aboutsummaryrefslogtreecommitdiff
path: root/modules/processing.py
diff options
context:
space:
mode:
Diffstat (limited to 'modules/processing.py')
-rw-r--r--modules/processing.py35
1 files changed, 22 insertions, 13 deletions
diff --git a/modules/processing.py b/modules/processing.py
index ff1ec4c9..372489f7 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -104,6 +104,12 @@ class StableDiffusionProcessing():
self.seed_resize_from_h = 0
self.seed_resize_from_w = 0
+ self.scripts = None
+ self.script_args = None
+ self.all_prompts = None
+ self.all_seeds = None
+ self.all_subseeds = None
+
def init(self, all_prompts, all_seeds, all_subseeds):
pass
@@ -350,32 +356,35 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
shared.prompt_styles.apply_styles(p)
if type(p.prompt) == list:
- all_prompts = p.prompt
+ p.all_prompts = p.prompt
else:
- all_prompts = p.batch_size * p.n_iter * [p.prompt]
+ p.all_prompts = p.batch_size * p.n_iter * [p.prompt]
if type(seed) == list:
- all_seeds = seed
+ p.all_seeds = seed
else:
- all_seeds = [int(seed) + (x if p.subseed_strength == 0 else 0) for x in range(len(all_prompts))]
+ p.all_seeds = [int(seed) + (x if p.subseed_strength == 0 else 0) for x in range(len(p.all_prompts))]
if type(subseed) == list:
- all_subseeds = subseed
+ p.all_subseeds = subseed
else:
- all_subseeds = [int(subseed) + x for x in range(len(all_prompts))]
+ p.all_subseeds = [int(subseed) + x for x in range(len(p.all_prompts))]
def infotext(iteration=0, position_in_batch=0):
- return create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration, position_in_batch)
+ return create_infotext(p, p.all_prompts, p.all_seeds, p.all_subseeds, comments, iteration, position_in_batch)
if os.path.exists(cmd_opts.embeddings_dir) and not p.do_not_reload_embeddings:
model_hijack.embedding_db.load_textual_inversion_embeddings()
+ if p.scripts is not None:
+ p.scripts.run_alwayson_scripts(p)
+
infotexts = []
output_images = []
with torch.no_grad(), p.sd_model.ema_scope():
with devices.autocast():
- p.init(all_prompts, all_seeds, all_subseeds)
+ p.init(p.all_prompts, p.all_seeds, p.all_subseeds)
if state.job_count == -1:
state.job_count = p.n_iter
@@ -387,9 +396,9 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
if state.interrupted:
break
- prompts = all_prompts[n * p.batch_size:(n + 1) * p.batch_size]
- seeds = all_seeds[n * p.batch_size:(n + 1) * p.batch_size]
- subseeds = all_subseeds[n * p.batch_size:(n + 1) * p.batch_size]
+ prompts = p.all_prompts[n * p.batch_size:(n + 1) * p.batch_size]
+ seeds = p.all_seeds[n * p.batch_size:(n + 1) * p.batch_size]
+ subseeds = p.all_subseeds[n * p.batch_size:(n + 1) * p.batch_size]
if (len(prompts) == 0):
break
@@ -490,10 +499,10 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
index_of_first_image = 1
if opts.grid_save:
- images.save_image(grid, p.outpath_grids, "grid", all_seeds[0], all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True)
+ images.save_image(grid, p.outpath_grids, "grid", p.all_seeds[0], p.all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True)
devices.torch_gc()
- return Processed(p, output_images, all_seeds[0], infotext() + "".join(["\n\n" + x for x in comments]), subseed=all_subseeds[0], all_prompts=all_prompts, all_seeds=all_seeds, all_subseeds=all_subseeds, index_of_first_image=index_of_first_image, infotexts=infotexts)
+ return Processed(p, output_images, p.all_seeds[0], infotext() + "".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], all_prompts=p.all_prompts, all_seeds=p.all_seeds, all_subseeds=p.all_subseeds, index_of_first_image=index_of_first_image, infotexts=infotexts)
class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):