from rknnlite.api import RKNNLite
import numpy as np

model_path = '/userdata/reenrr/inference_with_lite/mobilenetv2_640.rknn'

rknn_lite = RKNNLite()
rknn_lite.load_rknn(model_path)
rknn_lite.init_runtime()

# 通过实际推理获取输出维度
dummy_input = np.random.randn(1, 3, 640, 640).astype(np.float32)  # 根据模型输入尺寸调整
outputs = rknn_lite.inference(inputs=[dummy_input])

print("\n输出维度信息:")
for i, out in enumerate(outputs):
    print(f"Output {i} shape: {out.shape}")  # 查看输出形状

rknn_lite.release()