# python – ValueError: could not broadcast input array from shape (224,224,3) into shape (224,224)

## python – ValueError: could not broadcast input array from shape (224,224,3) into shape (224,224)

At least one item in your list is either not three dimensional, or its second or third dimension does not match the other elements. If only the first dimension does not match, the arrays are still matched, but as individual objects, no attempt is made to reconcile them into a new (four dimensional) array. Some examples are below:

That is, the offending elements `shape != (?, 224, 3)`

,

or `ndim != 3`

(with the `?`

being non-negative integer).

That is what is giving you the error.

Youll need to fix that, to be able to turn your list into a four (or three) dimensional array. Without context, it is impossible to say if you want to lose a dimension from the 3D items or add one to the 2D items (in the first case), or change the second or third dimension (in the second case).

Heres an example of the error:

```
>>> a = [np.zeros((224,224,3)), np.zeros((224,224,3)), np.zeros((224,224))]
>>> np.array(a)
ValueError: could not broadcast input array from shape (224,224,3) into shape (224,224)
```

or, different type of input, but the same error:

```
>>> a = [np.zeros((224,224,3)), np.zeros((224,224,3)), np.zeros((224,224,13))]
>>> np.array(a)
Traceback (most recent call last):
File <stdin>, line 1, in <module>
ValueError: could not broadcast input array from shape (224,224,3) into shape (224,224)
```

Alternatively, similar but with a different error message:

```
>>> a = [np.zeros((224,224,3)), np.zeros((224,224,3)), np.zeros((224,100,3))]
>>> np.array(a)
Traceback (most recent call last):
File <stdin>, line 1, in <module>
ValueError: could not broadcast input array from shape (224,224,3) into shape (224)
```

But the following will work, albeit with different results than (presumably) intended:

```
>>> a = [np.zeros((224,224,3)), np.zeros((224,224,3)), np.zeros((10,224,3))]
>>> np.array(a)
# long output omitted
>>> newa = np.array(a)
>>> newa.shape
3 # oops
>>> newa.dtype
dtype(O)
>>> newa[0].shape
(224, 224, 3)
>>> newa[1].shape
(224, 224, 3)
>>> newa[2].shape
(10, 224, 3)
>>>
```

Yea, Indeed @Evert answer is perfectly correct.

In addition Ill like to add one more reason that could encounter such error.

```
>>> np.array([np.zeros((20,200)),np.zeros((20,200)),np.zeros((20,200))])
```

This will be perfectly fine, However, This leads to error:

```
>>> np.array([np.zeros((20,200)),np.zeros((20,200)),np.zeros((20,201))])
ValueError: could not broadcast input array from shape (20,200) into shape (20)
```

The numpy arry within the list, must also be the same size.

#### python – ValueError: could not broadcast input array from shape (224,224,3) into shape (224,224)

You can covert `numpy.ndarray`

to `object`

using `astype(object)`

This will work:

```
>>> a = [np.zeros((224,224,3)).astype(object), np.zeros((224,224,3)).astype(object), np.zeros((224,224,13)).astype(object)]
```