bug

Scheaven

2021-07-23 2cacbb0be4b0c6591a0a72a57be4a7ed005db762

 src/detecter_tools/model.cpp

@@ -268,12 +268,72 @@
void Detecter::setOutput(int type)
{
    m_OutputTensors.clear();
    if(type==0)
        for (int i = 0; i < 3; ++i)
    printf("0-0-0-0-0-0------------------%d",type);
    if(type==2)
        for (int i = 0; i < 2; ++i)
        {
            TensorInfo outputTensor;
            outputTensor.numClasses = CLASS_BUM;
            outputTensor.blobName = "yolo_" + std::to_string(i);
            outputTensor.gridSize = (m_InputH / 32) * pow(2, i);
            outputTensor.grid_h = (m_InputH / 32) * pow(2, i);
            outputTensor.grid_w = (m_InputW / 32) * pow(2, i);
            outputTensor.stride = m_InputH / outputTensor.gridSize;
            outputTensor.stride_h = m_InputH / outputTensor.grid_h;
            outputTensor.stride_w = m_InputW / outputTensor.grid_w;
            outputTensor.numBBoxes = 3;
            outputTensor.volume = outputTensor.grid_h* outputTensor.grid_w
                *(outputTensor.numBBoxes*(5 + outputTensor.numClasses));
            if(i==1)
            {
                outputTensor.masks.push_back(1);
                outputTensor.masks.push_back(2);
                outputTensor.masks.push_back(3);
            }
            if(i==0)
            {
                outputTensor.masks.push_back(3);
                outputTensor.masks.push_back(4);
                outputTensor.masks.push_back(5);
            }
            outputTensor.anchors.push_back(10);
            outputTensor.anchors.push_back(14);
            outputTensor.anchors.push_back(23);
            outputTensor.anchors.push_back(27);
            outputTensor.anchors.push_back(37);
            outputTensor.anchors.push_back(58);
            outputTensor.anchors.push_back(81);
            outputTensor.anchors.push_back(82);
            outputTensor.anchors.push_back(135);
            outputTensor.anchors.push_back(169);
            outputTensor.anchors.push_back(344);
            outputTensor.anchors.push_back(319);

            if (m_ClassNames.empty())
            {
                for (uint32_t j=0;j< outputTensor.numClasses;++j)
                {
                    m_ClassNames.push_back(std::to_string(j));
                }
            }
            m_OutputTensors.push_back(outputTensor);
        }
    else
        for (int i = 0; i < 3; ++i)
        {
            TensorInfo outputTensor;
            outputTensor.numClasses = CLASS_BUM;
            outputTensor.blobName = "yolo_" + to_string(i);
            // if (i==0)
            // {
            //     outputTensor.blobName = "139_convolutional_reshape_2";
            // }else if (i==1)
            // {
            //     outputTensor.blobName = "150_convolutional_reshape_2";
            // }else if (i==2)
            // {
            //     outputTensor.blobName = "161_convolutional_reshape_2";
            // }
            outputTensor.gridSize = (m_InputH / 32) * pow(2, 2-i);
            outputTensor.grid_h = (m_InputH / 32) * pow(2, 2-i);
            outputTensor.grid_w = (m_InputW / 32) * pow(2, 2-i);
@@ -319,56 +379,6 @@
            outputTensor.anchors.push_back(243);
            outputTensor.anchors.push_back(459);
            outputTensor.anchors.push_back(401);

            if (m_ClassNames.empty())
            {
                for (uint32_t j=0;j< outputTensor.numClasses;++j)
                {
                    m_ClassNames.push_back(std::to_string(j));
                }
            }
            m_OutputTensors.push_back(outputTensor);
        }
    else
        for (int i = 0; i < 2; ++i)
        {

            TensorInfo outputTensor;
            outputTensor.numClasses = CLASS_BUM;
            outputTensor.blobName = "yolo_" + std::to_string(i);
            outputTensor.gridSize = (m_InputH / 32) * pow(2, i);
            outputTensor.grid_h = (m_InputH / 32) * pow(2, i);
            outputTensor.grid_w = (m_InputW / 32) * pow(2, i);
            outputTensor.stride = m_InputH / outputTensor.gridSize;
            outputTensor.stride_h = m_InputH / outputTensor.grid_h;
            outputTensor.stride_w = m_InputW / outputTensor.grid_w;
            outputTensor.numBBoxes = 3;
            outputTensor.volume = outputTensor.grid_h* outputTensor.grid_w
                *(outputTensor.numBBoxes*(5 + outputTensor.numClasses));
            if(i==1)
            {
                outputTensor.masks.push_back(1);
                outputTensor.masks.push_back(2);
                outputTensor.masks.push_back(3);
            }
            if(i==0)
            {
                outputTensor.masks.push_back(3);
                outputTensor.masks.push_back(4);
                outputTensor.masks.push_back(5);
            }
            outputTensor.anchors.push_back(10);
            outputTensor.anchors.push_back(14);
            outputTensor.anchors.push_back(23);
            outputTensor.anchors.push_back(27);
            outputTensor.anchors.push_back(37);
            outputTensor.anchors.push_back(58);
            outputTensor.anchors.push_back(81);
            outputTensor.anchors.push_back(82);
            outputTensor.anchors.push_back(135);
            outputTensor.anchors.push_back(169);
            outputTensor.anchors.push_back(344);
            outputTensor.anchors.push_back(319);

            if (m_ClassNames.empty())
            {