I am a beginner in python programming and was learning how to code a project from YouTube when I got stuck on the following code.
The full code is here: https://github.com/nikhilroxtomar/Retina-Blood-Vessel-Segmentation-using-UNET-in-TensorFlow/blob/main/data.py and the YouTube where it appears is at 24:30 - https://youtu.be/tpbWZVY2dng?t=1470 )
from albumentations import HorizontalFlip
def augment_data(images, masks, save_path, augment=True):
for idx, (x, y) in tqdm(enumerate(zip(images, masks)), total=len(images)):
""" Extracting names """
name = x.split("/")[-1].split(".")[0]
""" Reading image and mask """
x = cv2.imread(x, cv2.IMREAD_COLOR)
y = imageio.mimread(y)[0]
if augment == True:
aug = HorizontalFlip(p=1.0)
augmented = aug(image=x, mask=y)
x1 = augmented["image"]
y1 = augmented["mask"]
This part is what I don't understand
if augment == True:
aug = HorizontalFlip(p=1.0)
augmented = aug(image=x, mask=y)
x1 = augmented["image"]
y1 = augmented["mask"]
How is aug being used to take input parameters of an image? Is augmented being used as a dictionary? Can you please explain how?
aug
is instance of albumentations.augmentations.transforms.HorizontalFlip
class
Then if you look at the source code you will see that it inherits from
albumentations.core.transforms_interface.DualTransform
class which looking at the source code inherits from BasicTransform
class.
Looking at the BasicTransform
class you can see it implements __call__()
method. It takes variable number of keyword arguments **kwargs
and after some processing returns kwargs
(i.e. when you call aug()
). kwargs
is a dict with arguments you pass. In your case the keys are image
and mask
.
As a side note, instead of if augment == True:
it should be just if augment: