lint

Signed-off-by: vladmandic <mandic00@live.com>

html/reference-cloud.json

@@ -13,4 +13,4 @@
     "tags": "cloud",
     "skip": true
   }
-}
+}

html/reference-community.json

@@ -129,4 +129,4 @@
     "tags": "community",
     "skip": true
   }
-}
+}

html/reference-quant.json

@@ -216,4 +216,4 @@
     "tags": "quantized",
     "date": "2025 January"
   }
-}
+}

launch.py

@@ -70,7 +70,6 @@ def get_custom_args():
     ld = [f'{k}={v}' for k, v in os.environ.items() if k.startswith('LD_')]
     compute = [f'{k}={v}' for k, v in os.environ.items() if 'TORCH' in k or 'CUDA' in k or 'ROCM' in k or 'MIOPEN' in k]
     installer.log.debug(f'Flags: sd={env} ld={ld} compute={compute}')
-    installer.log.debug(f'Flags ')
     rec('args')
 
 

modules/processing_callbacks.py

@@ -121,15 +121,14 @@ def diffusers_callback(pipe, step: int = 0, timestep: int = 0, kwargs: dict = {}
                 width = max(getattr(p, 'width', 0), getattr(p, 'hr_upscale_to_x', 0))
                 height = max(getattr(p, 'height', 0), getattr(p, 'hr_upscale_to_y', 0))
             else:
-                width = getattr(p, 'width', 0)
-                height = getattr(p, 'height', 0)
+                width = getattr(p, 'width', 1024)
+                height = getattr(p, 'height', 1024)
             shared.state.current_latent = pipe._unpack_latents(kwargs['latents'], height, width, pipe.vae_scale_factor) # pylint: disable=protected-access
             if current_noise_pred is not None:
                 shared.state.current_noise_pred = pipe._unpack_latents(current_noise_pred, height, width, pipe.vae_scale_factor) # pylint: disable=protected-access
             else:
                 shared.state.current_noise_pred = current_noise_pred
         elif hasattr(pipe, "_unpatchify_latents"): # FLUX.2 - unpack [B, seq, patch_ch] to [B, ch, H, W]
-            # Get dimensions for unpacking, same logic as FLUX.1
             vae_scale = getattr(pipe, 'vae_scale_factor', 8)
             if p.hr_resize_mode > 0 and (p.hr_upscaler != 'None' or p.hr_resize_mode == 5) and p.is_hr_pass:
                 width = max(getattr(p, 'width', 0), getattr(p, 'hr_upscale_to_x', 0))

modules/video_models/video_save.py

@@ -4,6 +4,7 @@ import cv2
 import numpy as np
 import torch
 import einops
+from PIL import Image
 from modules import shared, errors ,timer, rife, processing
 from modules.video_models.video_utils import check_av