install GFPGAN inside SD repository in order to fix 'dark cast' issue #169

environment-mac.yaml

@@ -35,6 +35,7 @@ dependencies:
   - opencv==4.6.0
   - pudb==2022.1
   - pytorch-lightning==1.6.5
+  - realesrgan==0.2.5.0
   - scipy==1.9.1
   - streamlit==1.12.2
   - sympy==1.10.1
@@ -47,6 +48,7 @@ dependencies:
     - -e git+https://github.com/CompVis/taming-transformers.git@master#egg=taming-transformers
     - -e git+https://github.com/openai/CLIP.git@main#egg=clip
     - -e git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k_diffusion
+    - -e git+https://github.com/lstein/GFPGAN@fix-dark-cast-images#egg=gfpgan
     - -e .
 variables:
   PYTORCH_ENABLE_MPS_FALLBACK: 1

environment.yaml

@@ -1,4 +1,4 @@
-name: ldm
+name: sd-ldm
 channels:
   - pytorch
   - defaults
@@ -11,7 +11,7 @@ dependencies:
   - numpy=1.19.2
   - pip:
     - albumentations==0.4.3
-    - opencv-python==4.1.2.30
+    - opencv-python==4.5.5.64
     - pudb==2019.2
     - imageio==2.9.0
     - imageio-ffmpeg==0.4.2
@@ -28,4 +28,5 @@ dependencies:
     - -e git+https://github.com/openai/CLIP.git@main#egg=clip
     - -e git+https://github.com/CompVis/taming-transformers.git@master#egg=taming-transformers
     - -e git+https://github.com/lstein/k-diffusion.git@master#egg=k-diffusion
+    - -e git+https://github.com/lstein/GFPGAN@fix-dark-cast-images#egg=gfpgan
     - -e .

ldm/gfpgan/gfpgan_tools.py

@@ -8,10 +8,7 @@ from PIL import Image
 from scripts.dream import create_argv_parser
 
 arg_parser = create_argv_parser()
-opt = arg_parser.parse_args()
+opt        = arg_parser.parse_args()
-
-model_path = os.path.join(opt.gfpgan_dir, opt.gfpgan_model_path)
-gfpgan_model_exists = os.path.isfile(model_path)
 
 def run_gfpgan(image, strength, seed, upsampler_scale=4):
     print(f'>> GFPGAN - Restoring Faces for image seed:{seed}')
@@ -20,6 +17,9 @@ def run_gfpgan(image, strength, seed, upsampler_scale=4):
         warnings.filterwarnings('ignore', category=DeprecationWarning)
         warnings.filterwarnings('ignore', category=UserWarning)
         
+        model_path          = os.path.join(opt.gfpgan_dir, opt.gfpgan_model_path)
+        gfpgan_model_exists = os.path.isfile(model_path)
+
         try:
             if not gfpgan_model_exists:
                 raise Exception('GFPGAN model not found at path ' + model_path)
@@ -46,7 +46,10 @@ def run_gfpgan(image, strength, seed, upsampler_scale=4):
 
     if gfpgan is None:
         print(
-            f'>> GFPGAN not initialized. Their packages must be installed as siblings to the "stable-diffusion" folder, or set explicitly using the --gfpgan_dir option.'
+            f'>> WARNING: GFPGAN not initialized.'
+        )
+        print(
+            f'>> Download https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth to {model_path}, \nor change GFPGAN directory with --gfpgan_dir.'
         )
         return image
 

scripts/dream.py

@@ -183,7 +183,7 @@ def main_loop(t2i, outdir, prompt_as_dir, parser, infile):
         if len(opt.prompt) == 0:
             print('Try again with a prompt!')
             continue
-        if opt.init_img is not None and re.match('^-\d+$',opt.init_img): # retrieve previous value!
+        if opt.init_img is not None and re.match('^-\\d+$',opt.init_img): # retrieve previous value!
             try:
                 opt.init_img = last_results[int(opt.init_img)][0]
                 print(f'>> Reusing previous image {opt.init_img}')
@@ -478,7 +478,7 @@ def create_argv_parser():
     parser.add_argument(
         '--gfpgan_dir',
         type=str,
-        default='../GFPGAN',
+        default='./src/gfpgan',
         help='Indicates the directory containing the GFPGAN code.',
     )
     parser.add_argument(