diff --git a/CHANGELOG.md b/CHANGELOG.md
index 6130890..1320cfc 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -10,6 +10,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - [Freezeable layers (encoder/decoder/etc.)](https://github.com/faceshiftlabs/DeepFaceLab/tree/feature/freezable-weights)
 - [GAN stability improvements](https://github.com/faceshiftlabs/DeepFaceLab/tree/feature/gan-updates)
 
+## [1.2.1] - 2020-03-20
+### Fixed
+- Fixes bug with `fs-aug` color mode.
+
 ## [1.2.0] - 2020-03-17
 ### Added
 - [Random color training option](doc/features/random-color/README.md)
diff --git a/core/imagelib/color_transfer.py b/core/imagelib/color_transfer.py
index 7c7a1aa..185dac4 100644
--- a/core/imagelib/color_transfer.py
+++ b/core/imagelib/color_transfer.py
@@ -1,7 +1,7 @@
 import cv2
 import numpy as np
 from numpy import linalg as npla
-from random import random, shuffle, choice
+import random
 from scipy.stats import special_ortho_group
 import scipy as sp
 
@@ -371,12 +371,12 @@ def color_transfer(ct_mode, img_src, img_trg):
 
 
 # imported from faceswap
-def color_augmentation(img):
+def color_augmentation(img, seed=None):
     """ Color adjust RGB image """
     face = img
     face = np.clip(face*255.0, 0, 255).astype(np.uint8)
-    face = random_clahe(face)
-    face = random_lab(face)
+    face = random_clahe(face, seed)
+    face = random_lab(face, seed)
     img[:, :, :3] = face
     return (face / 255.0).astype(np.float32)
 
@@ -400,13 +400,14 @@ def random_lab_rotation(image, seed=None):
     return image
 
 
-def random_lab(image):
+def random_lab(image, seed=None):
     """ Perform random color/lightness adjustment in L*a*b* colorspace """
+    random.seed(seed)
     amount_l = 30 / 100
     amount_ab = 8 / 100
-    randoms = [(random() * amount_l * 2) - amount_l,  # L adjust
-                (random() * amount_ab * 2) - amount_ab,  # A adjust
-                (random() * amount_ab * 2) - amount_ab]  # B adjust
+    randoms = [(random.random() * amount_l * 2) - amount_l,  # L adjust
+                (random.random() * amount_ab * 2) - amount_ab,  # A adjust
+                (random.random() * amount_ab * 2) - amount_ab]  # B adjust
     image = cv2.cvtColor(  # pylint:disable=no-member
     image, cv2.COLOR_BGR2LAB).astype("float32") / 255.0  # pylint:disable=no-member
 
@@ -419,15 +420,16 @@ def random_lab(image):
                         cv2.COLOR_LAB2BGR)  # pylint:disable=no-member
     return image
 
-def random_clahe(image):
+def random_clahe(image, seed=None):
     """ Randomly perform Contrast Limited Adaptive Histogram Equalization """
-    contrast_random = random()
+    random.seed(seed)
+    contrast_random = random.random()
     if contrast_random > 50 / 100:
         return image
 
     # base_contrast = image.shape[0] // 128
     base_contrast = 1 # testing because it breaks on small sizes
-    grid_base = random() * 4
+    grid_base = random.random() * 4
     contrast_adjustment = int(grid_base * (base_contrast / 2))
     grid_size = base_contrast + contrast_adjustment
 
diff --git a/samplelib/SampleProcessor.py b/samplelib/SampleProcessor.py
index 2faa182..4df44a3 100644
--- a/samplelib/SampleProcessor.py
+++ b/samplelib/SampleProcessor.py
@@ -207,7 +207,7 @@ class SampleProcessor(object):
                         # Apply random color transfer
                         if ct_mode is not None and ct_sample is not None or ct_mode == 'fs-aug':
                             if ct_mode == 'fs-aug':
-                                img = imagelib.color_augmentation(img)
+                                img = imagelib.color_augmentation(img, sample_rnd_seed)
                             else:
                                 if ct_sample_bgr is None:
                                     ct_sample_bgr = ct_sample.load_bgr()