diff options
Diffstat (limited to 'scripts')
| -rw-r--r-- | scripts/img2imgalt.py | 3 | ||||
| -rw-r--r-- | scripts/outpainting_mk_2.py | 5 | ||||
| -rw-r--r-- | scripts/xy_grid.py | 8 |
3 files changed, 9 insertions, 7 deletions
diff --git a/scripts/img2imgalt.py b/scripts/img2imgalt.py index 0ef137f7..f9894cb0 100644 --- a/scripts/img2imgalt.py +++ b/scripts/img2imgalt.py @@ -8,7 +8,6 @@ import gradio as gr from modules import processing, shared, sd_samplers, prompt_parser
from modules.processing import Processed
-from modules.sd_samplers import samplers
from modules.shared import opts, cmd_opts, state
import torch
@@ -159,7 +158,7 @@ class Script(scripts.Script): combined_noise = ((1 - randomness) * rec_noise + randomness * rand_noise) / ((randomness**2 + (1-randomness)**2) ** 0.5)
- sampler = samplers[p.sampler_index].constructor(p.sd_model)
+ sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, p.sampler_index, p.sd_model)
sigmas = sampler.model_wrap.get_sigmas(p.steps)
diff --git a/scripts/outpainting_mk_2.py b/scripts/outpainting_mk_2.py index 11613ca3..a6468e09 100644 --- a/scripts/outpainting_mk_2.py +++ b/scripts/outpainting_mk_2.py @@ -85,8 +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):
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py index 1237e754..210c7b6e 100644 --- a/scripts/xy_grid.py +++ b/scripts/xy_grid.py @@ -1,8 +1,9 @@ from collections import namedtuple
from copy import copy
-from itertools import permutations
+from itertools import permutations, chain
import random
-
+import csv
+from io import StringIO
from PIL import Image
import numpy as np
@@ -168,7 +169,6 @@ re_range_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d re_range_count = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\[(\d+)\s*\])?\s*")
re_range_count_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d*)?)(?:\s*\[(\d+(?:.\d*)?)\s*\])?\s*")
-
class Script(scripts.Script):
def title(self):
return "X/Y plot"
@@ -197,7 +197,7 @@ class Script(scripts.Script): if opt.label == 'Nothing':
return [0]
- valslist = [x.strip() for x in vals.split(",")]
+ valslist = list(map(str.strip,chain.from_iterable(csv.reader(StringIO(vals)))))
if opt.type == int:
valslist_ext = []
|