Ndtyjky

How can I use something like below line to save images on a grid of 4x4 of heterogenous images? Imagine that images are identified by sample[i] and i takes 16 different values.

scipy.misc.imsave(str(img_index) + '.png', sample[1])

Similar to this answer but for 16 different images
https://stackoverflow.com/a/42041135/2414957

I am not biased towards the used method as long as it does the deed. Also, I am interested in saving images rather than showing them using plt.show() as I am using a remote server and dealing with CelebA image dataset which is a giant dataset. I just want to randomly select 16 images from my batch and save the results of DCGAN and see if it makes any sense or if it converges.

*Currently, I am saving images like below:

batch_no = random.randint(0, 63)





scipy.misc.imsave('sample_gan_images/iter_%d_epoch_%d_sample_%d.png' %(itr, epoch, batch_no), sample[batch_no])

and here, I have 25 epochs and 2000 iterations and batch size is 64.

Personally, I tend to use matplotlib.pyplot.subplots for these kinds of situations. If your images are really heterogenous it might be a better choice than the image concatenation based approach in the answer you linked to.

import matplotlib.pyplot as plt

from scipy.misc import face



x = 4

y = 4



fig,axarr = plt.subplots(x,y)

ims = [face() for i in range(x*y)]



for ax,im in zip(axarr.ravel(), ims):

    ax.imshow(im)



fig.savefig('faces.png')

My big complaint about subplots is the quantity of whitespace in the resulting figure. As well, for your application you may not want the axes ticks/frames. Here's a wrapper function that deals with those issues:

import matplotlib.pyplot as plt



def savegrid(ims, rows=None, cols=None, fill=True, showax=False):

    if rows is None != cols is None:

        raise ValueError("Set either both rows and cols or neither.")



    if rows is None:

        rows = len(ims)

        cols = 1



    gridspec_kw = {'wspace': 0, 'hspace': 0} if fill else {}

    fig,axarr = plt.subplots(rows, cols, gridspec_kw=gridspec_kw)



    if fill:

        bleed = 0

        fig.subplots_adjust(left=bleed, bottom=bleed, right=(1 - bleed), top=(1 - bleed))



    for ax,im in zip(axarr.ravel(), ims):

        ax.imshow(im)

        if not showax:

            ax.set_axis_off()



    kwargs = {'pad_inches': .01} if fill else {}

    fig.savefig('faces.png', **kwargs)

Running savegrid(ims, 4, 4) on the same set of images as used earlier yields:

If you use savegrid, if you want each individual image to take up less space, pass the fill=False keyword arg. If you want to show the axes ticks/frames, pass showax=True.

I found this on github, also sharing it:

import matplotlib.pyplot as plt



def merge_images(image_batch, size):

    h,w = image_batch.shape[1], image_batch.shape[2]

    c = image_batch.shape[3]

    img = np.zeros((int(h*size[0]), w*size[1], c))

    for idx, im in enumerate(image_batch):

        i = idx % size[1]

        j = idx // size[1]

        img[j*h:j*h+h, i*w:i*w+w,:] = im

    return img



im_merged = merge_images(sample, [8,8])

plt.imsave('sample_gan_images/im_merged.png', im_merged )