def gen_input_data(root_img, root_mask):
img_list = glob(os.path.join(root_img, '*.jpg'))
mask_list = glob(os.path.join(root_mask, '*.tif'))
mask_list = [os.path.basename(i) for i in mask_list]
img_list_exist = []
for i in img_list:
if (os.path.basename(i).split('.')[0] + '_OD.tif') in mask_list:
img_list_exist.append(i)
for i in img_list_exist:
img_file = i
mask_file = os.path.join(root_mask,
os.path.basename(i).split('.')[0] + '_OD.tif')
img = scipy.misc.imread(img_file)
img = img.astype(np.float32)
img /= 255
img_crop, params = tight_crop_params(img)
img_ahe = channelwise_ahe(img_crop)
raw_img = Image.fromarray(skimage.util.img_as_ubyte(img_crop))
ahe_img = Image.fromarray(skimage.util.img_as_ubyte(img_ahe))
mask = Image.open(mask_file)
scale_size = 512
pilImage_rescaled = scale_image(raw_img, scale_size)
pilAHE_rescaled = scale_image(ahe_img, scale_size)
pilMask_rescaled = scale_image_mask(mask, params, scale_size)
image_basename = os.path.basename(i).split('.')[0]
out_imagename = os.path.join(out_img, image_basename + '.png')
out_ahename = os.path.join(out_ahe, image_basename + '_ahe.png')
out_maskname = os.path.join(out_mask, image_basename + '_ahe_mask.png')
pilImage_rescaled.save(out_imagename)
print('save {}'.format(out_imagename))
pilAHE_rescaled.save(out_ahename)
print('save {}'.format(out_ahename))
pilMask_rescaled.save(out_maskname)
print('save {}'.format(out_maskname))
print('\n')
def crop_and_scale_imageandmask(img_file, mask_file, scale_size):
img = scipy.misc.imread(img_file)
img = img.astype(np.float32)
img /= 255
img_crop, params = tight_crop_params(img)
pilImage = Image.fromarray(skimage.util.img_as_ubyte(img_crop))
pilMask = Image.open(mask_file)
pilImage_rescaled = scale_image(pilImage, scale_size)
pilMask_rescaled = scale_image_mask(pilImage, scale_size)
return pilImage_rescaled, pilMask_rescaled
root = '../../data/IDRID/IDRID 3/test'
out_img = os.path.join(root, 'raw')
out_ahe = os.path.join(root, 'ahe')
os.makedirs(out_img, exist_ok=True)
os.makedirs(out_ahe, exist_ok=True)
root_img = '../../data/IDRID/IDRID 3/Training a and b'
img_file = '../../data/IDRID/IDRID 3/Training c/IDRiD_01.jpg'
img = scipy.misc.imread(img_file)
img = img.astype(np.float32)
img /= 255
img_crop, params = tight_crop_params(img)
def scale_image(image, scale_size):
w, h = image.size
tw, th = (scale_size, scale_size)
ratio_w = tw / w
if ratio_w < 1:
image = image.resize((tw, th), Image.CUBIC)
elif ratio_w > 1:
image = image.resize((tw, th), Image.CUBIC)
return image
def scale_image_mask(pil_img, params, scale_size):
mask = pil_img.convert('RGB')
np_mask = np.array(mask)