Prohibit whitespace errors and non ASCII chars (openvinotoolkit#56)

.github/PULL_REQUEST_TEMPLATE.md

@@ -19,4 +19,3 @@ Fixes # (issue)
 - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
 - [ ] Did you make sure to update the documentation with your changes?
 - [ ] Did you write any new necessary tests?
-

.github/workflows/test_accuracy.yml

@@ -54,4 +54,3 @@ jobs:
     - name: Run CPP Test
       run: |
         build/test_accuracy -d data -p tests/python/accuracy/public_scope.json
-

.github/workflows/test_precommit.yml

@@ -22,6 +22,12 @@ jobs:
     runs-on: ubuntu-latest
     steps:
     - uses: actions/checkout@v2
+    - name: git --no-pager diff --check $(git hash-object -t tree /dev/null)
+      run: git --no-pager diff --check $(git hash-object -t tree /dev/null)
+    - name: Prohibit non ASCII chars in file names
+      run: test $(git diff --name-only --diff-filter=A -z $(git hash-object -t tree /dev/null) | LC_ALL=C tr -d '[ -~]\0' | wc -c) == 0
+    - name: "! git grep -n '[^ -~]' -- ':(exclude)model_api/python/openvino/model_api/README.md'"
+      run: "! git grep -n '[^ -~]' -- ':(exclude)model_api/python/openvino/model_api/README.md'"
     - name: Setup Python ${{ matrix.python-version }}
       uses: actions/setup-python@v2
       with:
@@ -75,7 +81,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v2
-          
+
       - name: cppcheck
         uses: chmorgan/cppcheck-action@main
         with:

examples/cpp/synchronous_api/README.md

@@ -21,7 +21,7 @@ This example demonstrates how to use a C++ API of OpenVINO Model API for synchro
    ```
    - Build:
    ```
-   make -j 
+   make -j
    ```
 - Download a model by running a Python code with Model API, see Python [exaple](../../python/synchronous_api/README.md):
     ```python

examples/python/serving_api/README.md

@@ -1,6 +1,6 @@
 # Serving API example
 This example demonstrates how to use a Python API of OpenVINO Model API for a remote inference of models hosted with [OpenVINO Model Server](https://docs.openvino.ai/latest/ovms_what_is_openvino_model_server.html). This tutorial assumes that you are familiar with Docker subsystem and includes the following steps:
-- Run Docker image with 
+- Run Docker image with
 - Instantiate a model
 - Run inference
 - Process results

model_api/cpp/adapters/src/openvino_adapter.cpp

@@ -84,5 +84,3 @@ std::vector<std::string> OpenVINOInferenceAdapter::getOutputNames() const {
 const ov::AnyMap& OpenVINOInferenceAdapter::getModelConfig() const {
     return modelConfig;
 }
-
-

model_api/cpp/models/include/models/detection_model_centernet.h

@@ -49,7 +49,7 @@ class ModelCenterNet : public DetectionModel {
 
     ModelCenterNet(std::shared_ptr<ov::Model>& model, const ov::AnyMap& configuration);
     ModelCenterNet(std::shared_ptr<InferenceAdapter>& adapter);
-    
+
     std::shared_ptr<InternalModelData> preprocess(const InputData& inputData, InferenceInput& input) override;
     std::unique_ptr<ResultBase> postprocess(InferenceResult& infResult) override;
 

model_api/cpp/models/include/models/detection_model_retinaface.h

@@ -34,7 +34,7 @@ class ModelRetinaFace : public DetectionModelExt {
 public:
     static const int LANDMARKS_NUM = 5;
     static const int INIT_VECTOR_SIZE = 200;
-    
+
     ModelRetinaFace(std::shared_ptr<ov::Model>& model, const ov::AnyMap& configuration);
     ModelRetinaFace(std::shared_ptr<InferenceAdapter>& adapter);
     using DetectionModelExt::DetectionModelExt;

model_api/cpp/models/include/models/detection_model_retinaface_pt.h

@@ -45,7 +45,7 @@ class ModelRetinaFacePT : public DetectionModelExt {
     ModelRetinaFacePT(std::shared_ptr<ov::Model>& model, const ov::AnyMap& configuration);
     ModelRetinaFacePT(std::shared_ptr<InferenceAdapter>& adapter);
     using DetectionModelExt::DetectionModelExt;
-    
+
     std::unique_ptr<ResultBase> postprocess(InferenceResult& infResult) override;
     static std::string ModelType;
 

model_api/cpp/models/include/models/model_base.h

@@ -37,7 +37,7 @@ class ModelBase {
     ModelBase(const std::string& modelFile, const std::string& layout = "");
     ModelBase(std::shared_ptr<InferenceAdapter>& adapter);
     ModelBase(std::shared_ptr<ov::Model>& model, const ov::AnyMap& configuration);
-    
+
     virtual ~ModelBase() = default;
 
     std::shared_ptr<ov::Model> prepare();

model_api/cpp/models/src/classification_model.cpp

@@ -128,7 +128,7 @@ void ClassificationModel::updateModelInfo() {
 std::unique_ptr<ClassificationModel> ClassificationModel::create_model(const std::string& modelFile, const ov::AnyMap& configuration, bool preload) {
     auto core = ov::Core();
     std::shared_ptr<ov::Model> model = core.read_model(modelFile);
-    
+
     // Check model_type in the rt_info, ignore configuration
     std::string model_type = ClassificationModel::ModelType;
     try {
@@ -138,7 +138,7 @@ std::unique_ptr<ClassificationModel> ClassificationModel::create_model(const std
     } catch (const std::exception& e) {
         slog::warn << "Model type is not specified in the rt_info, use default model type: " << model_type << slog::endl;
     }
-    
+
     if (model_type != ClassificationModel::ModelType) {
         throw ov::Exception("Incorrect or unsupported model_type is provided in the model_info section: " + model_type);
     }

model_api/cpp/models/src/detection_model.cpp

@@ -94,7 +94,7 @@ std::unique_ptr<DetectionModel> DetectionModel::create_model(const std::string&
     } else {
         throw ov::Exception("Incorrect or unsupported model_type is provided in the model_info section: " + model_type);
     }
-    
+
     detectionModel->prepare();
     if (preload) {
         detectionModel->load(core);
@@ -126,7 +126,7 @@ std::unique_ptr<DetectionModel> DetectionModel::create_model(std::shared_ptr<Inf
     } else {
         throw ov::Exception("Incorrect or unsupported model_type is provided: " + model_type);
     }
-    
+
     return detectionModel;
 }
 

model_api/cpp/models/src/detection_model_ssd.cpp

@@ -206,7 +206,7 @@ void ModelSSD::prepareInputsOutputs(std::shared_ptr<ov::Model>& model) {
                                         inputLayout,
                                         resizeMode,
                                         interpolationMode,
-                                        ov::Shape{shape[ov::layout::width_idx(inputLayout)], 
+                                        ov::Shape{shape[ov::layout::width_idx(inputLayout)],
                                                   shape[ov::layout::height_idx(inputLayout)]});
 
                 netInputWidth = shape[ov::layout::width_idx(inputLayout)];

model_api/cpp/models/src/detection_model_yolo.cpp

@@ -99,7 +99,7 @@ static inline float linear(float x) {
 }
 
 ModelYolo::ModelYolo(std::shared_ptr<ov::Model>& model, const ov::AnyMap& configuration)
-    : DetectionModelExt(model, configuration) {    
+    : DetectionModelExt(model, configuration) {
     auto anchors_iter = configuration.find("anchors");
     if (anchors_iter == configuration.end()) {
         if (model->has_rt_info("model_info", "anchors")) {

model_api/cpp/models/src/image_model.cpp

@@ -159,7 +159,7 @@ std::shared_ptr<ov::Model> ImageModel::embedProcessing(std::shared_ptr<ov::Model
                                             bool brg2rgb,
                                             const std::vector<float>& mean,
                                             const std::vector<float>& scale) {
-    
+
     ov::preprocess::PrePostProcessor ppp(model);
 
     inputTransform.setPrecision(ppp, inputName);

model_api/cpp/utils/include/utils/image_utils.h

@@ -42,6 +42,5 @@ cv::Mat resizeImageExt(const cv::Mat& mat, int width, int height, RESIZE_MODE re
                        cv::Scalar BorderConstant = cv::Scalar(0, 0, 0));
 
 ov::preprocess::PostProcessSteps::CustomPostprocessOp createResizeGraph(RESIZE_MODE resizeMode,
-                                                                        const ov::Shape& size, 
+                                                                        const ov::Shape& size,
                                                                         const cv::InterpolationFlags interpolationMode = cv::INTER_LINEAR);
-