add postprocess_batch_list callback

modules/processing.py

@@ -717,7 +717,25 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
         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):
-        return create_infotext(p, p.all_prompts, p.all_seeds, p.all_subseeds, comments, iteration, position_in_batch, use_main_prompt)
+        all_prompts = p.all_prompts[:]
+        all_seeds = p.all_seeds[:]
+        all_subseeds = p.all_subseeds[:]
+
+        # apply changes to generation data
+        all_prompts[n * p.batch_size:(n + 1) * p.batch_size] = p.prompts
+        all_seeds[n * p.batch_size:(n + 1) * p.batch_size] = p.seeds
+        all_subseeds[n * p.batch_size:(n + 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[n * p.batch_size:(n + 1) * p.batch_size]
+        p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size] = p.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[n * p.batch_size:n * p.batch_size + len(p.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()
@@ -806,6 +824,10 @@ 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
+
             for i, x_sample in enumerate(x_samples_ddim):
                 p.batch_index = i
 

modules/scripts.py

@@ -16,6 +16,11 @@ class PostprocessImageArgs:
         self.image = image
 
 
+class PostprocessBatchListArgs:
+    def __init__(self, images):
+        self.images = images
+
+
 class Script:
     name = None
     """script's internal name derived from title"""
@@ -156,6 +161,25 @@ class Script:
 
         pass
 
+    def postprocess_batch_list(self, p, pp: PostprocessBatchListArgs, *args, **kwargs):
+        """
+        Same as postprocess_batch(), but receives batch images as a list of 3D tensors instead of a 4D tensor.
+        This is useful when you want to update the entire batch instead of individual images.
+
+        You can modify the postprocessing object (pp) to update the images in the batch, remove images, add images, etc.
+        If the number of images is different from the batch size when returning,
+        then the script has the responsibility to also update the following attributes in the processing object (p):
+          - p.prompts
+          - p.negative_prompts
+          - p.seeds
+          - p.subseeds
+
+        **kwargs will have same items as process_batch, and also:
+          - batch_number - index of current batch, from 0 to number of batches-1
+        """
+
+        pass
+
     def postprocess_image(self, p, pp: PostprocessImageArgs, *args):
         """
         Called for every image after it has been generated.
@@ -536,6 +560,14 @@ class ScriptRunner:
             except Exception:
                 errors.report(f"Error running postprocess_batch: {script.filename}", exc_info=True)
 
+    def postprocess_batch_list(self, p, pp: PostprocessBatchListArgs, **kwargs):
+        for script in self.alwayson_scripts:
+            try:
+                script_args = p.script_args[script.args_from:script.args_to]
+                script.postprocess_batch_list(p, pp, *script_args, **kwargs)
+            except Exception:
+                errors.report(f"Error running postprocess_batch_list: {script.filename}", exc_info=True)
+
     def postprocess_image(self, p, pp: PostprocessImageArgs):
         for script in self.alwayson_scripts:
             try: