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ruff formatting

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reformatted due to ruff errors
This commit is contained in:
skunkworxdark 2023-12-06 08:10:22 +00:00
parent 3b4b4ba40a
commit cd15d8b7a9
2 changed files with 12 additions and 11 deletions
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3
invokeai/backend/tiles/tiles.py
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@ -14,6 +14,7 @@ def calc_overlap(tiles: list[Tile], num_tiles_x, num_tiles_y) -> list[Tile]:
num_tiles_x: the number of tiles on the x axis.
num_tiles_y: the number of tiles on the y axis.
"""
def get_tile_or_none(idx_y: int, idx_x: int) -> Union[Tile, None]:
if idx_y < 0 or idx_y > num_tiles_y or idx_x < 0 or idx_x > num_tiles_x:
return None
@ -405,4 +406,4 @@ def merge_tiles_with_seam_blending(
dst_image[overlap_coords_bottom : first_tile_in_row.coords.bottom, :] = row_image[row_overlap_size:, :]
else:
# no overlap just paste the row
dst_image[first_tile_in_row.coords.top:first_tile_in_row.coords.bottom, :] = row_image
dst_image[first_tile_in_row.coords.top : first_tile_in_row.coords.bottom, :] = row_image

20
invokeai/backend/tiles/utils.py
View File

@ -49,7 +49,7 @@ def paste(dst_image: np.ndarray, src_image: np.ndarray, box: TBLR, mask: Optiona
dst_image[box.top : box.bottom, box.left : box.right] = src_image * mask + dst_image_box * (1.0 - mask)
def seam_blend(ia1: np.ndarray, ia2: np.ndarray, blend_amount: int, x_seam: bool,) -> np.ndarray:
def seam_blend(ia1: np.ndarray, ia2: np.ndarray, blend_amount: int, x_seam: bool) -> np.ndarray:
"""Blend two overlapping tile sections using a seams to find a path.
It is assumed that input images will be RGB np arrays and are the same size.
@ -94,7 +94,7 @@ def seam_blend(ia1: np.ndarray, ia2: np.ndarray, blend_amount: int, x_seam: bool
# Calc the energy in the difference
energy = np.abs(np.gradient(ia, axis=0)) + np.abs(np.gradient(ia, axis=1))
#Find the starting position of the seam
# Find the starting position of the seam
res = np.copy(energy)
for y in range(1, max_y):
row = res[y, :]
@ -106,7 +106,7 @@ def seam_blend(ia1: np.ndarray, ia2: np.ndarray, blend_amount: int, x_seam: bool
lowest_energy_line = np.empty([max_y], dtype="uint16")
lowest_energy_line[max_y - 1] = np.argmin(res[max_y - 1, min_x : max_x - 1])
#Calc the path of the seam
# Calc the path of the seam
for ypos in range(max_y - 2, -1, -1):
lowest_pos = lowest_energy_line[ypos + 1]
lpos = lowest_pos - 1
@ -130,18 +130,18 @@ def seam_blend(ia1: np.ndarray, ia2: np.ndarray, blend_amount: int, x_seam: bool
mask = cv2.blur(mask, (blend_amount, blend_amount))
# for visual debugging
#from PIL import Image
#m_image = Image.fromarray((mask * 255.0).astype("uint8"))
# from PIL import Image
# m_image = Image.fromarray((mask * 255.0).astype("uint8"))
# copy ia2 over ia1 while applying the seam mask
mask = np.expand_dims(mask, -1)
blended_image = ia1 * mask + ia2 * (1.0 - mask)
# for visual debugging
#i1 = Image.fromarray(ia1.astype("uint8"))
#i2 = Image.fromarray(ia2.astype("uint8"))
#b_image = Image.fromarray(blended_image.astype("uint8"))
#print(f"{ia1.shape}, {ia2.shape}, {mask.shape}, {blended_image.shape}")
#print(f"{i1.size}, {i2.size}, {m_image.size}, {b_image.size}")
# i1 = Image.fromarray(ia1.astype("uint8"))
# i2 = Image.fromarray(ia2.astype("uint8"))
# b_image = Image.fromarray(blended_image.astype("uint8"))
# print(f"{ia1.shape}, {ia2.shape}, {mask.shape}, {blended_image.shape}")
# print(f"{i1.size}, {i2.size}, {m_image.size}, {b_image.size}")
return blended_image