From ca5a9e79dc28eeaa3a161427a82e34703bf15765 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Sat, 22 Oct 2022 22:06:54 +0300
Subject: [PATCH] fix for img2img color correction in a batch #3218

---
 modules/processing.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index 27c669b09..b1877b807 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -403,8 +403,6 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             if (len(prompts) == 0):
                 break
 
-            #uc = p.sd_model.get_learned_conditioning(len(prompts) * [p.negative_prompt])
-            #c = p.sd_model.get_learned_conditioning(prompts)
             with devices.autocast():
                 uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps)
                 c = prompt_parser.get_multicond_learned_conditioning(shared.sd_model, prompts, p.steps)
@@ -716,6 +714,10 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
             batch_images = np.expand_dims(imgs[0], axis=0).repeat(self.batch_size, axis=0)
             if self.overlay_images is not None:
                 self.overlay_images = self.overlay_images * self.batch_size
+
+            if self.color_corrections is not None and len(self.color_corrections) == 1:
+                self.color_corrections = self.color_corrections * self.batch_size
+
         elif len(imgs) <= self.batch_size:
             self.batch_size = len(imgs)
             batch_images = np.array(imgs)