Transform Mona Lisa to grayscale using numpy array manipulation

mona_lisa.py

# Based on  https://www.degeneratestate.org/posts/2016/Oct/23/image-processing-with-numpy/

import numpy as np
import matplotlib.pylab as plt
import matplotlib.gridspec as gridspec

%matplotlib inline

original = plt.imread("mona_lisa_full.jpg")

original.shape

def plot(image1, image2, h=8, **kwargs):
    plt.close('all')
    fig = plt.figure(figsize=(16, 16))

    gs1 = gridspec.GridSpec(1, 2)
    ax1 = fig.add_subplot(gs1[0])
    ax2 = fig.add_subplot(gs1[1])
    ax1.axis("off")

    ax2.axis("off")

    ax1.imshow(image1, interpolation="none", **kwargs)
    ax2.imshow(image2, interpolation="none", **kwargs)

    gs1.tight_layout(fig)    

def to_grayscale(image, weights = np.c_[0.2989, 0.5870, 0.1140]):
    """
    Transforms a colour image to a grayscale image by
    taking the mean of the RGB values, weighted
    by the matrix weights
    """
    tile = np.tile(weights, reps=(im.shape[0],im.shape[1],1))
    return np.sum(tile * im, axis=2)

grayscale = to_grayscale(original)



plot(original, grayscale, cmap='gray')

Thanks for a function image resolution example!
Can you suggest sites or books which further discuss image manipulation with Numpy? I am preparing an Intermediate Python course for fall and I will use numpy, pandas, matplotlib and sympy.
leesmith404@gmail.com

Thanks for your comment.

Obviously google has several suggestions. I found the scipy lectures site to be very useful for a formal tutorial.

The link at the top of the gist https://www.degeneratestate.org/posts/2016/Oct/23/image-processing-with-numpy/ was the best example I could find.

Kaggle has several competitions on image processing and folks have posted their notebooks e.g. https://www.kaggle.com/akshayt19nayak/getting-started-image-processing-basics

WOW ! You spend almost as much time on the web as I do ! I will follow up on your suggestions. I have only found one book intended as a text for Intermediate Python. Know of any? lee

…

On Fri, Nov 29, 2019 at 5:56 PM Rajaram Gurumurthi ***@***.***> wrote: Thanks for your comment. Obviously google has several suggestions. I found the scipy lectures <https://scipy-lectures.org/advanced/image_processing/> site to be very useful for a formal tutorial. The link at the top of the git https://www.degeneratestate.org/posts/2016/Oct/23/image-processing-with-numpy/ was the best example I could find. Kaggle has several competitions on image processing and folks have posted their notebooks e.g. https://www.kaggle.com/akshayt19nayak/getting-started-image-processing-basics — You are receiving this because you commented. Reply to this email directly, view it on GitHub <https://gist.github.com/2a692ab879ea906b1cdbcae02bf2ed56?email_source=notifications&email_token=ADZORBU4TECR7XXJTHHQJDDQWHB4TA5CNFSM4JTEMTG2YY3PNVWWK3TUL52HS4DFVNDWS43UINXW23LFNZ2KUY3PNVWWK3TUL5UWJTQAF5AHQ#gistcomment-3096696>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ADZORBQZ2RYMOVBX44LKKR3QWHB4TANCNFSM4JTEMTGQ> .

sorry, no - google is my main tutor. I did buy this once for my kids and found it was useful for grown ups as well.