NanoTrack在NPU C++部署时的问题 about lighttrack-ncnn HOT 4 OPEN

参考的:https://github.com/Try2ChangeX/NanoTrack_RK3588_python 项目利用这个项目的模型文件，直接用python跑是正常的，然后参考您之前那个lighttrack的项目和nanotrack的ncnn项目做的，目前的问题是跟踪结果完全不正确，下附后处理部分的代码链接:https://github.com/fly-miao/issure_code
可能存在的问题：
1.模型是未量化的，是fp16
backbone_T.rknn的参数：
model input num: 1, output num: 1
index=0, name=x.3, n_dims=4, dims=[1, 127, 127, 3], n_elems=48387, size=96774, fmt=NHWC, type=FP16, qnt_type=AFFINE, zp=0, scale=1.000000
index=0, name=975, n_dims=4, dims=[1, 48, 8, 8], n_elems=3072, size=6144, fmt=NCHW, type=FP16, qnt_type=AFFINE, zp=0, scale=1.000000
model is NHWC input fmt
model is NCHW output fmt
backbone_X.rknn的参数：
model input num: 1, output num: 1
index=0, name=x.3, n_dims=4, dims=[1, 255, 255, 3], n_elems=195075, size=390150, fmt=NHWC, type=FP16, qnt_type=AFFINE, zp=0, scale=1.000000
index=0, name=975, n_dims=4, dims=[1, 48, 16, 16], n_elems=12288, size=24576, fmt=NCHW, type=FP16, qnt_type=AFFINE, zp=0, scale=1.000000
model is NHWC input fmt
model is NCHW output fmt
head.rknn的参数：
model input num: 2, output num: 2
index=0, name=z_f.1, n_dims=4, dims=[1, 8, 8, 48], n_elems=3072, size=6144, fmt=NHWC, type=FP16, qnt_type=AFFINE, zp=0, scale=1.000000
index=1, name=x_f.1, n_dims=4, dims=[1, 16, 16, 48], n_elems=12288, size=24576, fmt=NHWC, type=FP16, qnt_type=AFFINE, zp=0, scale=1.000000
index=0, name=231, n_dims=4, dims=[1, 2, 16, 16], n_elems=512, size=1024, fmt=NCHW, type=FP16, qnt_type=AFFINE, zp=0, scale=1.000000
index=1, name=26, n_dims=4, dims=[1, 4, 16, 16], n_elems=1024, size=2048, fmt=NCHW, type=FP16, qnt_type=AFFINE, zp=0, scale=1.000000
model is NHWC input fmt
model is NCHW output fmt
2.我看这个的python项目中没有bgr转rgb的操作，我默认使用bgr输入(也试过rgb，结果也是不对)
3.后处理部分，我完全按照lighttrack那个项目的操作没有改

from lighttrack-ncnn.

有没有对比python版本推理的output与C++版本的output是否有一样？

from lighttrack-ncnn.

I'm having the same problems, is there any progress?

from lighttrack-ncnn.

When I examine the models one by one in Netron App, I see that the inputs of the models are in NCHW format. However, when I load the model using the RKNPU2 C++ APIs, I see that the inputs are in NHWC format. Therefore, I believe that the implementation is not working correctly. How can I resolve this issue?

from lighttrack-ncnn.