diff options
Diffstat (limited to 'scripts/outpainting_mk_2.py')
| -rw-r--r-- | scripts/outpainting_mk_2.py | 45 |
1 files changed, 5 insertions, 40 deletions
diff --git a/scripts/outpainting_mk_2.py b/scripts/outpainting_mk_2.py index 9719bb8f..a6468e09 100644 --- a/scripts/outpainting_mk_2.py +++ b/scripts/outpainting_mk_2.py @@ -11,46 +11,8 @@ from modules import images, processing, devices from modules.processing import Processed, process_images
from modules.shared import opts, cmd_opts, state
-# https://github.com/parlance-zz/g-diffuser-bot
-def expand(x, dir, amount, power=0.75):
- is_left = dir == 3
- is_right = dir == 1
- is_up = dir == 0
- is_down = dir == 2
-
- if is_left or is_right:
- noise = np.zeros((x.shape[0], amount, 3), dtype=float)
- indexes = np.random.random((x.shape[0], amount)) ** power * (1 - np.arange(amount) / amount)
- if is_right:
- indexes = 1 - indexes
- indexes = (indexes * (x.shape[1] - 1)).astype(int)
-
- for row in range(x.shape[0]):
- if is_left:
- noise[row] = x[row][indexes[row]]
- else:
- noise[row] = np.flip(x[row][indexes[row]], axis=0)
-
- x = np.concatenate([noise, x] if is_left else [x, noise], axis=1)
- return x
-
- if is_up or is_down:
- noise = np.zeros((amount, x.shape[1], 3), dtype=float)
- indexes = np.random.random((x.shape[1], amount)) ** power * (1 - np.arange(amount) / amount)
- if is_down:
- indexes = 1 - indexes
- indexes = (indexes * x.shape[0] - 1).astype(int)
-
- for row in range(x.shape[1]):
- if is_up:
- noise[:, row] = x[:, row][indexes[row]]
- else:
- noise[:, row] = np.flip(x[:, row][indexes[row]], axis=0)
-
- x = np.concatenate([noise, x] if is_up else [x, noise], axis=0)
- return x
-
+# this function is taken from https://github.com/parlance-zz/g-diffuser-bot
def get_matched_noise(_np_src_image, np_mask_rgb, noise_q=1, color_variation=0.05):
# helper fft routines that keep ortho normalization and auto-shift before and after fft
def _fft2(data):
@@ -123,8 +85,11 @@ def get_matched_noise(_np_src_image, np_mask_rgb, noise_q=1, color_variation=0.0 src_dist = np.absolute(src_fft)
src_phase = src_fft / src_dist
+ # create a generator with a static seed to make outpainting deterministic / only follow global seed
+ rng = np.random.default_rng(0)
+
noise_window = _get_gaussian_window(width, height, mode=1) # start with simple gaussian noise
- noise_rgb = np.random.random_sample((width, height, num_channels))
+ noise_rgb = rng.random((width, height, num_channels))
noise_grey = (np.sum(noise_rgb, axis=2) / 3.)
noise_rgb *= color_variation # the colorfulness of the starting noise is blended to greyscale with a parameter
for c in range(num_channels):
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