I have a vector representation of n = 1000 images, where each image is represented as 2048 numbers. So I have a numpy array with a shape of (1000, 2048) that I need to find the mean of in a 2048-d vector. If I run this function:
def get_means(f_embeddings):
means = []
for embedding in f_embeddings:
means.append(np.mean(embedding))
return np.array(means)
I get an ndarray of shape (1000,). How do I loop loop over the array correctly to have a 2048-d vector of means from the original array?
CodePudding user response:
Try:
np.mean(f_embeddings, axis=0)
which should do it without the loop.