Explicit rotated_rect, simplify example (#134)

Author: Wovchena

examples/cpp/synchronous_api/main.cpp

@@ -1,5 +1,5 @@
 /*
-// Copyright (C) 2018-2022 Intel Corporation
+// Copyright (C) 2018-2023 Intel Corporation
 //
 // Licensed under the Apache License, Version 2.0 (the "License");
 // you may not use this file except in compliance with the License.
@@ -32,41 +32,32 @@
 #include <models/input_data.h>
 #include <models/results.h>
 
+int main(int argc, char* argv[]) try {
+    if (argc != 3) {
+        throw std::runtime_error(std::string{"Usage: "} + argv[0] + " <path_to_model> <path_to_image>");
+    }
 
-int main(int argc, char* argv[]) {
-    try {
-        if (argc != 3) {
-            std::cerr << "Usage : " << argv[0] << " <path_to_model> <path_to_image>"
-                      << std::endl;
-            return EXIT_FAILURE;
-        }
-
-        cv::Mat image = cv::imread(argv[2]);
-        if (!image.data) {
-            throw std::runtime_error{"Failed to read the image"};
-        }
+    cv::Mat image = cv::imread(argv[2]);
+    if (!image.data) {
+        throw std::runtime_error{"Failed to read the image"};
+    }
 
-        // Instantiate Object Detection model
-        auto model = DetectionModel::create_model(argv[1]); // works with SSD models. Download it using Python Model API
+    // Instantiate Object Detection model
+    auto model = DetectionModel::create_model(argv[1]); // works with SSD models. Download it using Python Model API
 
-        // Run the inference
-        auto result = model->infer(image);
+    // Run the inference
+    auto result = model->infer(image);
 
-        // Process detections
-        for (auto& obj : result->objects) {
+    // Process detections
+    for (auto& obj : result->objects) {
         std::cout << " " << std::left << std::setw(9) << obj.label << " | " << std::setw(10) << obj.confidence
-                    << " | " << std::setw(4) << int(obj.x) << " | " << std::setw(4) << int(obj.y) << " | "
-                    << std::setw(4) << int(obj.x + obj.width) << " | " << std::setw(4) << int(obj.y + obj.height)
-                    << std::endl;
-        }
-
-    } catch (const std::exception& error) {
-        std::cerr << error.what() << std::endl;
-        return 1;
-    } catch (...) {
-        std::cerr << "Unknown/internal exception happened." << std::endl;
-        return 1;
+            << " | " << std::setw(4) << int(obj.x) << " | " << std::setw(4) << int(obj.y) << " | "
+            << std::setw(4) << int(obj.x + obj.width) << " | " << std::setw(4) << int(obj.y + obj.height) << "\n";
     }
-
-    return 0;
+} catch (const std::exception& error) {
+    std::cerr << error.what() << '\n';
+    return 1;
+} catch (...) {
+    std::cerr << "Non-exception object thrown\n";
+    return 1;
 }

model_api/cpp/models/src/image_model.cpp

@@ -261,7 +261,7 @@ std::shared_ptr<InternalModelData> ImageModel::preprocess(const InputData& input
     auto img = inputTransform(origImg);
 
     if (!useAutoResize && !embedded_processing) {
-        // /* Resize and copy data from the image to the input tensor */
+        // Resize and copy data from the image to the input tensor
         auto tensorShape = inferenceAdapter->getInputShape(inputNames[0]).get_max_shape(); // first input should be image
         const ov::Layout layout("NHWC");
         const size_t width = tensorShape[ov::layout::width_idx(layout)];

model_api/python/openvino/model_api/models/utils.py

@@ -102,7 +102,7 @@ def __str__(self):
 
 
 class SegmentedObjectWithRects(SegmentedObject):
-    def __init__(self, segmented_object):
+    def __init__(self, segmented_object, rotated_rect):
         super().__init__(
             segmented_object.xmin,
             segmented_object.ymin,
@@ -113,6 +113,7 @@ def __init__(self, segmented_object):
             segmented_object.str_label,
             segmented_object.mask,
         )
+        self.rotated_rect = rotated_rect
 
     def __str__(self):
         res = super().__str__()
@@ -139,14 +140,15 @@ def __str__(self):
 def add_rotated_rects(segmented_objects):
     objects_with_rects = []
     for segmented_object in segmented_objects:
-        objects_with_rects.append(SegmentedObjectWithRects(segmented_object))
         mask = segmented_object.mask.astype(np.uint8)
         contours, hierarchies = cv2.findContours(
             mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE
         )
 
         contour = np.vstack(contours)
-        objects_with_rects[-1].rotated_rect = cv2.minAreaRect(contour)
+        objects_with_rects.append(
+            SegmentedObjectWithRects(segmented_object, cv2.minAreaRect(contour))
+        )
     return objects_with_rects