41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
from rknn.api import RKNN
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def convert_det_model():
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# 创建RKNN对象
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rknn = RKNN(verbose=True)
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# 配置模型
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print('--> Config model')
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rknn.config(
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mean_values=[[123.675, 116.28, 103.53]],
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std_values=[[58.395, 57.12, 57.375]],
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# mean_values=[[0, 0, 0]],
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# std_values=[[255, 255, 255]],
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# quant_img_RGB2BGR=True,
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target_platform='rk3588') # 根据您的芯片型号调整
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# 加载ONNX模型
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print('--> Loading model')
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ret = rknn.load_onnx(model='/home/admin-root/haotian/康达瑞贝斯机器狗/det_shape_20250814.onnx')
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if ret != 0:
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print('Load model failed!')
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exit(ret)
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# 构建模型
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print('--> Building model')
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ret = rknn.build(do_quantization=False
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# , dataset='./det_dataset.txt'
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)
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if ret != 0:
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print('Build model failed!')
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exit(ret)
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# 导出RKNN模型
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ret = rknn.export_rknn('./det_shape_255.rknn')
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if ret != 0:
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print('Export model failed!')
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exit(ret)
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rknn.release()
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convert_det_model() |