Initial setup for CLion

engines/OpenVINOEngine/src/models/image_model.cpp

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+/*
+// Copyright (C) 2021-2024 Intel Corporation
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+*/
+
+#include "models/image_model.h"
+
+#include <stdexcept>
+#include <vector>
+
+#include <opencv2/core.hpp>
+#include <openvino/openvino.hpp>
+
+#include <utils/image_utils.h>
+#include <utils/ocv_common.hpp>
+
+#include "models/input_data.h"
+#include "models/internal_model_data.h"
+
+ImageModel::ImageModel() {
+
+}
+ImageModel::ImageModel(const std::string& modelFileName, bool useAutoResize, const std::string& layout)
+    : ModelBase(modelFileName, layout),
+      useAutoResize(useAutoResize) {}
+
+std::shared_ptr<InternalModelData> ImageModel::preprocess(const InputData& inputData, ov::InferRequest& request) {
+    const auto& origImg = inputData.asRef<ImageInputData>().inputImage;
+    auto img = inputTransform(origImg);
+
+    if (!useAutoResize) {
+        // /* Resize and copy data from the image to the input tensor */
+        const ov::Tensor& frameTensor = request.get_tensor(inputsNames[0]);  // first input should be image
+        const ov::Shape& tensorShape = frameTensor.get_shape();
+        const ov::Layout layout("NHWC");
+        const size_t width = tensorShape[ov::layout::width_idx(layout)];
+        const size_t height = tensorShape[ov::layout::height_idx(layout)];
+        const size_t channels = tensorShape[ov::layout::channels_idx(layout)];
+        if (static_cast<size_t>(img.channels()) != channels) {
+            throw std::runtime_error(std::string("The number of channels for model input: ") +
+                                     std::to_string(channels) + " and image: " +
+                                     std::to_string(img.channels()) + " - must match");
+        }
+        if (channels != 1 && channels != 3) {
+            throw std::runtime_error("Unsupported number of channels");
+        }
+        img = resizeImageExt(img, width, height, resizeMode, interpolationMode);
+    }
+    request.set_tensor(inputsNames[0], wrapMat2Tensor(img));
+    return std::make_shared<InternalImageModelData>(origImg.cols, origImg.rows);
+}