diff options
Diffstat (limited to 'modules/processing.py')
| -rw-r--r-- | modules/processing.py | 62 |
1 files changed, 27 insertions, 35 deletions
diff --git a/modules/processing.py b/modules/processing.py index 6dc178e1..146e409a 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -600,8 +600,12 @@ def program_version(): return res
-def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0, use_main_prompt=False):
- index = position_in_batch + iteration * p.batch_size
+def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0, use_main_prompt=False, index=None, all_negative_prompts=None):
+ if index is None:
+ index = position_in_batch + iteration * p.batch_size
+
+ if all_negative_prompts is None:
+ all_negative_prompts = p.all_negative_prompts
clip_skip = getattr(p, 'clip_skip', opts.CLIP_stop_at_last_layers)
enable_hr = getattr(p, 'enable_hr', False)
@@ -642,7 +646,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter generation_params_text = ", ".join([k if k == v else f'{k}: {generation_parameters_copypaste.quote(v)}' for k, v in generation_params.items() if v is not None])
prompt_text = p.prompt if use_main_prompt else all_prompts[index]
- negative_prompt_text = f"\nNegative prompt: {p.all_negative_prompts[index]}" if p.all_negative_prompts[index] else ""
+ negative_prompt_text = f"\nNegative prompt: {all_negative_prompts[index]}" if all_negative_prompts[index] else ""
return f"{prompt_text}{negative_prompt_text}\n{generation_params_text}".strip()
@@ -716,29 +720,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: else:
p.all_subseeds = [int(subseed) + x for x in range(len(p.all_prompts))]
- def infotext(iteration=0, position_in_batch=0, use_main_prompt=False):
- all_prompts = p.all_prompts[:]
- all_negative_prompts = p.all_negative_prompts[:]
- all_seeds = p.all_seeds[:]
- all_subseeds = p.all_subseeds[:]
-
- # apply changes to generation data
- all_prompts[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.prompts
- all_negative_prompts[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.negative_prompts
- all_seeds[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.seeds
- all_subseeds[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.subseeds
-
- # update p.all_negative_prompts in case extensions changed the size of the batch
- # create_infotext below uses it
- old_negative_prompts = p.all_negative_prompts
- p.all_negative_prompts = all_negative_prompts
-
- try:
- return create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration, position_in_batch, use_main_prompt)
- finally:
- # restore p.all_negative_prompts in case extensions changed the size of the batch
- p.all_negative_prompts = old_negative_prompts
-
if os.path.exists(cmd_opts.embeddings_dir) and not p.do_not_reload_embeddings:
model_hijack.embedding_db.load_textual_inversion_embeddings()
@@ -826,9 +807,20 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if p.scripts is not None:
p.scripts.postprocess_batch(p, x_samples_ddim, batch_number=n)
- postprocess_batch_list_args = scripts.PostprocessBatchListArgs(list(x_samples_ddim))
- p.scripts.postprocess_batch_list(p, postprocess_batch_list_args, batch_number=n)
- x_samples_ddim = postprocess_batch_list_args.images
+ batch_params = scripts.PostprocessBatchListArgs(
+ list(x_samples_ddim),
+ p.all_prompts[n * p.batch_size:(n + 1) * p.batch_size],
+ p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size],
+ p.seeds,
+ p.subseeds,
+ )
+
+ if p.scripts is not None:
+ p.scripts.postprocess_batch_list(p, batch_params, batch_number=n)
+ x_samples_ddim = batch_params.images
+
+ def infotext(index=0, use_main_prompt=False):
+ return create_infotext(p, batch_params.prompts, batch_params.seeds, batch_params.subseeds, use_main_prompt=use_main_prompt, index=index, all_negative_prompts=batch_params.negative_prompts)
for i, x_sample in enumerate(x_samples_ddim):
p.batch_index = i
@@ -838,7 +830,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if p.restore_faces:
if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration:
- images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration")
+ images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-before-face-restoration")
devices.torch_gc()
@@ -855,15 +847,15 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if p.color_corrections is not None and i < len(p.color_corrections):
if opts.save and not p.do_not_save_samples and opts.save_images_before_color_correction:
image_without_cc = apply_overlay(image, p.paste_to, i, p.overlay_images)
- images.save_image(image_without_cc, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-color-correction")
+ images.save_image(image_without_cc, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-before-color-correction")
image = apply_color_correction(p.color_corrections[i], image)
image = apply_overlay(image, p.paste_to, i, p.overlay_images)
if opts.samples_save and not p.do_not_save_samples:
- images.save_image(image, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p)
+ images.save_image(image, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p)
- text = infotext(n, i)
+ text = infotext(i)
infotexts.append(text)
if opts.enable_pnginfo:
image.info["parameters"] = text
@@ -874,10 +866,10 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: image_mask_composite = Image.composite(image.convert('RGBA').convert('RGBa'), Image.new('RGBa', image.size), images.resize_image(2, p.mask_for_overlay, image.width, image.height).convert('L')).convert('RGBA')
if opts.save_mask:
- images.save_image(image_mask, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask")
+ images.save_image(image_mask, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-mask")
if opts.save_mask_composite:
- images.save_image(image_mask_composite, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask-composite")
+ images.save_image(image_mask_composite, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-mask-composite")
if opts.return_mask:
output_images.append(image_mask)
|