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Merged
saeugetier merged 2 commits into from
Nov 13, 2025
Merged

220 reduced resolution neural network for preview #224

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aded92d
Add support for 320x320 input size in YOLOv11SegDetectorNcnn constructor
saeugetier Nov 13, 2025
71cd33b
Add NCNN_LOW_RES option for faster preview in neural network runtime …
saeugetier Nov 13, 2025
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4 changes: 2 additions & 2 deletions qml/SettingsMenuForm.ui.qml
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Original file line number Diff line number Diff line change
Expand Up @@ -242,8 +242,8 @@ Item {
id: comboBoxNeuralNetworkRuntime
textRole: "text"
valueRole: "value"
model: [{text: "ONNX Runtime", value: "ONNX"}, {text: "NCNN Runtime", value: "NCNN"}]
Layout.preferredWidth: 200
model: [{text: "ONNX Runtime", value: "ONNX"}, {text: "NCNN Runtime", value: "NCNN"}, {text: "NCNN Runtime (faster preview)", value: "NCNN_LOW_RES"} ]
Layout.preferredWidth: 250
}
}
}
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14 changes: 14 additions & 0 deletions src/replacebackgroundvideofilter.cpp
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Expand Up @@ -57,6 +57,10 @@ void ReplaceBackgroundVideoFilter::setNeuralNetworkRuntime(QString runtime)
{
newRuntime = NeuralNetworkRuntime::ONNX;
}
else if (runtime.contains("NCNN_LOW_RES"))
{
newRuntime = NeuralNetworkRuntime::NCNN_LOW_RES;
}
else if (runtime.contains("NCNN"))
{
newRuntime = NeuralNetworkRuntime::NCNN;
Expand Down Expand Up @@ -111,6 +115,10 @@ QString ReplaceBackgroundVideoFilter::getNeuralNetworkRuntime() const
{
return QString("NCNN");
}
else if (mNeuralNetworkRuntime == NeuralNetworkRuntime::NCNN_LOW_RES)
{
return QString("NCNN_LOW_RES");
}
else
{
return QString("Unknown");
Expand Down Expand Up @@ -317,6 +325,12 @@ void ReplaceBackgroundFilterRunable::changeNeuralNetworkRuntime(const NeuralNetw
mYoloSegmentorPreview.reset(new YOLOv11SegDetectorNcnn("yolo11n-seg_ncnn_model", "coco.names", false));
mYoloSegmentorHighRes.reset(new YOLOv11SegDetectorNcnn("yolo11x-seg_ncnn_model", "coco.names", false));
}
else if (runtime == NeuralNetworkRuntime::NCNN_LOW_RES)
{
qDebug() << "[INFO] Change YOLOv11Segmentation runtime to NCNN_LOW_RES";
mYoloSegmentorPreview.reset(new YOLOv11SegDetectorNcnn("yolo11n-seg_ncnn_model_320", "coco.names", false, true));
mYoloSegmentorHighRes.reset(new YOLOv11SegDetectorNcnn("yolo11x-seg_ncnn_model", "coco.names", false));
}
}

void ReplaceBackgroundFilterRunable::prepareBackground(cv::Mat &bg, cv::Size size)
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3 changes: 2 additions & 1 deletion src/replacebackgroundvideofilter.h
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Expand Up @@ -17,7 +17,8 @@ class ReplaceBackgroundFilterRunable;
enum class NeuralNetworkRuntime
{
ONNX,
NCNN
NCNN,
NCNN_LOW_RES
};

class ReplaceBackgroundVideoFilter : public QVideoFrameInput
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13 changes: 10 additions & 3 deletions src/yolo11segncnn.cpp
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Expand Up @@ -9,7 +9,7 @@

YOLOv11SegDetectorNcnn::YOLOv11SegDetectorNcnn(const std::string &modelPath,
const std::string &labelsPath,
bool useGPU) : Yolo11Segementation(labelsPath)
bool useGPU, bool use320x320input) : Yolo11Segementation(labelsPath)
{
QString ressourcePathGeneric = QStandardPaths::locate(QStandardPaths::GenericDataLocation, "models", QStandardPaths::LocateDirectory);
QString ressourcePathApp = QStandardPaths::locate(QStandardPaths::AppDataLocation, "models", QStandardPaths::LocateDirectory);
Expand Down Expand Up @@ -48,7 +48,14 @@ YOLOv11SegDetectorNcnn::YOLOv11SegDetectorNcnn(const std::string &modelPath,
numOutputNodes = net.output_names().size();

isDynamicInputShape = false; // Assume static input shape by default. NCNN models typically have fixed input shapes.
inputImageShape = cv::Size(640, 640); // Default shape. This is fixed for YOLOv11SegNCNN

if(use320x320input) {
inputImageShape = cv::Size(320, 320);
}
else
{
inputImageShape = cv::Size(640, 640); // Default shape. This is fixed for YOLOv11SegNCNN
}

// Input
if (numInputNodes != 1)
Expand Down Expand Up @@ -277,7 +284,7 @@ std::vector<Segmentation> YOLOv11SegDetectorNcnn::segment(const cv::Mat &image,
cv::Scalar(114, 114, 114), /*auto_=*/false,
/*scaleFill=*/false, /*scaleUp=*/true, /*stride=*/32);

ncnn::Mat in = ncnn::Mat::from_pixels_resize(letterboxImage.data, ncnn::Mat::PIXEL_BGR2RGB, letterboxImage.cols, letterboxImage.rows, 640, 640);
ncnn::Mat in = ncnn::Mat::from_pixels_resize(letterboxImage.data, ncnn::Mat::PIXEL_BGR2RGB, letterboxImage.cols, letterboxImage.rows, inputImageShape.width, inputImageShape.height);

const float norm_vals[3] = {1 / 255.f, 1 / 255.f, 1 / 255.f};
in.substract_mean_normalize(0, norm_vals);
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2 changes: 1 addition & 1 deletion src/yolo11segncnn.h
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Expand Up @@ -30,7 +30,7 @@ class YOLOv11SegDetectorNcnn : public Yolo11Segementation {
public:
YOLOv11SegDetectorNcnn(const std::string &modelPath,
const std::string &labelsPath,
bool useGPU = false);
bool useGPU = false, bool use320x320input = false);

// Main API
std::vector<Segmentation> segment(const cv::Mat &image,
Expand Down