Files
easydiffusion/ui/sd_internal/custom_sd.patch

47 lines
1.9 KiB
Diff

diff --git a/ldm/dream/conditioning.py b/ldm/dream/conditioning.py
index dfa1089..e4908ad 100644
--- a/ldm/dream/conditioning.py
+++ b/ldm/dream/conditioning.py
@@ -12,8 +12,8 @@ log_tokenization() print out colour-coded tokens and warn if trunca
import re
import torch
-def get_uc_and_c(prompt, model, log_tokens=False, skip_normalize=False):
- uc = model.get_learned_conditioning([''])
+def get_uc_and_c(prompt, model, log_tokens=False, skip_normalize=False, negative_prompt=''):
+ uc = model.get_learned_conditioning([negative_prompt])
# get weighted sub-prompts
weighted_subprompts = split_weighted_subprompts(
diff --git a/ldm/generate.py b/ldm/generate.py
index 8f67403..d88ce2d 100644
--- a/ldm/generate.py
+++ b/ldm/generate.py
@@ -205,6 +205,7 @@ class Generate:
init_mask = None,
fit = False,
strength = None,
+ init_img_is_path = True,
# these are specific to GFPGAN/ESRGAN
gfpgan_strength= 0,
save_original = False,
@@ -303,11 +304,15 @@ class Generate:
uc, c = get_uc_and_c(
prompt, model=self.model,
skip_normalize=skip_normalize,
- log_tokens=self.log_tokenization
+ log_tokens=self.log_tokenization,
+ negative_prompt=(args['negative_prompt'] if 'negative_prompt' in args else '')
)
- (init_image,mask_image) = self._make_images(init_img,init_mask, width, height, fit)
-
+ if init_img_is_path:
+ (init_image,mask_image) = self._make_images(init_img,init_mask, width, height, fit)
+ else:
+ (init_image,mask_image) = (init_img, init_mask)
+
if (init_image is not None) and (mask_image is not None):
generator = self._make_inpaint()
elif init_image is not None: