使用api进行nv12 to rgb 的转换，没有起效

可以把多batch的输入[6*3*640*640]分成六个[1*3*640*640],但是

insert_image_convert转化没有起效,依然是rgb的输入

import os

import onnx

from hbdk4.compiler.onnx import export

from hbdk4.compiler import convert, compile, visualize, save

script_dir = os.path.dirname(os.path.realpath(__file__))

model_path = os.path.join(script_dir, "bev_fushion/hbm/bev_occ_lane_int16_100", "bev_occ_lane_int16_100_ptq_model.onnx")

onnx_model = onnx.load(model_path)

model = export(onnx_model)

func = model.functions[0]

# 将BATCH拆分开

func.inputs[0].insert_split(dim=0)

for input in func.inputs[::-1]:

if input.name != "img":

print(f"Skip non-image input: {input.name}")

continue

input = input.insert_transpose(permutes=[0, 2, 3, 1])

input = input.insert_image_preprocess(

mode="yuvbt601full2rgb",

divisor=255,

mean=[123.675, 116.28, 103.53],

std=[0.01712475, 0.017507, 0.01742919]

)

y, uv = input.insert_image_convert("nv12")

save(model, os.path.join(script_dir, "model_output_v2", "sample_addpre.bc"))

quantized_model = convert(model, march="nash-e")

save(quantized_model, os.path.join(script_dir, "model_output_v2", "sample_quantized_split.bc"))

hbm = compile(quantized_model, march="nash-e",path=os.path.join(script_dir, "model_output_v2", "sample.hbm"), debug=True,

opt=0, jobs=40, progress_bar=True)