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diff --git a/python/openvino/runtime/common/models/src/jpeg_restoration_model.cpp b/python/openvino/runtime/common/models/src/jpeg_restoration_model.cpp
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+++ b/python/openvino/runtime/common/models/src/jpeg_restoration_model.cpp
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+/*
+// 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.
+// 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 <stddef.h>
+
+#include <algorithm>
+#include <memory>
+#include <stdexcept>
+#include <string>
+#include <vector>
+
+#include <opencv2/core.hpp>
+#include <opencv2/imgcodecs.hpp>
+#include <opencv2/imgproc.hpp>
+#include <openvino/openvino.hpp>
+
+#include <utils/ocv_common.hpp>
+#include <utils/slog.hpp>
+
+#include "models/image_model.h"
+#include "models/input_data.h"
+#include "models/internal_model_data.h"
+#include "models/jpeg_restoration_model.h"
+#include "models/results.h"
+
+JPEGRestorationModel::JPEGRestorationModel(const std::string& modelFileName,
+                                           const cv::Size& inputImgSize,
+                                           bool _jpegCompression,
+                                           const std::string& layout)
+    : ImageModel(modelFileName, false, layout) {
+    netInputHeight = inputImgSize.height;
+    netInputWidth = inputImgSize.width;
+    jpegCompression = _jpegCompression;
+}
+
+void JPEGRestorationModel::prepareInputsOutputs(std::shared_ptr<ov::Model>& model) {
+    // --------------------------- Configure input & output -------------------------------------------------
+    // --------------------------- Prepare input  ------------------------------------------------------
+    if (model->inputs().size() != 1) {
+        throw std::logic_error("The JPEG Restoration model wrapper supports topologies with only 1 input");
+    }
+    inputsNames.push_back(model->input().get_any_name());
+
+    const ov::Shape& inputShape = model->input().get_shape();
+    const ov::Layout& inputLayout = getInputLayout(model->input());
+
+    if (inputShape.size() != 4 || inputShape[ov::layout::batch_idx(inputLayout)] != 1 ||
+        inputShape[ov::layout::channels_idx(inputLayout)] != 3) {
+        throw std::logic_error("3-channel 4-dimensional model's input is expected");
+    }
+
+    ov::preprocess::PrePostProcessor ppp(model);
+    ppp.input().tensor().set_element_type(ov::element::u8).set_layout("NHWC");
+
+    ppp.input().model().set_layout(inputLayout);
+
+    // --------------------------- Prepare output  -----------------------------------------------------
+    const ov::OutputVector& outputs = model->outputs();
+    if (outputs.size() != 1) {
+        throw std::logic_error("The JPEG Restoration model wrapper supports topologies with only 1 output");
+    }
+    const ov::Shape& outputShape = model->output().get_shape();
+    const ov::Layout outputLayout{"NCHW"};
+    if (outputShape.size() != 4 || outputShape[ov::layout::batch_idx(outputLayout)] != 1 ||
+        outputShape[ov::layout::channels_idx(outputLayout)] != 3) {
+        throw std::logic_error("3-channel 4-dimensional model's output is expected");
+    }
+
+    outputsNames.push_back(model->output().get_any_name());
+    ppp.output().tensor().set_element_type(ov::element::f32);
+    model = ppp.build();
+
+    changeInputSize(model);
+}
+
+void JPEGRestorationModel::changeInputSize(std::shared_ptr<ov::Model>& model) {
+    ov::Shape inputShape = model->input().get_shape();
+    const ov::Layout& layout = ov::layout::get_layout(model->input());
+
+    const auto batchId = ov::layout::batch_idx(layout);
+    const auto heightId = ov::layout::height_idx(layout);
+    const auto widthId = ov::layout::width_idx(layout);
+
+    if (inputShape[heightId] % stride || inputShape[widthId] % stride) {
+        throw std::logic_error("The shape of the model input must be divisible by stride");
+    }
+
+    netInputHeight = static_cast<int>((netInputHeight + stride - 1) / stride) * stride;
+    netInputWidth = static_cast<int>((netInputWidth + stride - 1) / stride) * stride;
+
+    inputShape[batchId] = 1;
+    inputShape[heightId] = netInputHeight;
+    inputShape[widthId] = netInputWidth;
+
+    model->reshape(inputShape);
+}
+
+std::shared_ptr<InternalModelData> JPEGRestorationModel::preprocess(const InputData& inputData,
+                                                                    ov::InferRequest& request) {
+    cv::Mat image = inputData.asRef<ImageInputData>().inputImage;
+    const size_t h = image.rows;
+    const size_t w = image.cols;
+    cv::Mat resizedImage;
+    if (jpegCompression) {
+        std::vector<uchar> encimg;
+        std::vector<int> params{cv::IMWRITE_JPEG_QUALITY, 40};
+        cv::imencode(".jpg", image, encimg, params);
+        image = cv::imdecode(cv::Mat(encimg), 3);
+    }
+
+    if (netInputHeight - stride < h && h <= netInputHeight && netInputWidth - stride < w && w <= netInputWidth) {
+        int bottom = netInputHeight - h;
+        int right = netInputWidth - w;
+        cv::copyMakeBorder(image, resizedImage, 0, bottom, 0, right, cv::BORDER_CONSTANT, 0);
+    } else {
+        slog::warn << "\tChosen model aspect ratio doesn't match image aspect ratio" << slog::endl;
+        cv::resize(image, resizedImage, cv::Size(netInputWidth, netInputHeight));
+    }
+    request.set_input_tensor(wrapMat2Tensor(resizedImage));
+
+    return std::make_shared<InternalImageModelData>(image.cols, image.rows);
+}
+
+std::unique_ptr<ResultBase> JPEGRestorationModel::postprocess(InferenceResult& infResult) {
+    ImageResult* result = new ImageResult;
+    *static_cast<ResultBase*>(result) = static_cast<ResultBase&>(infResult);
+
+    const auto& inputImgSize = infResult.internalModelData->asRef<InternalImageModelData>();
+    const auto outputData = infResult.getFirstOutputTensor().data<float>();
+
+    std::vector<cv::Mat> imgPlanes;
+    const ov::Shape& outputShape = infResult.getFirstOutputTensor().get_shape();
+    const size_t outHeight = static_cast<int>(outputShape[2]);
+    const size_t outWidth = static_cast<int>(outputShape[3]);
+    const size_t numOfPixels = outWidth * outHeight;
+    imgPlanes = std::vector<cv::Mat>{cv::Mat(outHeight, outWidth, CV_32FC1, &(outputData[0])),
+                                     cv::Mat(outHeight, outWidth, CV_32FC1, &(outputData[numOfPixels])),
+                                     cv::Mat(outHeight, outWidth, CV_32FC1, &(outputData[numOfPixels * 2]))};
+    cv::Mat resultImg;
+    cv::merge(imgPlanes, resultImg);
+
+    if (netInputHeight - stride < static_cast<size_t>(inputImgSize.inputImgHeight) &&
+        static_cast<size_t>(inputImgSize.inputImgHeight) <= netInputHeight &&
+        netInputWidth - stride < static_cast<size_t>(inputImgSize.inputImgWidth) &&
+        static_cast<size_t>(inputImgSize.inputImgWidth) <= netInputWidth) {
+        result->resultImage = resultImg(cv::Rect(0, 0, inputImgSize.inputImgWidth, inputImgSize.inputImgHeight));
+    } else {
+        cv::resize(resultImg, result->resultImage, cv::Size(inputImgSize.inputImgWidth, inputImgSize.inputImgHeight));
+    }
+
+    result->resultImage.convertTo(result->resultImage, CV_8UC3, 255);
+
+    return std::unique_ptr<ResultBase>(result);
+}