color correction option for all img2img modes #363

modules/img2img.py

@@ -1,5 +1,4 @@
 import math
-import cv2
 import numpy as np
 from PIL import Image, ImageOps, ImageChops
 
@@ -76,18 +75,7 @@ def img2img(prompt: str, negative_prompt: str, prompt_style: str, init_img, init
 
         state.job_count = n_iter
 
-        do_color_correction = False
-        try:
-            from skimage import exposure
-            do_color_correction = True
-        except:
-            print("Install scikit-image to perform color correction on loopback")
-
-
         for i in range(n_iter):
-            if do_color_correction and i == 0:
-                correction_target = cv2.cvtColor(np.asarray(init_img.copy()), cv2.COLOR_RGB2LAB)
-
             p.n_iter = 1
             p.batch_size = 1
             p.do_not_save_grid = True
@@ -101,16 +89,6 @@ def img2img(prompt: str, negative_prompt: str, prompt_style: str, init_img, init
             
             init_img = processed.images[0]
 
-            if do_color_correction and correction_target is not None:
-                init_img = Image.fromarray(cv2.cvtColor(exposure.match_histograms(
-                    cv2.cvtColor(
-                        np.asarray(init_img),
-                        cv2.COLOR_RGB2LAB
-                    ),
-                    correction_target,
-                    channel_axis=2
-                ), cv2.COLOR_LAB2RGB).astype("uint8"))
-
             p.init_images = [init_img]
             p.seed = processed.seed + 1
             p.denoising_strength = min(max(p.denoising_strength * denoising_strength_change_factor, 0.1), 1)

modules/processing.py

@@ -8,6 +8,8 @@ import torch
 import numpy as np
 from PIL import Image, ImageFilter, ImageOps
 import random
+import cv2
+from skimage import exposure
 
 import modules.sd_hijack
 from modules import devices
@@ -19,11 +21,30 @@ import modules.face_restoration
 import modules.images as images
 import modules.styles
 
+
 # some of those options should not be changed at all because they would break the model, so I removed them from options.
 opt_C = 4
 opt_f = 8
 
 
+def setup_color_correction(image):
+    correction_target = cv2.cvtColor(np.asarray(image.copy()), cv2.COLOR_RGB2LAB)
+    return correction_target
+
+
+def apply_color_correction(correction, image):
+    image = Image.fromarray(cv2.cvtColor(exposure.match_histograms(
+        cv2.cvtColor(
+            np.asarray(image),
+            cv2.COLOR_RGB2LAB
+        ),
+        correction,
+        channel_axis=2
+    ), cv2.COLOR_LAB2RGB).astype("uint8"))
+
+    return image
+
+
 class StableDiffusionProcessing:
     def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt="", prompt_style="None", seed=-1, subseed=-1, subseed_strength=0, seed_resize_from_h=-1, seed_resize_from_w=-1, sampler_index=0, batch_size=1, n_iter=1, steps=50, cfg_scale=7.0, width=512, height=512, restore_faces=False, tiling=False, do_not_save_samples=False, do_not_save_grid=False, extra_generation_params=None, overlay_images=None, negative_prompt=None):
         self.sd_model = sd_model
@@ -52,6 +73,7 @@ class StableDiffusionProcessing:
         self.extra_generation_params: dict = extra_generation_params
         self.overlay_images = overlay_images
         self.paste_to = None
+        self.color_corrections = None
 
     def init(self, seed):
         pass
@@ -265,6 +287,8 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
 
                 image = Image.fromarray(x_sample)
 
+                if p.color_corrections is not None and i < len(p.color_corrections):
+                    image = apply_color_correction(p.color_corrections[i], image)
 
                 if p.overlay_images is not None and i < len(p.overlay_images):
                     overlay = p.overlay_images[i]
@@ -420,6 +444,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
 
         latent_mask = self.latent_mask if self.latent_mask is not None else self.image_mask
 
+        self.color_corrections = []
         imgs = []
         for img in self.init_images:
             image = img.convert("RGB")
@@ -441,6 +466,9 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
                 if self.inpainting_fill != 1:
                     image = fill(image, latent_mask)
 
+            if opts.img2img_color_correction:
+                self.color_corrections.append(setup_color_correction(image))
+
             image = np.array(image).astype(np.float32) / 255.0
             image = np.moveaxis(image, 2, 0)
 

modules/shared.py

@@ -122,6 +122,7 @@ class Options:
         "export_for_4chan": OptionInfo(True, "If PNG image is larger than 4MB or any dimension is larger than 4000, downscale and save copy as JPG"),
         "enable_pnginfo": OptionInfo(True, "Save text information about generation parameters as chunks to png files"),
         "add_model_hash_to_info": OptionInfo(False, "Add model hash to generation information"),
+        "img2img_color_correction": OptionInfo(True, "Apply color correction to img2img results to match original colors."),
         "font": OptionInfo("", "Font for image grids that have text"),
         "enable_emphasis": OptionInfo(True, "Use (text) to make model pay more attention to text text and [text] to make it pay less attention"),
         "save_txt": OptionInfo(False, "Create a text file next to every image with generation parameters."),