问题描述
在将一个数组送入tensorflow训练时,报错如下:
ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type numpy.ndarray)
数组元素为数组,每个数组元素的shape不一致,示例如下:
cropImg[0].shape = (13, 13, 3)
cropImg[1].shape = (14, 13, 3)
cropImg[2].shape = (12, 13, 3)
环境
python 3.7.9
tensorflow 2.6.0
keras 2.6.0
解决方法
stackoverflow上有许多类似的报错,大概意思都是数据类型错误,转换的数据类型非报错中括号里的数据类型,如:
Unsupported object type numpy.ndarray指cropImg数组元素不是numpy.ndarray类型。
博主非常不解,尝试了许多方法,都显示cropImg数组元素数据类型为numpy.ndarray,但错误一直存在。
后来突然转念,在生成cropImg数组时,有一个warning:
VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify \'dtype=object\' when creating the ndarray
cropImg_ar = np.array(img_list)
cropImg数组元素为shape不一致的数组,这说明cropImg数组元素类型实际上为object,会不会是tensorflow不接受object类型的数据导致的?
将cropImg数组元素转换为shape一致后,问题解决。
参考链接
https://stackoverflow.com/questions/62570936/valueerror-failed-to-convert-a-numpy-array-to-a-tensor-unsupported-object-type
https://stackoverflow.com/questions/58636087/tensorflow-valueerror-failed-to-convert-a-numpy-array-to-a-tensor-unsupporte
https://blog.csdn.net/liveshow021_jxb/article/details/112752145
来源:https://www.cnblogs.com/go8t/p/15705970.html
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