attempt 2

1 files changed, 16 insertions, 12 deletions

diff --git a/modules/processing.py b/modules/processing.py
index 146e409a..e9108f11 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -621,12 +621,12 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Sampler": p.sampler_name,

         "CFG scale": p.cfg_scale,

         "Image CFG scale": getattr(p, 'image_cfg_scale', None),

-        "Seed": all_seeds[index],

+        "Seed": p.all_seeds[0] if use_main_prompt else all_seeds[index],

         "Face restoration": (opts.face_restoration_model if p.restore_faces else None),

         "Size": f"{p.width}x{p.height}",

         "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),

         "Model": (None if not opts.add_model_name_to_info else shared.sd_model.sd_checkpoint_info.name_for_extra),

-        "Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]),

+        "Variation seed": (None if p.subseed_strength == 0 else (p.all_subseeds[0] if use_main_prompt else all_subseeds[index])),

         "Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength),

         "Seed resize from": (None if p.seed_resize_from_w <= 0 or p.seed_resize_from_h <= 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),

         "Denoising strength": getattr(p, 'denoising_strength', None),

@@ -807,20 +807,24 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
             if p.scripts is not None:

                 p.scripts.postprocess_batch(p, x_samples_ddim, batch_number=n)

 

-            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,

-            )

+                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

+                p.prompts = batch_params.prompts

+                p.negative_prompts = batch_params.negative_prompts

+                p.seeds = batch_params.seeds

+                p.subseeds = batch_params.subseeds

 

             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)

+                return create_infotext(p, p.prompts, p.seeds, p.subseeds, use_main_prompt=use_main_prompt, index=index, all_negative_prompts=p.negative_prompts)

 

             for i, x_sample in enumerate(x_samples_ddim):

                 p.batch_index = i

@@ -910,7 +914,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
         p,

         images_list=output_images,

         seed=p.all_seeds[0],

-        info=infotext(),

+        info=infotexts[0],

         comments="".join(f"{comment}\n" for comment in comments),

         subseed=p.all_subseeds[0],

         index_of_first_image=index_of_first_image,