I have managed to load images in a folder using the command line sklearn: load_sample_images()
I would now like to convert it to a numpy.ndarray
format with float32
datatype
I was able to convert it to np.ndarray
using : np.array(X)
, however np.array(X, dtype=np.float32)
and np.asarray(X).astype('float32')
give me the error:
ValueError: setting an array element with a sequence.
Is there a way to work around this?
from sklearn_theano.datasets import load_sample_images
import numpy as np
kinect_images = load_sample_images()
X = kinect_images.images
X_new = np.array(X) # works
X_new = np.array(X[1], dtype=np.float32) # works
X_new = np.array(X, dtype=np.float32) # does not work
The similarity between an array and a list is that the elements of both array and a list can be identified by its index value. In Python lists can be converted to arrays by using two methods from the NumPy library: Using numpy. array()
To convert a list to array in Python, use the np. array() method. The np. array() is a numpy library function that takes a list as an argument and returns an array containing all the list elements.
If you have a list of lists, you only needed to use ...
import numpy as np
...
npa = np.asarray(someListOfLists, dtype=np.float32)
per this LINK in the scipy / numpy documentation. You just needed to define dtype inside the call to asarray.
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