20 lines
553 B
Python
20 lines
553 B
Python
from rknnlite.api import RKNNLite
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import numpy as np
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model_path = '/userdata/reenrr/inference_with_lite/mobilenetv2_640.rknn'
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rknn_lite = RKNNLite()
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rknn_lite.load_rknn(model_path)
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rknn_lite.init_runtime()
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# 通过实际推理获取输出维度
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dummy_input = np.random.randn(1, 3, 640, 640).astype(np.float32) # 根据模型输入尺寸调整
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outputs = rknn_lite.inference(inputs=[dummy_input])
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print("\n输出维度信息:")
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for i, out in enumerate(outputs):
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print(f"Output {i} shape: {out.shape}") # 查看输出形状
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rknn_lite.release()
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