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[CORE] Minor changes to handle YoloV11
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LAGNEAU Romain committed Oct 16, 2024
1 parent a65eebc commit 1272b22
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Showing 2 changed files with 16 additions and 10 deletions.
8 changes: 5 additions & 3 deletions modules/detection/include/visp3/detection/vpDetectorDNNOpenCV.h
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Original file line number Diff line number Diff line change
Expand Up @@ -74,6 +74,7 @@ BEGIN_VISP_NAMESPACE
* - Yolo v5, see usage to detect objects belonging to the COCO dataset using \ref dnn_supported_yolov5 network
* - Yolo v7, see usage to detect objects belonging to the COCO dataset using \ref dnn_supported_yolov7 network
* - Yolo v8, see usage to detect objects belonging to the COCO dataset using \ref dnn_supported_yolov8 network
* - Yolo v11, see usage to detect objects belonging to the COCO dataset using \ref dnn_supported_yolov11 network
*
* This class can be initialized from a JSON file if ViSP has been compiled with NLOHMANN JSON (see \ref soft_tool_json to see how to do it).
* Examples of such JSON files can be found in the tutorial folder.
Expand All @@ -98,8 +99,9 @@ class VISP_EXPORT vpDetectorDNNOpenCV
YOLO_V4 = 5, /*!< The \b vpDetectorDNNOpenCV object will use the parsing method corresponding to a YoloV4 DNN. See \b vpDetectorDNNOpenCV::postProcess_YoloV3_V4 for more information.*/
YOLO_V5 = 6, /*!< The \b vpDetectorDNNOpenCV object will use the parsing method corresponding to a YoloV5 DNN. See \b vpDetectorDNNOpenCV::postProcess_YoloV5_V7 for more information.*/
YOLO_V7 = 7, /*!< The \b vpDetectorDNNOpenCV object will use the parsing method corresponding to a YoloV7 DNN. See \b vpDetectorDNNOpenCV::postProcess_YoloV5_V7 for more information.*/
YOLO_V8 = 8, /*!< The \b vpDetectorDNNOpenCV object will use the parsing method corresponding to a YoloV8 DNN. See \b vpDetectorDNNOpenCV::postProcess_YoloV8 for more information.*/
COUNT = 9 /*!< The number of parsing method that come along with the \b vpDetectorDNNOpenCV class.*/
YOLO_V8 = 8, /*!< The \b vpDetectorDNNOpenCV object will use the parsing method corresponding to a YoloV8 DNN. See \b vpDetectorDNNOpenCV::postProcess_YoloV8_V11 for more information.*/
YOLO_V11 = 9, /*!< The \b vpDetectorDNNOpenCV object will use the parsing method corresponding to a YoloV11 DNN. See \b vpDetectorDNNOpenCV::postProcess_YoloV8_V11 for more information.*/
COUNT = 10 /*!< The number of parsing method that come along with the \b vpDetectorDNNOpenCV class.*/
} DNNResultsParsingType;

typedef struct DetectionCandidates
Expand Down Expand Up @@ -560,7 +562,7 @@ class VISP_EXPORT vpDetectorDNNOpenCV

void postProcess_YoloV5_V7(DetectionCandidates &proposals, std::vector<cv::Mat> &dnnRes, const NetConfig &netConfig);

void postProcess_YoloV8(DetectionCandidates &proposals, std::vector<cv::Mat> &dnnRes, const NetConfig &netConfig);
void postProcess_YoloV8_V11(DetectionCandidates &proposals, std::vector<cv::Mat> &dnnRes, const NetConfig &netConfig);

void postProcess_FasterRCNN(DetectionCandidates &proposals, std::vector<cv::Mat> &dnnRes, const NetConfig &netConfig);

Expand Down
18 changes: 11 additions & 7 deletions modules/detection/src/dnn/vpDetectorDNNOpenCV.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -50,7 +50,7 @@ BEGIN_VISP_NAMESPACE
*
* \return std::string The list of the supported parsing methods / types of DNNs.
*/
std::string vpDetectorDNNOpenCV::getAvailableDnnResultsParsingTypes()
std::string vpDetectorDNNOpenCV::getAvailableDnnResultsParsingTypes()
{
std::string list = "[";
for (unsigned int i = 0; i < vpDetectorDNNOpenCV::COUNT - 1; i++) {
Expand Down Expand Up @@ -88,6 +88,9 @@ std::string vpDetectorDNNOpenCV::dnnResultsParsingTypeToString(const DNNResultsP
case YOLO_V8:
name = "yolov8";
break;
case YOLO_V11:
name = "yolov11";
break;
case FASTER_RCNN:
name = "faster-rcnn";
break;
Expand Down Expand Up @@ -474,7 +477,7 @@ std::vector<cv::String> vpDetectorDNNOpenCV::getOutputsNames()
names.resize(outLayers.size());
for (size_t i = 0; i < outLayers.size(); ++i)
names[i] = layersNames[outLayers[i] - 1];
}
}
return names;
}
#endif
Expand All @@ -499,7 +502,8 @@ void vpDetectorDNNOpenCV::postProcess(DetectionCandidates &proposals)
postProcess_YoloV5_V7(proposals, m_dnnRes, m_netConfig);
break;
case YOLO_V8:
postProcess_YoloV8(proposals, m_dnnRes, m_netConfig);
case YOLO_V11:
postProcess_YoloV8_V11(proposals, m_dnnRes, m_netConfig);
break;
case FASTER_RCNN:
postProcess_FasterRCNN(proposals, m_dnnRes, m_netConfig);
Expand Down Expand Up @@ -815,7 +819,7 @@ void vpDetectorDNNOpenCV::postProcess_YoloV5_V7(DetectionCandidates &proposals,
\param dnnRes: raw results of the \b vpDetectorDNNOpenCV::detect step.
\param netConfig: the configuration of the network, to know for instance the DNN input size.
*/
void vpDetectorDNNOpenCV::postProcess_YoloV8(DetectionCandidates &proposals, std::vector<cv::Mat> &dnnRes, const NetConfig &netConfig)
void vpDetectorDNNOpenCV::postProcess_YoloV8_V11(DetectionCandidates &proposals, std::vector<cv::Mat> &dnnRes, const NetConfig &netConfig)
{
// Code adapted from here: https://github.com/JustasBart/yolov8_CPP_Inference_OpenCV_ONNX/blob/minimalistic/inference.cpp
// Compute the ratio between the original size of the image and the network size to translate network coordinates into
Expand Down Expand Up @@ -965,7 +969,7 @@ void vpDetectorDNNOpenCV::postProcess_SSD_MobileNet(DetectionCandidates &proposa
proposals.m_confidences.push_back(maxScore);
proposals.m_boxes.push_back(cv::Rect(left, top, width, height));
proposals.m_classIds.push_back(classId);
}
}
}
}
#endif
Expand Down Expand Up @@ -1146,7 +1150,7 @@ void vpDetectorDNNOpenCV::setPreferableTarget(const int &targetId) { m_net.setPr
void vpDetectorDNNOpenCV::setScaleFactor(const double &scaleFactor)
{
m_netConfig.m_scaleFactor = scaleFactor;
if ((m_netConfig.m_parsingMethodType == YOLO_V7 || m_netConfig.m_parsingMethodType == YOLO_V8) && m_netConfig.m_scaleFactor != 1 / 255.) {
if ((m_netConfig.m_parsingMethodType == YOLO_V7 || m_netConfig.m_parsingMethodType == YOLO_V8 || m_netConfig.m_parsingMethodType == YOLO_V11) && m_netConfig.m_scaleFactor != 1 / 255.) {
std::cout << "[vpDetectorDNNOpenCV::setParsingMethod] WARNING: scale factor should be 1/255. to normalize pixels value." << std::endl;
}
}
Expand All @@ -1169,7 +1173,7 @@ void vpDetectorDNNOpenCV::setParsingMethod(const DNNResultsParsingType &typePars
{
m_netConfig.m_parsingMethodType = typeParsingMethod;
m_parsingMethod = parsingMethod;
if ((m_netConfig.m_parsingMethodType == YOLO_V7 || m_netConfig.m_parsingMethodType == YOLO_V8) && m_netConfig.m_scaleFactor != 1 / 255.) {
if ((m_netConfig.m_parsingMethodType == YOLO_V7 || m_netConfig.m_parsingMethodType == YOLO_V8 || m_netConfig.m_parsingMethodType == YOLO_V11) && m_netConfig.m_scaleFactor != 1 / 255.) {
m_netConfig.m_scaleFactor = 1 / 255.;
std::cout << "[vpDetectorDNNOpenCV::setParsingMethod] NB: scale factor changed to 1/255. to normalize pixels value." << std::endl;
}
Expand Down

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