1 files changed, 92 insertions, 0 deletions
diff --git a/python/openvino/runtime/common/utils/include/samples/ocv_common.hpp b/python/openvino/runtime/common/utils/include/samples/ocv_common.hpp
new file mode 100644
index 0000000..94f3b1f
--- /dev/null
+++ b/python/openvino/runtime/common/utils/include/samples/ocv_common.hpp
@@ -0,0 +1,92 @@
+// Copyright (C) 2018-2022 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+/**
+ * @brief a header file with common samples functionality using OpenCV
+ * @file ocv_common.hpp
+ */
+
+#pragma once
+
+#include <opencv2/opencv.hpp>
+
+#include "openvino/openvino.hpp"
+#include "samples/common.hpp"
+
+/**
+ * @brief Sets image data stored in cv::Mat object to a given Blob object.
+ * @param orig_image - given cv::Mat object with an image data.
+ * @param blob - Blob object which to be filled by an image data.
+ * @param batchIndex - batch index of an image inside of the blob.
+ */
+template <typename T>
+void matU8ToBlob(const cv::Mat& orig_image, InferenceEngine::Blob::Ptr& blob, int batchIndex = 0) {
+    InferenceEngine::SizeVector blobSize = blob->getTensorDesc().getDims();
+    const size_t width = blobSize[3];
+    const size_t height = blobSize[2];
+    const size_t channels = blobSize[1];
+    InferenceEngine::MemoryBlob::Ptr mblob = InferenceEngine::as<InferenceEngine::MemoryBlob>(blob);
+    OPENVINO_ASSERT(mblob,
+                    "We expect blob to be inherited from MemoryBlob in matU8ToBlob, "
+                    "but by fact we were not able to cast inputBlob to MemoryBlob");
+    // locked memory holder should be alive all time while access to its buffer happens
+    auto mblobHolder = mblob->wmap();
+
+    T* blob_data = mblobHolder.as<T*>();
+
+    cv::Mat resized_image(orig_image);
+    if (static_cast<int>(width) != orig_image.size().width || static_cast<int>(height) != orig_image.size().height) {
+        cv::resize(orig_image, resized_image, cv::Size(width, height));
+    }
+
+    int batchOffset = batchIndex * width * height * channels;
+
+    for (size_t c = 0; c < channels; c++) {
+        for (size_t h = 0; h < height; h++) {
+            for (size_t w = 0; w < width; w++) {
+                blob_data[batchOffset + c * width * height + h * width + w] = resized_image.at<cv::Vec3b>(h, w)[c];
+            }
+        }
+    }
+}
+
+/**
+ * @brief Wraps data stored inside of a passed cv::Mat object by new Blob pointer.
+ * @note: No memory allocation is happened. The blob just points to already existing
+ *        cv::Mat data.
+ * @param mat - given cv::Mat object with an image data.
+ * @return resulting Blob pointer.
+ */
+static UNUSED InferenceEngine::Blob::Ptr wrapMat2Blob(const cv::Mat& mat) {
+    size_t channels = mat.channels();
+    size_t height = mat.size().height;
+    size_t width = mat.size().width;
+
+    size_t strideH = mat.step.buf[0];
+    size_t strideW = mat.step.buf[1];
+
+    bool is_dense = strideW == channels && strideH == channels * width;
+
+    OPENVINO_ASSERT(is_dense, "Doesn't support conversion from not dense cv::Mat");
+
+    InferenceEngine::TensorDesc tDesc(InferenceEngine::Precision::U8,
+                                      {1, channels, height, width},
+                                      InferenceEngine::Layout::NHWC);
+
+    return InferenceEngine::make_shared_blob<uint8_t>(tDesc, mat.data);
+}
+
+static UNUSED ov::Tensor wrapMat2Tensor(const cv::Mat& mat) {
+    const size_t channels = mat.channels();
+    const size_t height = mat.size().height;
+    const size_t width = mat.size().width;
+
+    const size_t strideH = mat.step.buf[0];
+    const size_t strideW = mat.step.buf[1];
+
+    const bool is_dense = strideW == channels && strideH == channels * width;
+    OPENVINO_ASSERT(is_dense, "Doesn't support conversion from not dense cv::Mat");
+
+    return ov::Tensor(ov::element::u8, ov::Shape{1, height, width, channels}, mat.data);
+}