def image_blurrer():
for f in os.listdir(BASE_DIR):
# check if the files are image
if f.endswith('.png' or '.jpg' or '.jpeg'):
print("Working on : " + f)
# Make the image object
i = Image.open(BASE_DIR + f)
# split the image name
fname, fext = os.path.splitext(f)
i.filter(ImageFilter.BLUR())
i.save('{}image_blur/{}_blur_30{}'.format(BASE_DIR, fname, fext))
else:
print("cant work on : " + f)
def calculate_fitness_blur_mean_difference(original_image, generated_image):
if original_image.width != generated_image.width:
print('FITNESS ERROR! Images are different.')
# Calculate difference between two images
original_image = ImageEnhance.Contrast(original_image).enhance(1.5)
generated_image = ImageEnhance.Contrast(generated_image).enhance(1.5)
difference = ImageChops.difference(original_image, generated_image)
# Blur image
difference = difference.filter(ImageFilter.BLUR())
# Calculate average brightness of differential image, this tells us how similar those images are
stats = ImageStat.Stat(difference)
average_brightness = (stats.rms[0] + stats.rms[1] + stats.rms[2]) / 3
# Return fitness value
return (255 - average_brightness) / 255
def blur(image: Image.Image) -> Image.Image:
return _apply_filter(image, ImageFilter.BLUR())
def blur_affine(img):
img = img.filter(ImageFilter.BLUR(1))
shear = transforms.RandomAffine(shear=0.2)
return (sheat(img))
