def main():
signal.signal(signal.SIGINT, signal_handler)
console = Console()
global gruvbox_factory
gruvbox_factory = GoNord()
gruvbox_factory.reset_palette()
add_gruvbox_palette()
console.print(
Panel('🏭 [bold green] Gruvbox Factory [/] 🏭',
expand=False,
border_style='yellow'))
console.print(
'⚠️ WARNING ⚠️\n[italic]make sure you\'re in the same directory of the image you want to convert [/]\n'
)
image_file = console.input(
'🖼️ [bold yellow]Which image do you want to manufacture?[/] ')
try:
image = gruvbox_factory.open_image(image_file)
except:
console.print(
'❌ [red]We had a problem in the pipeline! Make sure you\'re in the same path of the image you want to convert! [/]'
)
sys.exit(0)
console.print('🔨 [yellow]manufacturing your gruvbox wallpaper...[/]')
gruvbox_factory.convert_image(image, save_path=('gruvbox_' + image_file))
console.print('✅ [bold green]Done![/] [green](saved as gruvbox_' +
image_file + ')[/]')
def main():
signal.signal(signal.SIGINT, signal_handler)
console = Console()
gruvbox_factory = GoNord()
gruvbox_factory.reset_palette()
add_gruvbox_palette(gruvbox_factory)
# Checks if there's an argument
if len(sys.argv) > 1:
image_paths = fromCommandArgument(console)
else:
image_paths = fromTui(console)
for image_path in image_paths:
if os.path.isfile(image_path):
process_image(image_path, console, gruvbox_factory)
else:
console.print(
f"❌ [red]We had a problem in the pipeline! \nThe image at '{image_path}' could not be found! \nSkipping... [/]"
)
continue
def main():
parser = argparse.ArgumentParser()
parser.add_argument('input', help='File to generate image from.')
parser.add_argument(
'-s',
'--show',
help='Show image using xdg-open when image is generated.',
action='store_true')
parser.add_argument('-b',
'--blur',
help='Blur the image',
action='store_true')
parser.add_argument(
'--no_quantize',
help=
'Do not quantize the image before processing (may make the image look better)',
action='store_true')
args = parser.parse_args()
sInputImage = args.input
sOutputPath = './nordified/' + path.splitext(
path.basename(sInputImage))[0] + '-nordified.jpg'
print(f"Writing nordified version to {sOutputPath}..")
go_nord = GoNord()
image = go_nord.open_image(sInputImage)
if args.blur:
image = image.filter(ImageFilter.GaussianBlur(5))
go_nord.set_default_nord_palette()
#go_nord.disable_avg_algorithm()
image = go_nord.quantize_image(image, save_path=sOutputPath)
#go_nord.convert_image(image, save_path=sOutputPath)
# To base64
#go_nord.image_to_base64(image, 'jpeg')
print("Done.")
if args.show:
run('xdg-open {}'.format(sOutputPath), shell=True)
#!/usr/bin/env python
import argparse
from ImageGoNord import GoNord
parser = argparse.ArgumentParser(
description='convert image palette to specified palette')
parser.add_argument('colorscheme', type=str, help='name of the colorscheme')
parser.add_argument('image', type=str, help='path to the image')
args = parser.parse_args()
path = "/home/samy/.config/colorschemes/" + args.colorscheme
with open(path, 'r') as f:
lines = f.readlines()
colors = [line.split()[2] for line in lines]
go_nord = GoNord()
go_nord.reset_palette()
for color in colors:
go_nord.add_color_to_palette(color)
print(args.image)
image = go_nord.open_image(args.image)
go_nord.convert_image(image, save_path='/home/samy/Wallpapers/wall.png')
def test_resize_image(image: Image, go_nord: GoNord):
resized_image = go_nord.resize_image(image)
w, h = image.size
assert resized_image.size == (round(w / 2), round(h / 2))
def test_resize_image_with_size(image, go_nord: GoNord):
resized_image = go_nord.resize_image(image, size=(20, 20))
assert resized_image.size == (20, 20)
def test_resize_image_with_w_and_h(image, go_nord: GoNord):
resized_image = go_nord.resize_image(image, w=20, h=20)
assert resized_image.size == (20, 20)
def go_nord():
return GoNord()
from ImageGoNord import NordPaletteFile, GoNord
go_nord = GoNord()
"""image = go_nord.open_image("images/test-profile.jpg")
go_nord.convert_image(image, save_path='images/test.processed.jpg') """
# E.g. Avg algorithm and less colors
go_nord.enable_avg_algorithm()
go_nord.reset_palette()
# go_nord.add_file_to_palette(NordPaletteFile.POLAR_NIGHT)
# go_nord.add_file_to_palette(NordPaletteFile.SNOW_STORM)
# go_nord.add_color_to_palette('#FF0000')
go_nord.set_default_nord_palette()
image = go_nord.open_image("images/test.jpg")
go_nord.convert_image(image, save_path='images/test.avg.jpg')
# E.g. Resized img no Avg algorithm and less colors
go_nord.disable_avg_algorithm()
go_nord.reset_palette()
go_nord.add_file_to_palette(NordPaletteFile.POLAR_NIGHT)
go_nord.add_file_to_palette(NordPaletteFile.SNOW_STORM)
image = go_nord.open_image("images/test.jpg")
resized_img = go_nord.resize_image(image)
go_nord.convert_image(resized_img, save_path='images/test.resized.jpg')
# E.g. Quantize
image = go_nord.open_image("images/test.jpg")
go_nord.reset_palette()
wallpaper_ids = [sub['uniqid'] for sub in wallpaper_submissions]
ign_ids = [sub['uniqid'] for sub in ign_submissions]
wallpapers_to_process = [
x for x in wallpaper_submissions if x['uniqid'] not in ign_ids
]
print('Wallpaper processabili e unici: ' + str(len(wallpapers_to_process)))
if len(wallpapers_to_process) > 0:
published_post = 0
for sub in wallpapers_to_process:
if published_post >= MAX_POST_TO_PUBLISH:
break
go_nord = GoNord()
go_nord.set_default_nord_palette()
go_nord.enable_avg_algorithm()
for palette_key in FLAIR:
go_nord.reset_palette()
IGN_TITLE_PREFIX = '[' + palette_key + '] '
for hex_color in FLAIR[palette_key]['hex_colors']:
go_nord.add_color_to_palette(hex_color)
im = go_nord.base64_to_image(
base64.b64encode(requests.get(sub['url']).content))
img_path = 'images/' + sub['uniqid'] + '.' + sub['url'][-3:]
print('Processing ' + sub['title'])
try:
args = sys.argv[1:]
if len(args) == 0:
print(__doc__)
sys.exit(1)
# If help given then print the docstring of the module and exit
if "--help" in args or "-h" in args:
print(__doc__)
sys.exit(0)
if "--version" in args or "-v" in args:
print(VERSION)
sys.exit(0)
go_nord = GoNord()
IMAGE_ARGUMENT_PATTERN = r'-(-img|i)=*'
IS_IMAGE_PASSED = False
for arg in args:
searched_arg = re.search(IMAGE_ARGUMENT_PATTERN, arg)
if searched_arg is not None:
IS_IMAGE_PASSED = True
break
if not IS_IMAGE_PASSED:
to_console(confarg.logs["img"][1].format(arg), confarg.logs["img"][-1],
confarg.logs["err"][0])
sys.exit(1)
QUIET_MODE = "-q" in args or "--quiet" in args
def main():
dirOld = "/home/mir/Pictures/wallhaven/"
dirNew = "/home/mir/Pictures/newWall/"
for root, dirs, files in os.walk(dirOld):
for file in files:
imagePath = dirOld + file
name = file.split(".", 1)
oName = name[0] + "-Nord." + name[1]
savePath = dirNew + oName
# E.g. Replace pixel by pixel
go_nord = GoNord()
image = go_nord.open_image(imagePath)
go_nord.convert_image(image, save_path=savePath)
# E.g. Avg algorithm and less colors
go_nord.enable_avg_algorithm()
go_nord.reset_palette()
go_nord.add_file_to_palette(NordPaletteFile.POLAR_NIGHT)
go_nord.add_file_to_palette(NordPaletteFile.SNOW_STORM)
# You can add color also by their hex code
go_nord.add_color_to_palette("#FF0000")
image = go_nord.open_image(imagePath)
go_nord.convert_image(image, save_path=savePath)
# E.g. Resized img no Avg algorithm and less colors
go_nord.disable_avg_algorithm()
go_nord.reset_palette()
go_nord.add_file_to_palette(NordPaletteFile.POLAR_NIGHT)
go_nord.add_file_to_palette(NordPaletteFile.SNOW_STORM)
image = go_nord.open_image(imagePath)
resized_img = go_nord.resize_image(image)
go_nord.convert_image(resized_img, save_path=savePath)
# E.g. Quantize
image = go_nord.open_image(imagePath)
go_nord.reset_palette()
go_nord.set_default_nord_palette()
quantize_image = go_nord.quantize_image(image, save_path=savePath)
# To base64
go_nord.image_to_base64(quantize_image, "jpeg")
def setup_instance(req):
go_nord = GoNord()
hex_colors = []
if req.form.get('colors'):
hex_colors = req.form.get('colors').split(',')
if len(hex_colors) > 0:
go_nord.reset_palette()
for hex_color in hex_colors:
go_nord.add_color_to_palette(hex_color)
if req.form.get('is_avg'):
go_nord.enable_avg_algorithm()
if req.form.get('avg_box_width') and req.form.get('avg_box_height'):
go_nord.set_avg_box_data(int(req.form.get('avg_box_width')), int(req.form.get('avg_box_height')))
if req.form.get('blur'):
go_nord.enable_gaussian_blur()
return go_nord