import os 
import torch

IMG_EXTENSIONS = [
    '.jpg', '.JPG', '.jpeg', '.JPEG',
    '.png', '.PNG', '.ppm', '.PPM', '.bmp', '.BMP',
]


def is_image_file(filename):
    return any(filename.endswith(extension) for extension in IMG_EXTENSIONS)


def make_dataset(dir):
    images = []
    assert os.path.isdir(dir), '%s is not a valid directory' % dir

    for root, _, fnames in sorted(os.walk(dir)):
        for fname in fnames:
            if is_image_file(fname):
                path = os.path.join(root, fname)
                images.append(path)

    return images


def edge_compute(x):
    x_diffx = torch.abs(x[:,:,1:] - x[:,:,:-1])
    x_diffy = torch.abs(x[:,1:,:] - x[:,:-1,:])

    y = x.new(x.size())
    y.fill_(0)
    y[:,:,1:] += x_diffx
    y[:,:,:-1] += x_diffx
    y[:,1:,:] += x_diffy
    y[:,:-1,:] += x_diffy
    y = torch.sum(y,0,keepdim=True)/3
    y /= 4
    return y