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-rw-r--r--scripts/outpainting_mk_2.py40
-rw-r--r--scripts/sd_upscale.py2
-rw-r--r--scripts/xy_grid.py10
3 files changed, 7 insertions, 45 deletions
diff --git a/scripts/outpainting_mk_2.py b/scripts/outpainting_mk_2.py
index 9719bb8f..11613ca3 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):
diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py
index b87a145b..2653e2d4 100644
--- a/scripts/sd_upscale.py
+++ b/scripts/sd_upscale.py
@@ -34,7 +34,7 @@ class Script(scripts.Script):
seed = p.seed
init_img = p.init_images[0]
- img = upscaler.upscale(init_img, init_img.width * 2, init_img.height * 2)
+ img = upscaler.scaler.upscale(init_img, 2, upscaler.data_path)
devices.torch_gc()
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index 24fa5a0a..146663b0 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -45,11 +45,8 @@ def apply_sampler(p, x, xs):
def apply_checkpoint(p, x, xs):
- applicable = [info for info in modules.sd_models.checkpoints_list.values() if x in info.title]
- assert len(applicable) > 0, f'Checkpoint {x} for found'
-
- info = applicable[0]
-
+ info = modules.sd_models.get_closet_checkpoint_match(x)
+ assert info is not None, f'Checkpoint for {x} not found'
modules.sd_models.reload_model_weights(shared.sd_model, info)
@@ -159,6 +156,9 @@ class Script(scripts.Script):
p.batch_size = 1
def process_axis(opt, vals):
+ if opt.label == 'Nothing':
+ return [0]
+
valslist = [x.strip() for x in vals.split(",")]
if opt.type == int: