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// 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);
}
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