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fix(config): use new get_config across the app, use correct settings

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psychedelicious
2024-03-11 23:01:48 +11:00
parent 7b1f9409bc
commit 897fe497dc
18 changed files with 36 additions and 32 deletions
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4
invokeai/backend/image_util/depth_anything/__init__.py
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@ -9,14 +9,14 @@ from einops import repeat
from PIL import Image
from torchvision.transforms import Compose
from invokeai.app.services.config.config_default import InvokeAIAppConfig
from invokeai.app.services.config.config_default import get_config
from invokeai.backend.image_util.depth_anything.model.dpt import DPT_DINOv2
from invokeai.backend.image_util.depth_anything.utilities.util import NormalizeImage, PrepareForNet, Resize
from invokeai.backend.util.devices import choose_torch_device
from invokeai.backend.util.logging import InvokeAILogger
from invokeai.backend.util.util import download_with_progress_bar
config = InvokeAIAppConfig.get_config()
config = get_config()
logger = InvokeAILogger.get_logger(config=config)
DEPTH_ANYTHING_MODELS = {

4
invokeai/backend/image_util/dw_openpose/wholebody.py
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@ -6,7 +6,7 @@ import pathlib
import numpy as np
import onnxruntime as ort
from invokeai.app.services.config.config_default import InvokeAIAppConfig
from invokeai.app.services.config.config_default import get_config
from invokeai.backend.util.devices import choose_torch_device
from invokeai.backend.util.util import download_with_progress_bar
@ -24,7 +24,7 @@ DWPOSE_MODELS = {
},
}
config = InvokeAIAppConfig.get_config()
config = get_config
class Wholebody:

6
invokeai/backend/image_util/lama.py
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@ -6,9 +6,11 @@ import torch
from PIL import Image
import invokeai.backend.util.logging as logger
from invokeai.app.services.config import get_invokeai_config
from invokeai.app.services.config.config_default import get_config
from invokeai.backend.util.devices import choose_torch_device
config = get_config()
def norm_img(np_img):
if len(np_img.shape) == 2:
@ -29,7 +31,7 @@ def load_jit_model(url_or_path, device):
class LaMA:
def __call__(self, input_image: Image.Image, *args: Any, **kwds: Any) -> Any:
device = choose_torch_device()
model_location = get_invokeai_config().models_path / "core/misc/lama/lama.pt"
model_location = get_config().models_path / "core/misc/lama/lama.pt"
model = load_jit_model(model_location, device)
image = np.asarray(input_image.convert("RGB"))

4
invokeai/backend/image_util/patchmatch.py
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@ -8,9 +8,9 @@ be suppressed or deferred
import numpy as np
import invokeai.backend.util.logging as logger
from invokeai.app.services.config import InvokeAIAppConfig
from invokeai.app.services.config.config_default import get_config
config = InvokeAIAppConfig.get_config()
config = get_config()
class PatchMatch:

4
invokeai/backend/image_util/txt2mask.py
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@ -33,11 +33,11 @@ from PIL import Image, ImageOps
from transformers import AutoProcessor, CLIPSegForImageSegmentation
import invokeai.backend.util.logging as logger
from invokeai.app.services.config import InvokeAIAppConfig
from invokeai.app.services.config.config_default import get_config
CLIPSEG_MODEL = "CIDAS/clipseg-rd64-refined"
CLIPSEG_SIZE = 352
config = InvokeAIAppConfig.get_config()
config = get_config()
class SegmentedGrayscale(object):