FLAGS_d                            // device specifier
         }.cfgNumRequests(config.maxAsyncRequests)
-         .pluginConfig(config.execNetworkConfig);
+         .pluginConfig(config.getLegacyConfig());
         slog::info << "The background matting model " << FLAGS_m << " is loaded to " << FLAGS_d << " device." << slog::endl;
 
         auto kernels = cv::gapi::combine(custom::kernels(),

demos/classification_benchmark_demo/cpp/README.md

@@ -119,33 +119,7 @@ and `<omz_dir>/data/dataset_classes/imagenet_2012.txt` labels file with all othe
 
 ## Running
 
-Running the application with the `-h` option yields the following usage message:
-
-```
-classification_benchmark_demo [OPTION]
-Options:
-
-    -h                        Print a usage message.
-    -i "<path>"               Required. Path to a folder with images or path to an image file.
-    -m "<path>"               Required. Path to an .xml file with a trained model.
-      -l "<absolute_path>"    Required for CPU custom layers.Absolute path to a shared library with the kernels implementation.
-          Or
-      -c "<absolute_path>"    Required for GPU custom kernels. Absolute path to the .xml file with kernels description.
-    -auto_resize              Optional. Enables resizable input.
-    -labels "<path>"          Required. Path to .txt file with labels.
-    -gt "<path>"              Optional. Path to ground truth .txt file.
-    -d "<device>"             Optional. Specify the target device to infer on (the list of available devices is shown below). Default value is CPU. The demo will look for a suitable plugin for device specified.
-    -nthreads "<integer>"     Optional. Specify count of threads.
-    -nstreams "<integer>"     Optional. Specify count of streams.
-    -nireq "<integer>"        Optional. Number of infer requests.
-    -nt "<integer>"           Optional. Number of top results. Default value is 5. Must be >= 1.
-    -res "<WxH>"              Optional. Set image grid resolution in format WxH. Default value is 1280x720.
-    -no_show                  Optional. Disable showing of processed images.
-    -time "<integer>"         Optional. Time in seconds to execute program. Default is -1 (infinite time).
-    -u                        Optional. List of monitors to show initially.
-```
-
-Running the application with the empty list of options yields an error message.
+Running the demo with the `-h` option yields a usage message.
 
 The number of `InferRequest`s is specified by -nireq flag. Each `InferRequest` acts as a "buffer": it waits in queue before being filled with images and sent for inference, then after the inference completes, it waits in queue until its results are processed. Increasing the number of `InferRequest`s usually increases performance, because in that case multiple `InferRequest`s can be processed simultaneously if the device supports parallelization. However, big number of `InferRequest`s increases latency because each image still needs to wait in queue.
 

demos/classification_benchmark_demo/cpp/main.cpp

@@ -1,35 +1,37 @@
-// Copyright (C) 2018-2019 Intel Corporation
+// Copyright (C) 2020-2022 Intel Corporation
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-#include <queue>
-#include <memory>
-#include <string>
 #include <chrono>
-#include <condition_variable>
-#include <mutex>
-#include <cstdio>
-#include <functional>
-#include <atomic>
+#include <fstream>
+#include <iostream>
+#include <limits>
+#include <string>
+#include <vector>
 
-#include <inference_engine.hpp>
 #include <gflags/gflags.h>
+#include <opencv2/opencv.hpp>
+#include <openvino/openvino.hpp>
+
+#include <models/classification_model.h>
+#include <models/results.h>
 #include <pipelines/async_pipeline.h>
 #include <pipelines/metadata.h>
-#include <models/classification_model.h>
-#include <utils/common.hpp>
-#include <utils/slog.hpp>
+
 #include <utils/args_helper.hpp>
+#include <utils/common.hpp>
 #include <utils/ocv_common.hpp>
 #include <utils/performance_metrics.hpp>
+#include <utils/slog.hpp>
 
 #include "grid_mat.hpp"
 
 static const char help_message[] = "Print a usage message.";
 static const char image_message[] = "Required. Path to a folder with images or path to an image file.";
 static const char model_message[] = "Required. Path to an .xml file with a trained model.";
 static const char labels_message[] = "Required. Path to .txt file with labels.";
+static const char layout_message[] = "Optional. Specify inputs layouts."
+                                     " Ex. \"[NCHW]\" or \"input1[NCHW],input2[NC]\" in case of more than one input.";
 static const char gt_message[] = "Optional. Path to ground truth .txt file.";
 static const char target_device_message[] = "Optional. Specify the target device to infer on (the list of available "
                                             "devices is shown below). Default value is CPU. "
@@ -40,10 +42,6 @@ static const char num_inf_req_message[] = "Optional. Number of infer requests.";
 static const char image_grid_resolution_message[] = "Optional. Set image grid resolution in format WxH. "
                                                     "Default value is 1280x720.";
 static const char ntop_message[] = "Optional. Number of top results. Default value is 5. Must be >= 1.";
-static const char custom_cldnn_message[] = "Required for GPU custom kernels. "
-                                           "Absolute path to the .xml file with kernels description.";
-static const char custom_cpu_library_message[] = "Required for CPU custom layers."
-                                                 "Absolute path to a shared library with the kernels implementation.";
 static const char input_resizable_message[] = "Optional. Enables resizable input.";
 static const char no_show_message[] = "Optional. Disable showing of processed images.";
 static const char execution_time_message[] = "Optional. Time in seconds to execute program. "
@@ -54,15 +52,14 @@ DEFINE_bool(h, false, help_message);
 DEFINE_string(i, "", image_message);
 DEFINE_string(m, "", model_message);
 DEFINE_string(labels, "", labels_message);
+DEFINE_string(layout, "", layout_message);
 DEFINE_string(gt, "", gt_message);
 DEFINE_string(d, "CPU", target_device_message);
 DEFINE_uint32(nthreads, 0, num_threads_message);
 DEFINE_string(nstreams, "", num_streams_message);
 DEFINE_uint32(nireq, 0, num_inf_req_message);
 DEFINE_uint32(nt, 5, ntop_message);
 DEFINE_string(res, "1280x720", image_grid_resolution_message);
-DEFINE_string(c, "", custom_cldnn_message);
-DEFINE_string(l, "", custom_cpu_library_message);
 DEFINE_bool(auto_resize, false, input_resizable_message);
 DEFINE_bool(no_show, false, no_show_message);
 DEFINE_uint32(time, std::numeric_limits<gflags::uint32>::max(), execution_time_message);
@@ -76,11 +73,9 @@ static void showUsage() {
     std::cout << "    -h                        " << help_message << std::endl;
     std::cout << "    -i \"<path>\"               " << image_message << std::endl;
     std::cout << "    -m \"<path>\"               " << model_message << std::endl;
-    std::cout << "      -l \"<absolute_path>\"    " << custom_cpu_library_message << std::endl;
-    std::cout << "          Or" << std::endl;
-    std::cout << "      -c \"<absolute_path>\"    " << custom_cldnn_message << std::endl;
     std::cout << "    -auto_resize              " << input_resizable_message << std::endl;
     std::cout << "    -labels \"<path>\"          " << labels_message << std::endl;
+    std::cout << "    -layout \"<string>\"        " << layout_message << std::endl;
     std::cout << "    -gt \"<path>\"              " << gt_message << std::endl;
     std::cout << "    -d \"<device>\"             " << target_device_message << std::endl;
     std::cout << "    -nthreads \"<integer>\"     " << num_threads_message << std::endl;
@@ -165,11 +160,12 @@ int main(int argc, char *argv[]) {
         if (!FLAGS_gt.empty()) {
             std::map<std::string, unsigned> classIndicesMap;
             std::ifstream inputGtFile(FLAGS_gt);
-            if (!inputGtFile.is_open()) throw std::runtime_error("Can't open the ground truth file.");
+            if (!inputGtFile.is_open()) {
+                throw std::runtime_error("Can't open the ground truth file.");
+            }
 
             std::string line;
-            while (std::getline(inputGtFile, line))
-            {
+            while (std::getline(inputGtFile, line)) {
                 size_t separatorIdx = line.find(' ');
                 if (separatorIdx == std::string::npos) {
                     throw std::runtime_error("The ground truth file has incorrect format.");
@@ -196,7 +192,7 @@ int main(int argc, char *argv[]) {
             std::fill(classIndices.begin(), classIndices.end(), 0);
         }
 
-        //------------------------------ Running Detection routines ----------------------------------------------
+        //------------------------------ Running routines ----------------------------------------------
         std::vector<std::string> labels = ClassificationModel::loadLabels(FLAGS_labels);
         for (const auto & classIndex : classIndices) {
             if (classIndex >= labels.size()) {
@@ -205,11 +201,11 @@ int main(int argc, char *argv[]) {
                 }
         }
 
-        slog::info << *InferenceEngine::GetInferenceEngineVersion() << slog::endl;
-        InferenceEngine::Core core;
-        AsyncPipeline pipeline(std::unique_ptr<ModelBase>(new ClassificationModel(FLAGS_m, FLAGS_nt, FLAGS_auto_resize, labels)),
-            ConfigFactory::getUserConfig(FLAGS_d, FLAGS_l, FLAGS_c, FLAGS_nireq, FLAGS_nstreams, FLAGS_nthreads),
-            core);
+        slog::info << ov::get_openvino_version() << slog::endl;
+        ov::Core core;
+
+        AsyncPipeline pipeline(std::unique_ptr<ModelBase>(new ClassificationModel(FLAGS_m, FLAGS_nt, FLAGS_auto_resize, labels, FLAGS_layout)),
+            ConfigFactory::getUserConfig(FLAGS_d, FLAGS_nireq, FLAGS_nstreams, FLAGS_nthreads), core);
 
         Presenter presenter(FLAGS_u, 0);
         int width;

demos/common/cpp/models/CMakeLists.txt

@@ -12,4 +12,4 @@ source_group("include" FILES ${HEADERS})
 
 add_library(models STATIC ${SOURCES} ${HEADERS})
 target_include_directories(models PUBLIC "${CMAKE_CURRENT_SOURCE_DIR}/include")
-target_link_libraries(models PRIVATE ngraph::ngraph gflags ${InferenceEngine_LIBRARIES} utils opencv_core opencv_imgproc)
+target_link_libraries(models PRIVATE gflags ${InferenceEngine_LIBRARIES} utils opencv_core opencv_imgproc)

demos/common/cpp/models/include/models/associative_embedding_decoder.h

@@ -1,5 +1,5 @@
 /*
-// Copyright (C) 2021 Intel Corporation
+// Copyright (C) 2021-2022 Intel Corporation
 //
 // Licensed under the Apache License, Version 2.0 (the "License");
 // you may not use this file except in compliance with the License.
@@ -13,10 +13,9 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 */
-#pragma once
-#include "opencv2/core.hpp"
-#include "results.h"
 
+#pragma once
+#include <opencv2/core.hpp>
 
 struct Peak {
     explicit Peak(const cv::Point2f& keypoint = cv::Point2f(-1, -1),
@@ -31,7 +30,6 @@ struct Peak {
     float tag;
 };
 
-
 class Pose {
     public:
         explicit Pose(size_t numJoints) : peaks(numJoints) {}

demos/common/cpp/models/include/models/classification_model.h

@@ -1,5 +1,5 @@
 /*
-// Copyright (C) 2018-2020 Intel Corporation
+// Copyright (C) 2020-2022 Intel Corporation
 //
 // Licensed under the Apache License, Version 2.0 (the "License");
 // you may not use this file except in compliance with the License.
@@ -13,20 +13,26 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 */
-#pragma once
 
+#pragma once
+#include <string>
+#include <vector>
+#include <openvino/openvino.hpp>
 #include "models/image_model.h"
+#include "models/results.h"
 
 class ClassificationModel : public ImageModel {
 public:
     /// Constructor
     /// @param modelFileName name of model to load.
     /// @param nTop - number of top results.
     /// Any detected object with confidence lower than this threshold will be ignored.
-    /// @param useAutoResize - if true, image will be resized by IE.
+    /// @param useAutoResize - if true, image will be resized by openvino.
     /// Otherwise, image will be preprocessed and resized using OpenCV routines.
     /// @param labels - array of labels for every class.
-    ClassificationModel(const std::string& modelFileName, size_t nTop, bool useAutoResize, const std::vector<std::string>& labels);
+    /// @param layout - model input layout
+    ClassificationModel(const std::string& modelFileName, size_t nTop, bool useAutoResize,
+        const std::vector<std::string>& labels, const std::string& layout = "");
 
     std::unique_ptr<ResultBase> postprocess(InferenceResult& infResult) override;
 
@@ -36,5 +42,5 @@ class ClassificationModel : public ImageModel {
     size_t nTop;
     std::vector<std::string> labels;
 
-    void prepareInputsOutputs(InferenceEngine::CNNNetwork& cnnNetwork) override;
+    void prepareInputsOutputs(std::shared_ptr<ov::Model>& model) override;
 };

demos/common/cpp/models/include/models/deblurring_model.h

@@ -1,5 +1,5 @@
 /*
-// Copyright (C) 2021 Intel Corporation
+// Copyright (C) 2021-2022 Intel Corporation
 //
 // Licensed under the Apache License, Version 2.0 (the "License");
 // you may not use this file except in compliance with the License.
@@ -15,23 +15,28 @@
 */
 
 #pragma once
-
-#include "image_model.h"
+#include <string>
+#include <vector>
+#include <opencv2/opencv.hpp>
+#include <openvino/openvino.hpp>
+#include "models/image_model.h"
+#include "models/results.h"
 
 class DeblurringModel : public ImageModel {
 public:
     /// Constructor
     /// @param modelFileName name of model to load
     /// @param inputImgSize size of image to set model input shape
-    DeblurringModel(const std::string& modelFileName, const cv::Size& inputImgSize);
+    /// @param layout - model input layout
+    DeblurringModel(const std::string& modelFileName, const cv::Size& inputImgSize, const std::string& layout = "");
 
     std::shared_ptr<InternalModelData> preprocess(
-        const InputData& inputData, InferenceEngine::InferRequest::Ptr& request) override;
+        const InputData& inputData, ov::InferRequest& request) override;
     std::unique_ptr<ResultBase> postprocess(InferenceResult& infResult) override;
 
 protected:
-    void prepareInputsOutputs(InferenceEngine::CNNNetwork & cnnNetwork) override;
-    void changeInputSize(InferenceEngine::CNNNetwork& cnnNetwork);
+    void prepareInputsOutputs(std::shared_ptr<ov::Model>& model) override;
+    void changeInputSize(std::shared_ptr<ov::Model>& model);
 
     static const size_t stride = 32;
 };

demos/common/cpp/models/include/models/detection_model.h

@@ -1,5 +1,5 @@
 /*
-// Copyright (C) 2018-2020 Intel Corporation
+// Copyright (C) 2020-2022 Intel Corporation
 //
 // Licensed under the Apache License, Version 2.0 (the "License");
 // you may not use this file except in compliance with the License.
@@ -13,7 +13,10 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 */
+
 #pragma once
+#include <string>
+#include <vector>
 #include "models/image_model.h"
 
 class DetectionModel : public ImageModel {
@@ -22,17 +25,20 @@ class DetectionModel : public ImageModel {
     /// @param modelFileName name of model to load
     /// @param confidenceThreshold - threshold to eliminate low-confidence detections.
     /// Any detected object with confidence lower than this threshold will be ignored.
-    /// @param useAutoResize - if true, image will be resized by IE.
+    /// @param useAutoResize - if true, image will be resized by openvino.
     /// Otherwise, image will be preprocessed and resized using OpenCV routines.
     /// @param labels - array of labels for every class. If this array is empty or contains less elements
     /// than actual classes number, default "Label #N" will be shown for missing items.
-    DetectionModel(const std::string& modelFileName, float confidenceThreshold, bool useAutoResize, const std::vector<std::string>& labels);
+    /// @param layout - model input layout
+    DetectionModel(const std::string& modelFileName, float confidenceThreshold, bool useAutoResize,
+        const std::vector<std::string>& labels, const std::string& layout = "");
 
     static std::vector<std::string> loadLabels(const std::string& labelFilename);
 
 protected:
     float confidenceThreshold;
     std::vector<std::string> labels;
 
-    std::string getLabelName(int labelID) { return (size_t)labelID < labels.size() ? labels[labelID] : std::string("Label #") + std::to_string(labelID); }
+    std::string getLabelName(int labelID) { return (size_t)labelID < labels.size() ?
+                                                   labels[labelID] : std::string("Label #") + std::to_string(labelID); }
 };

demos/common/cpp/models/include/models/detection_model_centernet.h

@@ -1,5 +1,5 @@
 /*
-// Copyright (C) 2020-2021 Intel Corporation
+// Copyright (C) 2020-2022 Intel Corporation
 //
 // Licensed under the Apache License, Version 2.0 (the "License");
 // you may not use this file except in compliance with the License.
@@ -15,7 +15,11 @@
 */
 
 #pragma once
-#include "detection_model.h"
+#include <string>
+#include <vector>
+#include <openvino/openvino.hpp>
+#include "models/detection_model.h"
+#include "models/results.h"
 
 class ModelCenterNet : public DetectionModel {
 public:
@@ -31,11 +35,11 @@ class ModelCenterNet : public DetectionModel {
     static const int INIT_VECTOR_SIZE = 200;
 
     ModelCenterNet(const std::string& modelFileName, float confidenceThreshold,
-        const std::vector<std::string>& labels = std::vector<std::string>());
+        const std::vector<std::string>& labels = std::vector<std::string>(), const std::string& layout = "");
     std::shared_ptr<InternalModelData> preprocess(
-        const InputData& inputData, InferenceEngine::InferRequest::Ptr& request) override;
+        const InputData& inputData, ov::InferRequest& request) override;
     std::unique_ptr<ResultBase> postprocess(InferenceResult& infResult) override;
 
 protected:
-    void prepareInputsOutputs(InferenceEngine::CNNNetwork& cnnNetwork) override;
+    void prepareInputsOutputs(std::shared_ptr<ov::Model>& model) override;
 };