mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2026-02-08 20:42:32 +08:00
Remove 3.10 code for 3.8 code
This commit is contained in:
Silversith
parent
14d9b11a35
commit
8b7505d5bb
@ -12,8 +12,8 @@
|
|||||||
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||||
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
|
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
|
||||||
# THE SOFTWARE.
|
# THE SOFTWARE.
|
||||||
|
import image as image
|
||||||
|
import pilgram
|
||||||
from PIL import Image, ImageFilter, ImageEnhance, ImageOps, ImageDraw, ImageChops, ImageFont
|
from PIL import Image, ImageFilter, ImageEnhance, ImageOps, ImageDraw, ImageChops, ImageFont
|
||||||
from PIL.PngImagePlugin import PngInfo
|
from PIL.PngImagePlugin import PngInfo
|
||||||
from io import BytesIO
|
from io import BytesIO
|
||||||
@ -698,9 +698,6 @@ class WAS_Image_Style_Filter:
|
|||||||
subprocess.check_call(
|
subprocess.check_call(
|
||||||
[sys.executable, '-m', 'pip', '-q', 'install', 'pilgram'])
|
[sys.executable, '-m', 'pip', '-q', 'install', 'pilgram'])
|
||||||
|
|
||||||
# Import Pilgram module
|
|
||||||
import pilgram
|
|
||||||
|
|
||||||
# Convert image to PIL
|
# Convert image to PIL
|
||||||
image = tensor2pil(image)
|
image = tensor2pil(image)
|
||||||
|
|
||||||
@ -708,68 +705,66 @@ class WAS_Image_Style_Filter:
|
|||||||
WFilter = WAS_Filter_Class()
|
WFilter = WAS_Filter_Class()
|
||||||
|
|
||||||
# Apply blending
|
# Apply blending
|
||||||
match style:
|
if style == "1977":
|
||||||
case "1977":
|
out_image = pilgram._1977(image)
|
||||||
out_image = pilgram._1977(image)
|
elif style == "aden":
|
||||||
case "aden":
|
out_image = pilgram.aden(image)
|
||||||
out_image = pilgram.aden(image)
|
elif style == "brannan":
|
||||||
case "brannan":
|
out_image = pilgram.brannan(image)
|
||||||
out_image = pilgram.brannan(image)
|
elif style == "brooklyn":
|
||||||
case "brooklyn":
|
out_image = pilgram.brooklyn(image)
|
||||||
out_image = pilgram.brooklyn(image)
|
elif style == "clarendon":
|
||||||
case "clarendon":
|
out_image = pilgram.clarendon(image)
|
||||||
out_image = pilgram.clarendon(image)
|
elif style == "earlybird":
|
||||||
case "earlybird":
|
out_image = pilgram.earlybird(image)
|
||||||
out_image = pilgram.earlybird(image)
|
elif style == "fairy tale":
|
||||||
case "fairy tale":
|
out_image = WFilter.sparkle(image)
|
||||||
out_image = WFilter.sparkle(image)
|
elif style == "gingham":
|
||||||
case "gingham":
|
out_image = pilgram.gingham(image)
|
||||||
out_image = pilgram.gingham(image)
|
elif style == "hudson":
|
||||||
case "hudson":
|
out_image = pilgram.hudson(image)
|
||||||
out_image = pilgram.hudson(image)
|
elif style == "inkwell":
|
||||||
case "inkwell":
|
out_image = pilgram.inkwell(image)
|
||||||
out_image = pilgram.inkwell(image)
|
elif style == "kelvin":
|
||||||
case "kelvin":
|
out_image = pilgram.kelvin(image)
|
||||||
out_image = pilgram.kelvin(image)
|
elif style == "lark":
|
||||||
case "lark":
|
out_image = pilgram.lark(image)
|
||||||
out_image = pilgram.lark(image)
|
elif style == "lofi":
|
||||||
case "lofi":
|
out_image = pilgram.lofi(image)
|
||||||
out_image = pilgram.lofi(image)
|
elif style == "maven":
|
||||||
case "maven":
|
out_image = pilgram.maven(image)
|
||||||
out_image = pilgram.maven(image)
|
elif style == "mayfair":
|
||||||
case "mayfair":
|
out_image = pilgram.mayfair(image)
|
||||||
out_image = pilgram.mayfair(image)
|
elif style == "moon":
|
||||||
case "moon":
|
out_image = pilgram.moon(image)
|
||||||
out_image = pilgram.moon(image)
|
elif style == "nashville":
|
||||||
case "nashville":
|
out_image = pilgram.nashville(image)
|
||||||
out_image = pilgram.nashville(image)
|
elif style == "perpetua":
|
||||||
case "perpetua":
|
out_image = pilgram.perpetua(image)
|
||||||
out_image = pilgram.perpetua(image)
|
elif style == "reyes":
|
||||||
case "reyes":
|
out_image = pilgram.reyes(image)
|
||||||
out_image = pilgram.reyes(image)
|
elif style == "rise":
|
||||||
case "rise":
|
out_image = pilgram.rise(image)
|
||||||
out_image = pilgram.rise(image)
|
elif style == "slumber":
|
||||||
case "slumber":
|
out_image = pilgram.slumber(image)
|
||||||
out_image = pilgram.slumber(image)
|
elif style == "stinson":
|
||||||
case "stinson":
|
out_image = pilgram.stinson(image)
|
||||||
out_image = pilgram.stinson(image)
|
elif style == "toaster":
|
||||||
case "toaster":
|
out_image = pilgram.toaster(image)
|
||||||
out_image = pilgram.toaster(image)
|
elif style == "valencia":
|
||||||
case "valencia":
|
out_image = pilgram.valencia(image)
|
||||||
out_image = pilgram.valencia(image)
|
elif style == "walden":
|
||||||
case "walden":
|
out_image = pilgram.walden(image)
|
||||||
out_image = pilgram.walden(image)
|
elif style == "willow":
|
||||||
case "willow":
|
out_image = pilgram.willow(image)
|
||||||
out_image = pilgram.willow(image)
|
elif style == "xpro2":
|
||||||
case "xpro2":
|
out_image = pilgram.xpro2(image)
|
||||||
out_image = pilgram.xpro2(image)
|
else:
|
||||||
case _:
|
out_image = image
|
||||||
out_image = image
|
|
||||||
|
|
||||||
out_image = out_image.convert("RGB")
|
out_image = out_image.convert("RGB")
|
||||||
|
|
||||||
return (torch.from_numpy(np.array(out_image).astype(np.float32) / 255.0).unsqueeze(0), )
|
return (torch.from_numpy(np.array(out_image).astype(np.float32) / 255.0).unsqueeze(0),)
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
# COMBINE NODE
|
# COMBINE NODE
|
||||||
@ -825,37 +820,36 @@ class WAS_Image_Blending_Mode:
|
|||||||
img_b = tensor2pil(image_b)
|
img_b = tensor2pil(image_b)
|
||||||
|
|
||||||
# Apply blending
|
# Apply blending
|
||||||
match mode:
|
if mode == "color":
|
||||||
case "color":
|
out_image = pilgram.css.blending.color(img_a, img_b)
|
||||||
out_image = pilgram.css.blending.color(img_a, img_b)
|
elif mode == "color_burn":
|
||||||
case "color_burn":
|
out_image = pilgram.css.blending.color_burn(img_a, img_b)
|
||||||
out_image = pilgram.css.blending.color_burn(img_a, img_b)
|
elif mode == "color_dodge":
|
||||||
case "color_dodge":
|
out_image = pilgram.css.blending.color_dodge(img_a, img_b)
|
||||||
out_image = pilgram.css.blending.color_dodge(img_a, img_b)
|
elif mode == "darken":
|
||||||
case "darken":
|
out_image = pilgram.css.blending.darken(img_a, img_b)
|
||||||
out_image = pilgram.css.blending.darken(img_a, img_b)
|
elif mode == "difference":
|
||||||
case "difference":
|
out_image = pilgram.css.blending.difference(img_a, img_b)
|
||||||
out_image = pilgram.css.blending.difference(img_a, img_b)
|
elif mode == "exclusion":
|
||||||
case "exclusion":
|
out_image = pilgram.css.blending.exclusion(img_a, img_b)
|
||||||
out_image = pilgram.css.blending.exclusion(img_a, img_b)
|
elif mode == "hard_light":
|
||||||
case "hard_light":
|
out_image = pilgram.css.blending.hard_light(img_a, img_b)
|
||||||
out_image = pilgram.css.blending.hard_light(img_a, img_b)
|
elif mode == "hue":
|
||||||
case "hue":
|
out_image = pilgram.css.blending.hue(img_a, img_b)
|
||||||
out_image = pilgram.css.blending.hue(img_a, img_b)
|
elif mode == "lighten":
|
||||||
case "lighten":
|
out_image = pilgram.css.blending.lighten(img_a, img_b)
|
||||||
out_image = pilgram.css.blending.lighten(img_a, img_b)
|
elif mode == "multiply":
|
||||||
case "multiply":
|
out_image = pilgram.css.blending.multiply(img_a, img_b)
|
||||||
out_image = pilgram.css.blending.multiply(img_a, img_b)
|
elif mode == "add":
|
||||||
case "add":
|
out_image = pilgram.css.blending.normal(img_a, img_b)
|
||||||
out_image = pilgram.css.blending.normal(img_a, img_b)
|
elif mode == "overlay":
|
||||||
case "overlay":
|
out_image = pilgram.css.blending.overlay(img_a, img_b)
|
||||||
out_image = pilgram.css.blending.overlay(img_a, img_b)
|
elif mode == "screen":
|
||||||
case "screen":
|
out_image = pilgram.css.blending.screen(img_a, img_b)
|
||||||
out_image = pilgram.css.blending.screen(img_a, img_b)
|
elif mode == "soft_light":
|
||||||
case "soft_light":
|
out_image = pilgram.css.blending.soft_light(img_a, img_b)
|
||||||
out_image = pilgram.css.blending.soft_light(img_a, img_b)
|
else:
|
||||||
case _:
|
out_image = img_a
|
||||||
out_image = img_a
|
|
||||||
|
|
||||||
out_image = out_image.convert("RGB")
|
out_image = out_image.convert("RGB")
|
||||||
|
|
||||||
@ -938,13 +932,12 @@ class WAS_Image_Monitor_Distortion_Filter:
|
|||||||
WFilter = WAS_Filter_Class()
|
WFilter = WAS_Filter_Class()
|
||||||
|
|
||||||
# Apply image effect
|
# Apply image effect
|
||||||
match mode:
|
if mode == 'Digital Distortion':
|
||||||
case 'Digital Distortion':
|
image = WFilter.digital_distortion(image, amplitude, offset)
|
||||||
image = WFilter.digital_distortion(image, amplitude, offset)
|
elif mode == 'Signal Distortion':
|
||||||
case 'Signal Distortion':
|
image = WFilter.signal_distortion(image, amplitude)
|
||||||
image = WFilter.signal_distortion(image, amplitude)
|
elif mode == 'TV Distortion':
|
||||||
case 'TV Distortion':
|
image = WFilter.tv_vhs_distortion(image, amplitude)
|
||||||
image = WFilter.tv_vhs_distortion(image, amplitude)
|
|
||||||
|
|
||||||
return (pil2tensor(image), )
|
return (pil2tensor(image), )
|
||||||
|
|
||||||
@ -1021,13 +1014,12 @@ class WAS_Image_Analyze:
|
|||||||
WFilter = WAS_Filter_Class()
|
WFilter = WAS_Filter_Class()
|
||||||
|
|
||||||
# Analye Image
|
# Analye Image
|
||||||
match mode:
|
if mode == 'Black White Levels':
|
||||||
case 'Black White Levels':
|
image = WFilter.black_white_levels(image)
|
||||||
image = WFilter.black_white_levels(image)
|
elif mode == 'RGB Levels':
|
||||||
case 'RGB Levels':
|
image = WFilter.channel_frequency(image)
|
||||||
image = WFilter.channel_frequency(image)
|
|
||||||
|
|
||||||
return (pil2tensor(image), )
|
return (pil2tensor(image), )
|
||||||
|
|
||||||
|
|
||||||
# IMAGE GENERATE GRADIENT
|
# IMAGE GENERATE GRADIENT
|
||||||
@ -1995,13 +1987,14 @@ class WAS_Image_Rotate:
|
|||||||
rotation = int((rotation//90)*90)
|
rotation = int((rotation//90)*90)
|
||||||
|
|
||||||
# Set Sampler
|
# Set Sampler
|
||||||
match sampler:
|
if sampler == 'nearest':
|
||||||
case 'nearest':
|
sampler = Image.NEAREST
|
||||||
sampler = Image.NEAREST
|
elif sampler == 'bicubic':
|
||||||
case 'bicubic':
|
sampler = Image.BICUBIC
|
||||||
sampler = Image.BICUBIC
|
elif sampler == 'bilinear':
|
||||||
case 'bilinear':
|
sampler = Image.BILINEAR
|
||||||
sampler = Image.BILINEAR
|
else:
|
||||||
|
sampler = Image.NEAREST # default to nearest if none of the above
|
||||||
|
|
||||||
# Rotate Image
|
# Rotate Image
|
||||||
if mode == 'internal':
|
if mode == 'internal':
|
||||||
@ -2244,14 +2237,13 @@ class WAS_Image_Edge:
|
|||||||
image = tensor2pil(image)
|
image = tensor2pil(image)
|
||||||
|
|
||||||
# Detect edges
|
# Detect edges
|
||||||
match mode:
|
if mode == "normal":
|
||||||
case "normal":
|
image = image.filter(ImageFilter.FIND_EDGES)
|
||||||
image = image.filter(ImageFilter.FIND_EDGES)
|
elif mode == "laplacian":
|
||||||
case "laplacian":
|
kernel = (-1, -1, -1, -1, 8, -1, -1, -1, -1)
|
||||||
image = image.filter(ImageFilter.Kernel((3, 3), (-1, -1, -1, -1, 8,
|
image = image.filter(ImageFilter.Kernel((3, 3), kernel, scale=1, offset=0))
|
||||||
-1, -1, -1, -1), 1, 0))
|
else:
|
||||||
case _:
|
image = image
|
||||||
image = image
|
|
||||||
|
|
||||||
return (torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0), )
|
return (torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0), )
|
||||||
|
|
||||||
@ -3645,15 +3637,14 @@ class WAS_Random_Number:
|
|||||||
random.seed(seed)
|
random.seed(seed)
|
||||||
|
|
||||||
# Return random number
|
# Return random number
|
||||||
match number_type:
|
if number_type == 'integer':
|
||||||
case 'integer':
|
number = random.randint(minimum, maximum)
|
||||||
number = random.randint(minimum, maximum)
|
elif number_type == 'float':
|
||||||
case 'float':
|
number = random.uniform(minimum, maximum)
|
||||||
number = random.uniform(minimum, maximum)
|
elif number_type == 'bool':
|
||||||
case 'bool':
|
number = random.random()
|
||||||
number = random.random()
|
else:
|
||||||
case _:
|
return
|
||||||
return
|
|
||||||
|
|
||||||
# Return number
|
# Return number
|
||||||
return (number, )
|
return (number, )
|
||||||
@ -3682,13 +3673,14 @@ class WAS_Constant_Number:
|
|||||||
def return_constant_number(self, number_type, number):
|
def return_constant_number(self, number_type, number):
|
||||||
|
|
||||||
# Return number
|
# Return number
|
||||||
match number_type:
|
if number_type == 'integer':
|
||||||
case 'integer':
|
return (int(number), )
|
||||||
return (int(number), )
|
elif number_type == 'float':
|
||||||
case 'integer':
|
return (float(number), )
|
||||||
return (float(number), )
|
elif number_type == 'bool':
|
||||||
case 'bool':
|
return ((1 if int(number) > 0 else 0), )
|
||||||
return ((1 if int(number) > 0 else 0), )
|
else:
|
||||||
|
return
|
||||||
|
|
||||||
|
|
||||||
# NUMBER TO SEED
|
# NUMBER TO SEED
|
||||||
@ -3898,34 +3890,32 @@ class WAS_Number_Operation:
|
|||||||
|
|
||||||
def math_operations(self, number_a, number_b, operation="addition"):
|
def math_operations(self, number_a, number_b, operation="addition"):
|
||||||
|
|
||||||
# Return random number
|
if operation == 'addition':
|
||||||
match operation:
|
return ((number_a + number_b),)
|
||||||
case 'addition':
|
elif operation == 'subtraction':
|
||||||
return ((number_a + number_b), )
|
return ((number_a - number_b),)
|
||||||
case 'subtraction':
|
elif operation == 'division':
|
||||||
return ((number_a - number_b), )
|
return ((number_a / number_b),)
|
||||||
case 'division':
|
elif operation == 'floor division':
|
||||||
return ((number_a / number_b), )
|
return ((number_a // number_b),)
|
||||||
case 'floor division':
|
elif operation == 'multiplication':
|
||||||
return ((number_a // number_b), )
|
return ((number_a * number_b),)
|
||||||
case 'multiplication':
|
elif operation == 'exponentiation':
|
||||||
return ((number_a * number_b), )
|
return ((number_a ** number_b),)
|
||||||
case 'exponentiation':
|
elif operation == 'modulus':
|
||||||
return ((number_a ** number_b), )
|
return ((number_a % number_b),)
|
||||||
case 'modulus':
|
elif operation == 'greater-than':
|
||||||
return ((number_a % number_b), )
|
return (+(number_a > number_b),)
|
||||||
case 'greater-than':
|
elif operation == 'greater-than or equals':
|
||||||
return (+(number_a > number_b), )
|
return (+(number_a >= number_b),)
|
||||||
case 'greater-than or equals':
|
elif operation == 'less-than':
|
||||||
return (+(number_a >= number_b), )
|
return (+(number_a < number_b),)
|
||||||
case 'less-than':
|
elif operation == 'less-than or equals':
|
||||||
return (+(number_a < number_b), )
|
return (+(number_a <= number_b),)
|
||||||
case 'less-than or equals':
|
elif operation == 'equals':
|
||||||
return (+(number_a <= number_b), )
|
return (+(number_a == number_b),)
|
||||||
case 'equals':
|
elif operation == 'does not equal':
|
||||||
return (+(number_a == number_b), )
|
return (+(number_a != number_b),)
|
||||||
case 'does not equal':
|
|
||||||
return (+(number_a != number_b), )
|
|
||||||
|
|
||||||
|
|
||||||
#! MISC
|
#! MISC
|
||||||
|
|||||||
Loading…
Reference in New Issue
Block a user