demos/tests: enable retinaface-resnet50-pytorch.onnx (#3823)

openvinotoolkit · Aug 14, 2023 · a698773 · a698773
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Showing 5 changed files with 23 additions and 26 deletions.
diff --git a/demos/common/cpp/models/src/detection_model_retinaface_pt.cpp b/demos/common/cpp/models/src/detection_model_retinaface_pt.cpp
@@ -50,7 +50,7 @@ void ModelRetinaFacePT::prepareInputsOutputs(std::shared_ptr<ov::Model>& model)
         throw std::logic_error("RetinaFacePT model wrapper expects models that have only 1 input");
     }
 
-    const ov::Shape& inputShape = model->input().get_shape();
+    const ov::Shape& inputShape = model->input().get_partial_shape().get_max_shape();
     const ov::Layout& inputLayout = getInputLayout(model->input());
 
     if (inputShape[ov::layout::channels_idx(inputLayout)] != 3) {
@@ -94,7 +94,7 @@ void ModelRetinaFacePT::prepareInputsOutputs(std::shared_ptr<ov::Model>& model)
         ppp.output(outTensorName)
             .tensor()
             .set_element_type(ov::element::f32)
-            .set_layout(output.get_shape().size() == 4 ? nchw : chw);
+            .set_layout(output.get_partial_shape().size() == 4 ? nchw : chw);
 
         if (outTensorName.find("bbox") != std::string::npos) {
             outputsNames[OUT_BOXES] = outTensorName;
@@ -106,7 +106,7 @@ void ModelRetinaFacePT::prepareInputsOutputs(std::shared_ptr<ov::Model>& model)
             outputsNames.resize(std::max(outputsNames.size(), (size_t)OUT_LANDMARKS + 1));
             outputsNames[OUT_LANDMARKS] = outTensorName;
             landmarksNum =
-                output.get_shape()[ov::layout::width_idx(chw)] / 2;  // Each landmark consist of 2 variables (x and y)
+                output.get_partial_shape()[ov::layout::width_idx(chw)].get_length() / 2;  // Each landmark consist of 2 variables (x and y)
         } else {
             continue;
         }

diff --git a/demos/common/cpp/models/src/model_base.cpp b/demos/common/cpp/models/src/model_base.cpp
@@ -47,11 +47,10 @@ ov::CompiledModel ModelBase::compileModel(const ModelConfig& config, ov::Core& c
 }
 
 ov::Layout ModelBase::getInputLayout(const ov::Output<ov::Node>& input) {
-    const ov::Shape& inputShape = input.get_shape();
     ov::Layout layout = ov::layout::get_layout(input);
     if (layout.empty()) {
         if (inputsLayouts.empty()) {
-            layout = getLayoutFromShape(inputShape);
+            layout = getLayoutFromShape(input.get_partial_shape());
             slog::warn << "Automatically detected layout '" << layout.to_string() << "' for input '"
                        << input.get_any_name() << "' will be used." << slog::endl;
         } else if (inputsLayouts.size() == 1) {

diff --git a/demos/common/cpp/models/src/segmentation_model.cpp b/demos/common/cpp/models/src/segmentation_model.cpp
@@ -96,8 +96,7 @@ void SegmentationModel::prepareInputsOutputs(std::shared_ptr<ov::Model>& model)
 
     const ov::Shape& outputShape = output.get_partial_shape().get_max_shape();
 
-    constexpr bool gues_layout = true;
-    ov::Layout outputLayout = getLayoutFromShape(outputShape, gues_layout);
+    ov::Layout outputLayout = getLayoutFromShape(outputShape);
     outHeight = static_cast<int>(outputShape[ov::layout::height_idx(outputLayout)]);
     outWidth = static_cast<int>(outputShape[ov::layout::width_idx(outputLayout)]);
 

diff --git a/demos/common/cpp/utils/include/utils/ocv_common.hpp b/demos/common/cpp/utils/include/utils/ocv_common.hpp
@@ -114,14 +114,14 @@ static inline void resize2tensor(const cv::Mat& mat, const ov::Tensor& tensor) {
 struct IntervalCondition {
     using DimType = size_t;
     using IndexType = size_t;
-    using ConditionChecker = std::function<bool(IndexType, const ov::Shape&)>;
+    using ConditionChecker = std::function<bool(IndexType, const ov::PartialShape&)>;
 
     template<class Cond>
     constexpr IntervalCondition(IndexType i1, IndexType i2, Cond c) :
-        impl([=](IndexType i0, const ov::Shape& shape) {
-            return c(shape[i0], shape[i1]) && c(shape[i0], shape[i2]);})
+        impl([=](IndexType i0, const ov::PartialShape& shape) {
+            return c(shape[i0].get_max_length(), shape[i1].get_max_length()) && c(shape[i0].get_max_length(), shape[i2].get_max_length());})
     {}
-    bool operator() (IndexType i0, const ov::Shape& shape) const { return impl(i0, shape); }
+    bool operator() (IndexType i0, const ov::PartialShape& shape) const { return impl(i0, shape); }
 private:
     ConditionChecker impl;
 };
@@ -132,7 +132,7 @@ IntervalCondition makeCond(Args&&...args) {
 }
 using LayoutCondition = std::tuple<size_t/*dim index*/, IntervalCondition, std::string>;
 
-static inline std::tuple<bool, ov::Layout> makeGuesLayoutFrom4DShape(const ov::Shape& shape) {
+static inline std::tuple<bool, ov::Layout> makeGuesLayoutFrom4DShape(const ov::PartialShape& shape) {
     // at the moment we make assumption about NCHW & NHCW only
     // if hypothetical C value is less than hypothetical H and W - then
     // out assumption is correct and we pick a corresponding layout
@@ -151,7 +151,7 @@ static inline std::tuple<bool, ov::Layout> makeGuesLayoutFrom4DShape(const ov::S
     return {false, ov::Layout{}};
 }
 
-static inline ov::Layout getLayoutFromShape(const ov::Shape& shape, bool gues_layout = false) {
+static inline ov::Layout getLayoutFromShape(const ov::PartialShape& shape) {
     if (shape.size() == 2) {
         return "NC";
     }
@@ -165,10 +165,10 @@ static inline ov::Layout getLayoutFromShape(const ov::Shape& shape, bool gues_la
         throw std::runtime_error("Can't guess layout for " + shape.to_string());
     }
     if (shape.size() == 4) {
-        if (shape[1] >= 1 && shape[1] <= 4) {
+        if (ov::Interval{1, 4}.contains(shape[1].get_interval())) {
             return "NCHW";
         }
-        if (shape[3] >= 1 && shape[3] <= 4) {
+        if (ov::Interval{1, 4}.contains(shape[3].get_interval())) {
             return "NHWC";
         }
         if (shape[1] == shape[2]) {
@@ -177,17 +177,14 @@ static inline ov::Layout getLayoutFromShape(const ov::Shape& shape, bool gues_la
         if (shape[2] == shape[3]) {
             return "NCHW";
         }
-        if (gues_layout) {
-            bool guesResult = false;
-            ov::Layout guessedLayout;
-            std::tie(guesResult, guessedLayout) = makeGuesLayoutFrom4DShape(shape);
-            if (guesResult) {
-                return guessedLayout;
-            }
+        bool guesResult = false;
+        ov::Layout guessedLayout;
+        std::tie(guesResult, guessedLayout) = makeGuesLayoutFrom4DShape(shape);
+        if (guesResult) {
+            return guessedLayout;
         }
     }
-    throw std::runtime_error(std::string("Usupported " + std::to_string(shape.size()) + "D shape: ") +
-                             shape.to_string());
+    throw std::runtime_error("Usupported " + std::to_string(shape.size()) + "D shape");
 }
 
 /**

diff --git a/demos/tests/cases.py b/demos/tests/cases.py
@@ -493,8 +493,10 @@ def single_option_cases(key, *args):
                 TestCase(options={'-at': 'retinaface-pytorch'}),
                 [
                     TestCase(options={'-m': ModelArg('retinaface-resnet50-pytorch')}),
-                    # TestCase(options={'-m': ModelFileArg('retinaface-resnet50-pytorch', 'retinaface-resnet50-pytorch.onnx'),
-                    #                   '-mean_values': "104.0 117.0 123.0"}),  dynamic bathc: get_shape was called on a descriptor::Tensor with dynamic shape
+                    TestCase({
+                        '-m': ModelFileArg('retinaface-resnet50-pytorch', 'retinaface-resnet50-pytorch.onnx'),
+                        '-mean_values': "104.0 117.0 123.0",
+                    }),
                 ]
             ),
             *combine_cases(