Merge branch 'master' into hypernetwork-training

1 files changed, 8 insertions, 4 deletions

diff --git a/modules/extras.py b/modules/extras.py
index 1d9e64e5..41e8612c 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -29,7 +29,7 @@ def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_v
     if extras_mode == 1:

         #convert file to pillow image

         for img in image_folder:

-            image = Image.fromarray(np.array(Image.open(img)))

+            image = Image.open(img)

             imageArr.append(image)

             imageNameArr.append(os.path.splitext(img.orig_name)[0])

     else:

@@ -98,6 +98,10 @@ def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_v
                           no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo,

                           forced_filename=image_name if opts.use_original_name_batch else None)

 

+        if opts.enable_pnginfo:

+            image.info = existing_pnginfo

+            image.info["extras"] = info

+

         outputs.append(image)

 

     devices.torch_gc()

@@ -169,9 +173,9 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int
 

     print(f"Loading {secondary_model_info.filename}...")

     secondary_model = torch.load(secondary_model_info.filename, map_location='cpu')

-   

-    theta_0 = primary_model['state_dict']

-    theta_1 = secondary_model['state_dict']

+

+    theta_0 = sd_models.get_state_dict_from_checkpoint(primary_model)

+    theta_1 = sd_models.get_state_dict_from_checkpoint(secondary_model)

 

     theta_funcs = {

         "Weighted Sum": weighted_sum,