diff --git a/src/python/enfugue/diffusion/invocation/layers.py b/src/python/enfugue/diffusion/invocation/layers.py
index 43f97662..63a71fef 100644
--- a/src/python/enfugue/diffusion/invocation/layers.py
+++ b/src/python/enfugue/diffusion/invocation/layers.py
@@ -1253,7 +1253,7 @@ def pasted_image_callback(images: List[Image]) -> None:
             from enfugue.diffusion.util import interpolate_frames, reflect_frames
             with pipeline.interpolator.film() as interpolate:
                 if self.interpolate_frames:
-                    if task_callback:
+                    if task_callback is not None:
                         task_callback("Interpolating")
                     result["frames"] = [
                         frame for frame in interpolate_frames(
@@ -1266,7 +1266,7 @@ def pasted_image_callback(images: List[Image]) -> None:
                 else:
                     result["frames"] = result["images"]
                 if self.reflect:
-                    if task_callback:
+                    if task_callback is not None:
                         task_callback("Reflecting")
                     result["frames"] = [
                         frame for frame in reflect_frames(
diff --git a/src/python/enfugue/diffusion/pipeline.py b/src/python/enfugue/diffusion/pipeline.py
index 5903d306..07948e76 100644
--- a/src/python/enfugue/diffusion/pipeline.py
+++ b/src/python/enfugue/diffusion/pipeline.py
@@ -289,7 +289,7 @@ def open_image(cls, path: str) -> List[PIL.Image.Image]:
             return [PIL.Image.open(path)]
 
     @classmethod
-    def get_config_from_url(cls, cache_dir: dir, url: dir) -> Dict[str, Any]:
+    def get_config_from_url(cls, cache_dir: str, url: str) -> Dict[str, Any]:
         """
         Downloads remote config and loads it
         """
@@ -541,7 +541,6 @@ def from_ckpt(
                 cache_dir,
                 "https://huggingface.co/segmind/Segmind-Vega/raw/main/unet/config.json?filename=segmind-vega-unet-config.json"
             )
-            logger.critical(unet_config)
         else:
             unet_config = create_unet_diffusers_config(original_config, image_size=image_size)
 
@@ -624,7 +623,7 @@ def from_ckpt(
                     check_size=False
                 )
                 task_callback("Loading VAE")
-                VAE_Config = AutoencoderKL._dict_from_json_file(vae_config_path)
+                vae_config = AutoencoderKL._dict_from_json_file(vae_config_path)
                 if "scaling_factor" in vae_config:
                     vae_config["scaling_factor"] = cls.get_vae_scale_factor(vae_config["scaling_factor"])
                 vae = AutoencoderKL.from_config(vae_config)
@@ -3485,9 +3484,9 @@ def __call__(
 
         # Open images if they're files
         if isinstance(image, str):
-            image = self.open_image(image)
+            image = self.open_image(image) # type: ignore[unreachable]
         if isinstance(mask, str):
-            mask = self.open_image(mask)
+            mask = self.open_image(mask) # type: ignore[unreachable]
 
         if image is not None and type(image) is not torch.Tensor:
             if isinstance(image, list):