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fix(nodes): fix trivial typing issues

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This commit is contained in:
psychedelicious 2023-05-05 11:38:17 +10:00
parent 20f6a597ab
commit 49db6f4fac
1 changed files with 16 additions and 13 deletions
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29
invokeai/backend/generator/inpaint.py
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@ -4,6 +4,7 @@ invokeai.backend.generator.inpaint descends from .generator
from __future__ import annotations
import math
from typing import Tuple, Union
import cv2
import numpy as np
@ -59,7 +60,7 @@ class Inpaint(Img2Img):
writeable=False,
)
def infill_patchmatch(self, im: Image.Image) -> Image:
def infill_patchmatch(self, im: Image.Image) -> Image.Image:
if im.mode != "RGBA":
return im
@ -75,18 +76,18 @@ class Inpaint(Img2Img):
return im_patched
def tile_fill_missing(
self, im: Image.Image, tile_size: int = 16, seed: int = None
) -> Image:
self, im: Image.Image, tile_size: int = 16, seed: Union[int, None] = None
) -> Image.Image:
# Only fill if there's an alpha layer
if im.mode != "RGBA":
return im
a = np.asarray(im, dtype=np.uint8)
tile_size = (tile_size, tile_size)
tile_size_tuple = (tile_size, tile_size)
# Get the image as tiles of a specified size
tiles = self.get_tile_images(a, *tile_size).copy()
tiles = self.get_tile_images(a, *tile_size_tuple).copy()
# Get the mask as tiles
tiles_mask = tiles[:, :, :, :, 3]
@ -127,7 +128,9 @@ class Inpaint(Img2Img):
return si
def mask_edge(self, mask: Image, edge_size: int, edge_blur: int) -> Image:
def mask_edge(
self, mask: Image.Image, edge_size: int, edge_blur: int
) -> Image.Image:
npimg = np.asarray(mask, dtype=np.uint8)
# Detect any partially transparent regions
@ -206,8 +209,8 @@ class Inpaint(Img2Img):
cfg_scale,
ddim_eta,
conditioning,
init_image: PIL.Image.Image | torch.FloatTensor,
mask_image: PIL.Image.Image | torch.FloatTensor,
init_image: Image.Image | torch.FloatTensor,
mask_image: Image.Image | torch.FloatTensor,
strength: float,
mask_blur_radius: int = 8,
# Seam settings - when 0, doesn't fill seam
@ -222,7 +225,7 @@ class Inpaint(Img2Img):
infill_method=None,
inpaint_width=None,
inpaint_height=None,
inpaint_fill: tuple(int) = (0x7F, 0x7F, 0x7F, 0xFF),
inpaint_fill: Tuple[int, int, int, int] = (0x7F, 0x7F, 0x7F, 0xFF),
attention_maps_callback=None,
**kwargs,
):
@ -239,7 +242,7 @@ class Inpaint(Img2Img):
self.inpaint_width = inpaint_width
self.inpaint_height = inpaint_height
if isinstance(init_image, PIL.Image.Image):
if isinstance(init_image, Image.Image):
self.pil_image = init_image.copy()
# Do infill
@ -250,8 +253,8 @@ class Inpaint(Img2Img):
self.pil_image.copy(), seed=self.seed, tile_size=tile_size
)
elif infill_method == "solid":
solid_bg = PIL.Image.new("RGBA", init_image.size, inpaint_fill)
init_filled = PIL.Image.alpha_composite(solid_bg, init_image)
solid_bg = Image.new("RGBA", init_image.size, inpaint_fill)
init_filled = Image.alpha_composite(solid_bg, init_image)
else:
raise ValueError(
f"Non-supported infill type {infill_method}", infill_method
@ -269,7 +272,7 @@ class Inpaint(Img2Img):
# Create init tensor
init_image = image_resized_to_grid_as_tensor(init_filled.convert("RGB"))
if isinstance(mask_image, PIL.Image.Image):
if isinstance(mask_image, Image.Image):
self.pil_mask = mask_image.copy()
debug_image(
mask_image,