Merge branch 'main' into feat/use-custom-vaes

invokeai/backend/args.py

@@ -490,7 +490,7 @@ class Args(object):
             "-z",
             type=int,
             default=6,
-            choices=range(0, 9),
+            choices=range(0, 10),
             dest="png_compression",
             help="level of PNG compression, from 0 (none) to 9 (maximum). Default is 6.",
         )
@@ -943,7 +943,6 @@ class Args(object):
             "--png_compression",
             "-z",
             type=int,
-            default=6,
             choices=range(0, 10),
             dest="png_compression",
             help="level of PNG compression, from 0 (none) to 9 (maximum). [6]",

invokeai/backend/generator/base.py

@@ -497,7 +497,8 @@ class Generator:
         matched_result.paste(init_image, (0, 0), mask=multiplied_blurred_init_mask)
         return matched_result
 
-    def sample_to_lowres_estimated_image(self, samples):
+    @staticmethod
+    def sample_to_lowres_estimated_image(samples):
         # origingally adapted from code by @erucipe and @keturn here:
         # https://discuss.huggingface.co/t/decoding-latents-to-rgb-without-upscaling/23204/7
 

invokeai/backend/generator/inpaint.py

@@ -159,6 +159,7 @@ class Inpaint(Img2Img):
         seam_size: int,
         seam_blur: int,
         prompt,
+        seed,
         sampler,
         steps,
         cfg_scale,
@@ -192,7 +193,7 @@ class Inpaint(Img2Img):
 
         seam_noise = self.get_noise(im.width, im.height)
 
-        result = make_image(seam_noise)
+        result = make_image(seam_noise, seed)
 
         return result
 
@@ -342,6 +343,7 @@ class Inpaint(Img2Img):
                     seam_size,
                     seam_blur,
                     prompt,
+                    seed,
                     sampler,
                     seam_steps,
                     cfg_scale,

invokeai/backend/model_management/convert_ckpt_to_diffusers.py

@@ -1086,9 +1086,10 @@ def load_pipeline_from_original_stable_diffusion_ckpt(
         dlogging.set_verbosity_error()
 
         checkpoint = (
-            load_file(checkpoint_path)
-            if Path(checkpoint_path).suffix == ".safetensors"
-            else torch.load(checkpoint_path)
+            torch.load(checkpoint_path)
+            if Path(checkpoint_path).suffix == ".ckpt"
+            else load_file(checkpoint_path)
+            
         )
         cache_dir = global_cache_dir("hub")
         pipeline_class = (

invokeai/backend/model_management/model_manager.py

@@ -730,9 +730,9 @@ v        Apply picklescanner to the indicated checkpoint and issue a warning
 
         # another round of heuristics to guess the correct config file.
         checkpoint = (
-            safetensors.torch.load_file(model_path)
-            if model_path.suffix == ".safetensors"
-            else torch.load(model_path)
+            torch.load(model_path)
+            if model_path.suffix == ".ckpt"
+            else safetensors.torch.load_file(model_path)
         )
 
         # additional probing needed if no config file provided

invokeai/backend/util/util.py

@@ -3,6 +3,9 @@ import math
 import multiprocessing as mp
 import os
 import re
+import io
+import base64
+
 from collections import abc
 from inspect import isfunction
 from pathlib import Path
@@ -364,3 +367,16 @@ def url_attachment_name(url: str) -> dict:
 def download_with_progress_bar(url: str, dest: Path) -> bool:
     result = download_with_resume(url, dest, access_token=None)
     return result is not None
+
+
+def image_to_dataURL(image: Image.Image, image_format: str = "PNG") -> str:
+    """
+    Converts an image into a base64 image dataURL.
+    """
+    buffered = io.BytesIO()
+    image.save(buffered, format=image_format)
+    mime_type = Image.MIME.get(image_format.upper(), "image/" + image_format.lower())
+    image_base64 = f"data:{mime_type};base64," + base64.b64encode(
+        buffered.getvalue()
+    ).decode("UTF-8")
+    return image_base64