How do I convert an array of two colour images to an array of two gray scale images using the
to_grayscale (from this site) function below.
Important: I don’t want image files, I want the array
image_g defined below.
First create the function and sample images:
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams['image.cmap'] = 'gray'
tile = np.tile(np.c_[0.333, 0.333, 0.333], reps=(im.shape,im.shape,1))
return np.sum(tile * im, axis=2)
images = np.random.randint(0, 255, 24).reshape(2, 2, 2, 3)
out> (2, 2, 2, 3)
How do I convert
images to an array of gray scale images
image_g ? I’d like to do something like this:
image_g = np.somefunction(to_grayscale, images)
out> (2, 2, 2)
somefunction is a placeholder for the answer.
if you really want to use what you write, then check out these methods to map a function to an array (mapping is what your “somefunction” would mean):
But I would not use that, the easiest and fastest way of greyscaling I know using the mean would be this one line:
images_g = np.mean(images, -1)
At least for your example above it looks identical (looking at the pics with
plt.imshow() ) and is fully vectorized = fast, faster than mapping your python function (which is irrelevant for 2 pics, but I assume that’s not your usecase…)
Thanks to the link, it seems this should be on par with the fastest method:
images_g = np.array([to_grayscale(images[i]) for i in range(images.shape)])
Please let me know if there is a more elegant way to do this (except for
np.mean which is great for the specific case where I don’t ever need to change the
0.333 values in the function).
It would be really nice if Fast.ai had a default function for this purpose!
Do you mean opening images as grayscale by default? ImageList and open_image take a convert_mode argument. See docs
Yes, but they take data from a path correct?
Having a numpy -> fastai Image and vice versa would be helpful without and file save, or file open… if there is a one line way of doing this please let me know!