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Merge branch 'comfyanonymous:master' into feature/blockweights

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Dr.Lt.Data 2023-05-02 22:57:45 +09:00 committed by GitHub
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3 changed files with 17 additions and 10 deletions
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2
.ci/nightly/update_windows/update_comfyui_and_python_dependencies.bat
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@ -1,3 +1,3 @@
..\python_embeded\python.exe .\update.py ..\ComfyUI\
..\python_embeded\python.exe -s -m pip install --upgrade --pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cu118 -r ../ComfyUI/requirements.txt pygit2
..\python_embeded\python.exe -s -m pip install --upgrade --pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cu121 -r ../ComfyUI/requirements.txt pygit2
pause

10
.github/workflows/windows_release_nightly_pytorch.yml vendored
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@ -19,21 +19,21 @@ jobs:
fetch-depth: 0
- uses: actions/setup-python@v4
with:
python-version: '3.10.9'
python-version: '3.11.3'
- shell: bash
run: |
cd ..
cp -r ComfyUI ComfyUI_copy
curl https://www.python.org/ftp/python/3.10.9/python-3.10.9-embed-amd64.zip -o python_embeded.zip
curl https://www.python.org/ftp/python/3.11.3/python-3.11.3-embed-amd64.zip -o python_embeded.zip
unzip python_embeded.zip -d python_embeded
cd python_embeded
echo 'import site' >> ./python310._pth
echo 'import site' >> ./python311._pth
curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
./python.exe get-pip.py
python -m pip wheel torch torchvision torchaudio --pre --extra-index-url https://download.pytorch.org/whl/nightly/cu118 -r ../ComfyUI/requirements.txt pygit2 -w ../temp_wheel_dir
python -m pip wheel torch torchvision torchaudio --pre --extra-index-url https://download.pytorch.org/whl/nightly/cu121 -r ../ComfyUI/requirements.txt pygit2 -w ../temp_wheel_dir
ls ../temp_wheel_dir
./python.exe -s -m pip install --pre ../temp_wheel_dir/*
sed -i '1i../ComfyUI' ./python310._pth
sed -i '1i../ComfyUI' ./python311._pth
cd ..

15
nodes.py
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@ -5,6 +5,7 @@ import sys
import json
import hashlib
import traceback
import math
from PIL import Image
from PIL.PngImagePlugin import PngInfo
@ -223,13 +224,13 @@ class VAEEncodeForInpaint:
@classmethod
def INPUT_TYPES(s):
return {"required": { "pixels": ("IMAGE", ), "vae": ("VAE", ), "mask": ("MASK", )}}
return {"required": { "pixels": ("IMAGE", ), "vae": ("VAE", ), "mask": ("MASK", ), "grow_mask_by": ("INT", {"default": 6, "min": 0, "max": 64, "step": 1}),}}
RETURN_TYPES = ("LATENT",)
FUNCTION = "encode"
CATEGORY = "latent/inpaint"
def encode(self, vae, pixels, mask):
def encode(self, vae, pixels, mask, grow_mask_by=6):
x = (pixels.shape[1] // 64) * 64
y = (pixels.shape[2] // 64) * 64
mask = torch.nn.functional.interpolate(mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1])), size=(pixels.shape[1], pixels.shape[2]), mode="bilinear")
@ -240,8 +241,14 @@ class VAEEncodeForInpaint:
mask = mask[:,:,:x,:y]
#grow mask by a few pixels to keep things seamless in latent space
kernel_tensor = torch.ones((1, 1, 6, 6))
mask_erosion = torch.clamp(torch.nn.functional.conv2d(mask.round(), kernel_tensor, padding=3), 0, 1)
if grow_mask_by == 0:
mask_erosion = mask
else:
kernel_tensor = torch.ones((1, 1, grow_mask_by, grow_mask_by))
padding = math.ceil((grow_mask_by - 1) / 2)
mask_erosion = torch.clamp(torch.nn.functional.conv2d(mask.round(), kernel_tensor, padding=padding), 0, 1)
m = (1.0 - mask.round()).squeeze(1)
for i in range(3):
pixels[:,:,:,i] -= 0.5