can‘t convert np.ndarray of type numpy.object_. The only supported types are: float64, float32, floa

报错：

Traceback (most recent call last):File "train.py", line 116, in <module>trainer.train()File "/home/xinying/CDCN-Face-Anti-Spoofing.pytorch/trainer/FASTrainer.py", line 160, in trainimg, depth_map, depth_map_15, depth_map_8, depth_map_5 = self.patch_exchange(img, depth_map, target_shape=(32, 32, 3))File "/home/xinying/CDCN-Face-Anti-Spoofing.pytorch/trainer/FASTrainer.py", line 128, in patch_exchangeimages = torch.from_numpy(np.array(images))
TypeError: can't convert np.ndarray of type numpy.object_. The only supported types are: float64, float32, float16, complex64, complex128, int64, int32, int16, int8, uint8, and bool

问题描述：
当把np转换成torch tensor时，

trainx = torch.from_numpy(np.reshape(train_x, newshape=(-1,25)))

解决方法：
由于读入的numpy数组里的元素是object类型，无法将这种类型转换成tensor。

所以，将numpy数组进行强制类型转换成float类型（或者任何pytorch支持的类型：float64, float32, float16, int64, int32, int16, int8, uint8, and bool）即可。

trainx = trainx.astype(float)  # numpy强制类型转换

images.append(img_i.cpu().numpy())
images = torch.from_numpy(np.array(images))

即可

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can‘t convert np.ndarray of type numpy.object_. The only supported types are: float64, float32, floa

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