jenkins: linux-gnu, armeabi-v7, windows
Change-Id: I572b43a41344bfe438e18a2a5892b6b7be416e36
diff --git a/GreenScreen/pluginInference.h b/GreenScreen/pluginInference.h
index 37436af..8d405f8 100644
--- a/GreenScreen/pluginInference.h
+++ b/GreenScreen/pluginInference.h
@@ -15,7 +15,8 @@
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
- * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301
+ * USA.
*/
#pragma once
@@ -26,59 +27,58 @@
#include <opencv2/core.hpp>
// STL
#include <array>
-#include <vector>
-#include <tuple>
#include <iostream>
+#include <tuple>
+#include <vector>
namespace jami {
-class PluginInference : public TensorflowInference {
+class PluginInference : public TensorflowInference
+{
public:
- /**
- * @brief PluginInference
- * Is a type of supervised learning where we detect objects in images
- * Draw a bounding boxes around them
- * @param model
- */
- PluginInference(TFModel model);
- ~PluginInference();
+ /**
+ * @brief PluginInference
+ * Is a type of supervised learning where we detect objects in images
+ * Draw a bounding boxes around them
+ * @param model
+ */
+ PluginInference(TFModel model);
+ ~PluginInference();
#ifdef TFLITE
- /**
- * @brief getInput
- * Returns the input where to fill the data
- * Use this method if you know what you are doing, all the necessary checks
- * on dimensions must be done on your part
- * @return std::tuple<uint8_t *, std::vector<int>>
- * The first element in the tuple is the pointer to the storage location
- * The second element is a dimensions vector that will helps you make
- * The necessary checks to make your data size match the input one
- */
- std::pair<uint8_t*, std::vector<int>> getInput();
+ /**
+ * @brief getInput
+ * Returns the input where to fill the data
+ * Use this method if you know what you are doing, all the necessary checks
+ * on dimensions must be done on your part
+ * @return std::tuple<uint8_t *, std::vector<int>>
+ * The first element in the tuple is the pointer to the storage location
+ * The second element is a dimensions vector that will helps you make
+ * The necessary checks to make your data size match the input one
+ */
+ std::pair<uint8_t*, std::vector<int>> getInput();
#else
- void ReadTensorFromMat(const cv::Mat& image);
+ void ReadTensorFromMat(const cv::Mat& image);
-#endif //TFLITE
+#endif // TFLITE
- std::vector<float> masksPredictions() const;
+ std::vector<float> masksPredictions() const;
+ /**
+ * @brief setExpectedImageDimensions
+ * Sets imageWidth and imageHeight from the sources
+ */
+ void setExpectedImageDimensions();
- /**
- * @brief setExpectedImageDimensions
- * Sets imageWidth and imageHeight from the sources
- */
- void setExpectedImageDimensions();
-
- // Getters
- int getImageWidth() const;
- int getImageHeight() const;
- int getImageNbChannels() const;
-
+ // Getters
+ int getImageWidth() const;
+ int getImageHeight() const;
+ int getImageNbChannels() const;
private:
- int imageWidth = 0;
- int imageHeight = 0;
- int imageNbChannels = 0;
+ int imageWidth = 0;
+ int imageHeight = 0;
+ int imageNbChannels = 0;
};
} // namespace jami