bool RLInferenceModel::loadModel()

in inference_pkg/src/intel_inference_eng.cpp [203:233]
29 lines of code
5 McCabe index (conditional complexity)

    bool RLInferenceModel::loadModel(const char* artifactPath,
                            std::shared_ptr<InferTask::ImgProcessBase> imgProcess) {
        if (doInference_) {
            RCLCPP_ERROR(inferenceNode->get_logger(), "Please stop inference prior to loading a model");
            return false;
        }
        if (!imgProcess) {
            RCLCPP_ERROR(inferenceNode->get_logger(), "Invalid image processing algorithm");
            return false;
        }
        // Set the image processing algorithms
        imgProcess_ = imgProcess;
        // Load the model
        try {
            inferRequest_ = setMultiHeadModel(artifactPath, "CPU", core_, inputNamesArr_,
                                     outputName_, InferenceEngine::Precision::FP32,
                                     InferenceEngine::Precision::FP32, inferenceNode);
            for(size_t i = 0; i != inputNamesArr_.size(); ++i) {
                auto input = inferRequest_.GetBlob(inputNamesArr_[i]);
                std::unordered_map<std::string, int> params_ = {{"width", input->getTensorDesc().getDims()[3]},
                       {"height", input->getTensorDesc().getDims()[2]},
                       {"channels", input->getTensorDesc().getDims()[1]}};
                paramsArr_.push_back(params_);
            }
        }
        catch (const std::exception &ex) {
            RCLCPP_ERROR(inferenceNode->get_logger(), "Model failed to load: %s", ex.what());
            return false;
        }
        return true;
    }