apply lint

api/onnx_web/chain/blend_denoise_localstd.py

@@ -32,7 +32,10 @@ class BlendDenoiseLocalStdStage(BaseStage):
         logger.info("denoising source images")
 
         return StageResult.from_arrays(
-            [remove_noise(source, threshold=strength)[0] for source in sources.as_numpy()]
+            [
+                remove_noise(source, threshold=strength)[0]
+                for source in sources.as_numpy()
+            ]
         )
 
 
@@ -59,7 +62,9 @@ def replace_noise(region: np.ndarray, threshold: int, deviation: float, op = np.
     diff = np.abs(central_pixel - region_normal)
 
     # If the whole region is fairly consistent but the central pixel deviates significantly,
-    if diff > (region_deviation + threshold) and diff < (region_deviation + threshold * deviation):
+    if diff > (region_deviation + threshold) and diff < (
+        region_deviation + threshold * deviation
+    ):
         surrounding_pixels = region[region != central_pixel]
         surrounding_median = op(surrounding_pixels)
         # replace it with the median of surrounding pixels
@@ -69,7 +74,12 @@ def replace_noise(region: np.ndarray, threshold: int, deviation: float, op = np.
     return False
 
 
-def remove_noise(image: np.ndarray, threshold: int, deviation: float, region_size: Tuple[int, int] = (6, 6)):
+def remove_noise(
+    image: np.ndarray,
+    threshold: int,
+    deviation: float,
+    region_size: Tuple[int, int] = (6, 6),
+):
     # Create a copy of the original image to store the result
     result_image = np.copy(image)
     result_mask = np.zeros_like(image)

api/onnx_web/diffusers/patches/vae.py

@@ -5,9 +5,9 @@ import numpy as np
 import torch
 from diffusers import OnnxRuntimeModel
 from diffusers.pipelines.onnx_utils import ORT_TO_NP_TYPE
-from ..version_safe_diffusers import AutoencoderKLOutput, DecoderOutput
 
 from ...server import ServerContext
+from ..version_safe_diffusers import AutoencoderKLOutput, DecoderOutput
 
 logger = getLogger(__name__)
 

api/onnx_web/diffusers/version_safe_diffusers.py

@@ -37,8 +37,8 @@ else:
 
 
 if is_diffusers_0_24:
-    from diffusers.models.modeling_outputs import AutoencoderKLOutput
     from diffusers.models.autoencoders.vae import DecoderOutput
+    from diffusers.models.modeling_outputs import AutoencoderKLOutput
 else:
     from diffusers.models.autoencoder_kl import AutoencoderKLOutput
     from diffusers.models.vae import DecoderOutput