STRCL-SSCD/augment.py at main · zxt9/STRCL-SSCD · GitHub

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import PIL.ImageEnhance
import PIL.ImageOps
from PIL import Image
import matplotlib.pyplot as plt
import numpy as np

file_name = 'A.png'
img=Image.open(file_name)

augment_method = 'equalize'

# blur
if augment_method == 'blur':
    from PIL import Image, ImageFilter
    class MyGaussianBlur(ImageFilter.Filter):
        name = "GaussianBlur"

        def __init__(self, radius=2, bounds=None):
            self.radius = radius
            self.bounds = bounds

        def filter(self, image):
            if self.bounds:
                clips = image.crop(self.bounds).gaussian_blur(self.radius)
                image.paste(clips, self.bounds)
                return image
            else:
                return image.gaussian_blur(self.radius)
    img = img.filter(MyGaussianBlur(radius=3))

elif augment_method == "solarize":
    img = PIL.ImageOps.solarize(img, 120)

elif augment_method == "posterize":
    img = PIL.ImageOps.posterize(img, 3)

elif augment_method =='autocontrast':
    img = PIL.ImageOps.autocontrast(img)

elif augment_method == 'brightness':
    img = PIL.ImageEnhance.Brightness(img).enhance(0.5)

elif augment_method == 'color':
    img = PIL.ImageEnhance.Color(img).enhance(0.2)

elif augment_method == 'equalize':
    img = PIL.ImageOps.equalize(img)

elif augment_method == 'sharpness':
    img = PIL.ImageEnhance.Sharpness(img).enhance(0.9)

img.save(augment_method + '.png', quality=95)
plt.figure("augment")
plt.imshow(img)
plt.show()