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Merge branch 'Main' into feature/preview-latent

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Lt.Dr.Data 2023-05-22 16:38:21 +09:00
commit 261dc9c832
2 changed files with 4 additions and 2 deletions
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2
comfy/k_diffusion/sampling.py
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@ -620,6 +620,7 @@ def sample_dpmpp_2m_sde(model, x, sigmas, extra_args=None, callback=None, disabl
old_denoised = None old_denoised = None
h_last = None h_last = None
h = None
for i in trange(len(sigmas) - 1, disable=disable): for i in trange(len(sigmas) - 1, disable=disable):
denoised = model(x, sigmas[i] * s_in, **extra_args) denoised = model(x, sigmas[i] * s_in, **extra_args)
@ -628,7 +629,6 @@ def sample_dpmpp_2m_sde(model, x, sigmas, extra_args=None, callback=None, disabl
if sigmas[i + 1] == 0: if sigmas[i + 1] == 0:
# Denoising step # Denoising step
x = denoised x = denoised
h = None
else: else:
# DPM-Solver++(2M) SDE # DPM-Solver++(2M) SDE
t, s = -sigmas[i].log(), -sigmas[i + 1].log() t, s = -sigmas[i].log(), -sigmas[i + 1].log()

4
nodes.py
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@ -8,7 +8,7 @@ import traceback
import math import math
import time import time
from PIL import Image, ImageDraw from PIL import Image, ImageDraw, ImageOps
from PIL.PngImagePlugin import PngInfo from PIL.PngImagePlugin import PngInfo
import numpy as np import numpy as np
import safetensors.torch import safetensors.torch
@ -1187,6 +1187,7 @@ class LoadImage:
def load_image(self, image): def load_image(self, image):
image_path = folder_paths.get_annotated_filepath(image) image_path = folder_paths.get_annotated_filepath(image)
i = Image.open(image_path) i = Image.open(image_path)
i = ImageOps.exif_transpose(i)
image = i.convert("RGB") image = i.convert("RGB")
image = np.array(image).astype(np.float32) / 255.0 image = np.array(image).astype(np.float32) / 255.0
image = torch.from_numpy(image)[None,] image = torch.from_numpy(image)[None,]
@ -1230,6 +1231,7 @@ class LoadImageMask:
def load_image(self, image, channel): def load_image(self, image, channel):
image_path = folder_paths.get_annotated_filepath(image) image_path = folder_paths.get_annotated_filepath(image)
i = Image.open(image_path) i = Image.open(image_path)
i = ImageOps.exif_transpose(i)
if i.getbands() != ("R", "G", "B", "A"): if i.getbands() != ("R", "G", "B", "A"):
i = i.convert("RGBA") i = i.convert("RGBA")
mask = None mask = None