Hello, everyone
I want to speed up YoloV3 on my TX2 by using TensorRT.
I have already convert Darknet model to Caffe model and I can implement YoloV2 by TensorRT now.
I have reference the deepstream2.0 yolov3 example and it didn’t has upsampling layer in plugin layer.
I guessed it use deconvolution instead of upsampling. Is it right ?
My prototxt is as below. If so. Could I directly change the “Upsample” to “Deconvolution” and rewrite the param?
layer {
bottom: "layer85-conv"
top: "layer85-conv"
name: "layer85-act"
type: "ReLU"
relu_param {
negative_slope: 0.1
}
}
layer {
bottom: "layer85-conv"
top: "layer86-upsample"
name: "layer86-upsample"
type: "Upsample"
upsample_param {
scale: 2
}
}
layer {
bottom: "layer86-upsample"
bottom: "layer62-shortcut"
top: "layer87-route"
name: "layer87-route"
type: "Concat"
}