onnx模型转换到rknn脚本

from rknn.api import RKNN

ONNX_MODEL = './onnx_models/yolov5s_rm_transpose.onnx'

platform="rk1808"

platform = "rv1109"

RKNN_MODEL = 'yolov5s_relu_{}_out_opt.rknn'.format(platform)

if name == 'main':

add_perm = False # 如果设置成True,则将模型输入layout修改成NHWC

Create RKNN object

rknn = RKNN(verbose=True)

pre-process config

print('--> config model')

rknn.config(batch_size=1, mean_values=[[0, 0, 0]], std_values=[[255, 255, 255]], reorder_channel='0 1 2', target_platform=[platform],

force_builtin_perm=add_perm, output_optimize=1)

print('done')

Load tensorflow model

print('--> Loading model')

ret = rknn.load_onnx(model=ONNX_MODEL)

if ret != 0:

print('Load resnet50v2 failed!')

exit(ret)

print('done')

Build model

print('--> Building model')

ret = rknn.build(do_quantization=True, dataset='./dataset.txt')

if ret != 0:

print('Build resnet50 failed!')

exit(ret)

print('done')

rknn.export_rknn_precompile_model(RKNN_MODEL)

rknn.export_rknn(RKNN_MODEL)

rknn.release()