def process(self, img):
import numpy
from PIL import Image
out = kernels.gaussian_blur_filter(
numpy.array(img),
sigma=self.n)
return Image.fromarray(out)
if __name__ == '__main__':
from PIL import Image
from instakit.utils import static
image_paths = map(
lambda image_file: static.path('img', image_file),
static.listfiles('img'))
image_inputs = map(
lambda image_path: Image.open(image_path).convert('RGB'),
image_paths)
for image_input in image_inputs:
#image_input.show()
#GaussianBlur(n=3).process(image_input).show()
Contour().process(image_input).show()
Detail().process(image_input).show()
Emboss().process(image_input).show()
EdgeEnhance().process(image_input).show()
EdgeEnhanceMore().process(image_input).show()
FindEdges().process(image_input).show()
Smooth().process(image_input).show()
SmoothMore().process(image_input).show()
def names(cls):
return [curve_file.rstrip('.acv') \
for curve_file in static.listfiles('acv') \
if curve_file.lower().endswith('.acv')]
else:
self.nY = n
def process(self, img):
import numpy
from PIL import Image
out = kernels.gaussian_blur_filter(numpy.array(img), sigma=self.n)
return Image.fromarray(out)
if __name__ == '__main__':
from PIL import Image
from instakit.utils import static
image_paths = map(lambda image_file: static.path('img', image_file),
static.listfiles('img'))
image_inputs = map(
lambda image_path: Image.open(image_path).convert('RGB'), image_paths)
for image_input in image_inputs:
#image_input.show()
#GaussianBlur(n=3).process(image_input).show()
Contour().process(image_input).show()
Detail().process(image_input).show()
Emboss().process(image_input).show()
EdgeEnhance().process(image_input).show()
EdgeEnhanceMore().process(image_input).show()
FindEdges().process(image_input).show()
Smooth().process(image_input).show()
SmoothMore().process(image_input).show()
Sharpen().process(image_input).show()
def names(cls):
return [curve_file.rstrip('.acv') \
for curve_file in static.listfiles('acv') \
if curve_file.lower().endswith('.acv')]
