Description
Using the block of code below,
parser->parseFromFile(
onnx_file_path.c_str(), static_cast<int>(nvinfer1::ILogger::Severity::kINFO));
std::vector<nvinfer1::ITensor *> scores, boxes, classes;
const auto input = network->getInput(0);
const auto num_outputs = network->getNbOutputs();
std::cout<<num_outputs<<std::endl;
const auto input_dims = input->getDimensions();
const auto input_channel = input_dims.d[1];
const auto input_height = input_dims.d[2];
const auto input_width = input_dims.d[3];
for (int i = 0; i < num_outputs; ++i) {
auto output = network->getOutput(i);
std::vector<float> anchor(
yolo_config.anchors.begin() + i * yolo_config.num_anchors * 2,
yolo_config.anchors.begin() + (i + 1) * yolo_config.num_anchors * 2);
auto yoloLayerPlugin = yolo::YoloLayerPlugin(
input_width, input_height, 3, anchor, yolo_config.scale_x_y[i], yolo_config.score_thresh,
yolo_config.use_darknet_layer);
std::vector<nvinfer1::ITensor *> inputs = {output};
auto layer = network->addPluginV2(inputs.data(), inputs.size(), yoloLayerPlugin);
scores.push_back(layer->getOutput(0));
boxes.push_back(layer->getOutput(1));
classes.push_back(layer->getOutput(2));
}
std::cout<<"SCORES !!!!!!!!!!!!!!!!!!!!!!"<< scores.size() <<std::endl;
std::cout<<"BOXES !!!!!!!!!!!!!!!!!!!!!!"<< boxes.size() <<std::endl;
std::cout<<"CLASSES !!!!!!!!!!!!!!!!!!!!!!"<< classes.size() <<std::endl;
// Cleanup outputs
for (int i = 0; i < num_outputs; i++) {
std::cout<<"Output "<<i<<std::endl;
auto output = network->getOutput(i);
network->unmarkOutput(*output);
}
// Concat tensors from each feature map
std::vector<nvinfer1::ITensor *> concat;
for (auto tensors : {scores, boxes, classes}) {
std::cout<<"ADDING !!!!!!!!!!!!!!!!!!!!!! "<< tensors.data()<< tensors.data() <<std::endl;
auto layer = network->addConcatenation(tensors.data(), tensors.size());
layer->setAxis(1);
std::cout<<"ADDED !!!!!!!!!!!!!!!!!!!!!!"<<std::endl;
auto output = layer->getOutput(0);
concat.push_back(output);
}
I get num_outputs = 0. When I manually set num_outputs it yields;
Parameter check failed at: ../builder/Layers.cpp::PluginV2Layer::1728, condition: (inputs[0]) != nullptr
Parameter check failed at: ../builder/Layers.cpp::PluginV2Layer::1728, condition: (inputs[0]) != nullptr
Parameter check failed at: ../builder/Layers.cpp::PluginV2Layer::1728, condition: (inputs[0]) != nullptr
By doing
model = onnx.load('yolov4.onnx')
output = model.graph.output
I can get output nodes correctly. So i guess onnx model is ok.
Environment
TensorRT Version: 7.0.0.11
GPU Type: RTX2070
Nvidia Driver Version: 460
CUDA Version: 10.0
CUDNN Version: 7.6.5
ONNX Version: 1.6.0
Relevant files
I use this onnx model.