Getting black image!

[Coderx7]

First of all thank you very much for this.
When I try to run your example code with these two images, I always get a black image!

This is the whole code which is given in the first page , I just replaced the random numpy array statement with these two images!:

import imgaug as ia
from imgaug import augmenters as iaa
import numpy as np

im = caffe.io.load_image('buckskin_s_000331.png')
im2 = caffe.io.load_image('buckskin_s_000005.png')
images = np.zeros([2,32,32,3])
images[0] = im
images[1] = im2
# Sometimes(0.5, ...) applies the given augmenter in 50% of all cases,
# e.g. Sometimes(0.5, GaussianBlur(0.3)) would blur roughly every second image.
st = lambda aug: iaa.Sometimes(0.3, aug)

# Define our sequence of augmentation steps that will be applied to every image
# All augmenters with per_channel=0.5 will sample one value _per image_
# in 50% of all cases. In all other cases they will sample new values
# _per channel_.
seq = iaa.Sequential([
        iaa.Fliplr(0.5), # horizontally flip 50% of all images
        iaa.Flipud(0.5), # vertically flip 50% of all images
        st(iaa.Superpixels(p_replace=(0, 1.0), n_segments=(20, 200))), # convert images into their superpixel representation
        st(iaa.Crop(percent=(0, 0.1))), # crop images by 0-10% of their height/width
        st(iaa.GaussianBlur((0, 3.0))), # blur images with a sigma between 0 and 3.0
        st(iaa.Sharpen(alpha=(0, 1.0), strength=(0.75, 1.5))), # sharpen images
        st(iaa.Emboss(alpha=(0, 1.0), strength=(0, 2.0))), # emboss images
        # search either for all edges or for directed edges
        st(iaa.Sometimes(0.5,
            iaa.EdgeDetect(alpha=(0, 0.7)),
            iaa.DirectedEdgeDetect(alpha=(0, 0.7), direction=(0.0, 1.0)),
        )),
        st(iaa.AdditiveGaussianNoise(loc=0, scale=(0.0, 0.2), per_channel=0.5)), # add gaussian noise to images
        st(iaa.Dropout((0.0, 0.1), per_channel=0.5)), # randomly remove up to 10% of the pixels
        st(iaa.Invert(0.25, per_channel=True)), # invert color channels
        st(iaa.Add((-10, 10), per_channel=0.5)), # change brightness of images (by -10 to 10 of original value)
        st(iaa.Multiply((0.5, 1.5), per_channel=0.5)), # change brightness of images (50-150% of original value)
        st(iaa.ContrastNormalization((0.5, 2.0), per_channel=0.5)), # improve or worsen the contrast
        st(iaa.Affine(
            scale={"x": (0.8, 1.2), "y": (0.8, 1.2)}, # scale images to 80-120% of their size, individually per axis
            translate_px={"x": (-16, 16), "y": (-16, 16)}, # translate by -16 to +16 pixels (per axis)
            rotate=(-45, 45), # rotate by -45 to +45 degrees
            shear=(-16, 16), # shear by -16 to +16 degrees
            order=ia.ALL, # use any of scikit-image's interpolation methods
            cval=(0, 255), # if mode is constant, use a cval between 0 and 255
            mode=ia.ALL # use any of scikit-image's warping modes (see 2nd image from the top for examples)
        )),
        st(iaa.ElasticTransformation(alpha=(0.5, 3.5), sigma=0.25)) # apply elastic transformations with random strengths
    ],
    random_order=True # do all of the above in random order
)

images_aug = seq.augment_images(images)
plt.imshow(images_aug[0])
plt.show()

what is wrong here?

[Coderx7]

OK, I ran some more tests individually on each of those options, it seems onlyiaa.Fliplr(0.5)and iaa.Flipud(0.5) work. the rest result in a black image which I posted above!
What am I missing here?!
(By the way I'm on windows10.)

[aleju]

caffe's load_image seems to return floats in the range 0-1.0, while the library usually expects uint8 in the range 0-255. So you would have to do something like (img*255).astype(np.uint8) after loading the images.
Considering your image size of 32x32, the number of augmenters is also rather large. You should probably decrease each augmenters probability by changing st = lambda aug: iaa.Sometimes(0.3, aug) to st = lambda aug: iaa.Sometimes(0.1, aug).
Further, you should use something like seq.show_grid(images[0], rows=8, cols=8) to show your augmenters results instead of plt.imshow(images_aug[0]), as the latter one will result in the same augmentation at every script run.

[Coderx7]

@aleju : Thank you very much. The black image issue is gone.
and speaking of seg.show_grid(), it fails for me with this error RuntimeError: Could not execute image viewer.
I could'nt find a way to solve it, I have no idea whats causing this! so thats why I used the plt.imshow instead

[aleju]

The threads that I can find sound like the command see must be available for misc.imshow to work (or an image viewer must be set in the environment variable SCIPY_PIL_IMAGE_VIEWER). I guess that command isn't available in Windows 10. Maybe I'll switch to OpenCV's imshow equivalent.

[Coderx7]

I installed see through pip yet I still get the same error.

[aleju]

I meant a command line program see, not a pypi package with that name, i.e. you must be able to type see in the command line and not get an error (that's how I understood it from the help threads - the program seems to be available on Ubuntu by default).

[wanghaisheng]

how to install the see program over mac os