int32_t minInputWidth = std::max(m_options.minInputWidth, inputW);
// this options.minInputWidth (at least from within this function) can be bigger than inputW, if user set it big and dont use
// so in result you have
/*
kMIN m_options.minInputWidth
kOPT inputW
kMAX inputW
*/
if (doesSupportDynamicBatch) {
optProfile->setDimensions(inputName, nvinfer1::OptProfileSelector::kMIN, nvinfer1::Dims4(1, inputC, inputH, minInputWidth));
} else {
optProfile->setDimensions(inputName, nvinfer1::OptProfileSelector::kMIN,
nvinfer1::Dims4(m_options.optBatchSize, inputC, inputH, minInputWidth));
}fix:
int32_t minInputWidth = std::max(m_options.minInputWidth, inputW);
if (not doesSupportDynamicWidth) {minInputWidth = inputW;}also engine is build on assumption that it will be used with rgb image
but it is not
we (now) have different input/output model
i not made code by myself, i just changed yours
so, ill either create my repo based on your code, or fork-pull_request to make different api(basically rewrite) in different folder in your repository
now i plan to make different layers and get rid of exceptions (use tl::expected instead), and for this github repo instead of directly using logger replace with re-entering
fix:
also engine is build on assumption that it will be used with rgb image
but it is not
we (now) have different input/output model
i not made code by myself, i just changed yours
so, ill either create my repo based on your code, or fork-pull_request to make different api(basically rewrite) in different folder in your repository
now i plan to make different layers and get rid of exceptions (use tl::expected instead), and for this github repo instead of directly using logger replace with re-entering