cleanup

README.md

@@ -221,13 +221,14 @@ This should be fully cross-platform, but we'd really love to have additional con
 ### **Evolution**
 
 <a href="https://star-history.com/#vladmandic/automatic&Date">
-  <picture>
+  <picture width=640>
     <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=vladmandic/automatic&type=Date&theme=dark" />
-    <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=vladmandic/automatic&type=Date" />
-    <img alt="Star History Chart" src="https://api.star-history.com/svg?repos=vladmandic/automatic&type=Date" />
+    <img src="https://api.star-history.com/svg?repos=vladmandic/automatic&type=Date" alt="starts" width="320">
   </picture>
 </a>
 
+- [OSS Stats](https://ossinsight.io/analyze/vladmandic/automatic#overview)
+
 ### **Docs**
 
 If you're unsure how to use a feature, best place to start is [Wiki](https://github.com/vladmandic/automatic/wiki) and if its not there,  

TODO.md

@@ -6,13 +6,18 @@ Main ToDo list can be found at [GitHub projects](https://github.com/users/vladma
 
 - zluda
 - stable cascade
-- control second pass: <https://github.com/vladmandic/automatic/issues/2783>  
-- onediff: <https://github.com/siliconflow/onediff>
+- init latents, variations, tiling
+- lora sliders: <https://github.com/vladmandic/automatic/issues/2868>
 - diffusers public callbacks  
 - image2video: pia and vgen pipelines  
 - video2video
+- preprocess api  
+
+## Control missing features
+
+- second pass: <https://github.com/vladmandic/automatic/issues/2783>  
+- inpaint masking explicit processing size: <https://github.com/vladmandic/automatic/issues/2857>
+- outpaint return mask and optional override future run_masking
 - control api  
 - masking api  
-- preprocess api  
-- bind panZoom to control input
-- masking.outpaint should return mask and override future run_masking
+- inpaint pan/zoom

extensions-builtin/Lora/lora_convert.py

@@ -109,7 +109,6 @@ class KeyConvert:
         if shared.backend == shared.Backend.ORIGINAL:
             self.converter = self.original
             self.is_sd2 = 'model_transformer_resblocks' in shared.sd_model.network_layer_mapping
-
         else:
             self.converter = self.diffusers
             self.is_sdxl = True if shared.sd_model_type == "sdxl" else False

extensions-builtin/Lora/network.py

@@ -6,7 +6,6 @@ import enum
 from modules import sd_models, hashes, shared
 
 NetworkWeights = namedtuple('NetworkWeights', ['network_key', 'sd_key', 'w', 'sd_module'])
-
 metadata_tags_order = {"ss_sd_model_name": 1, "ss_resolution": 2, "ss_clip_skip": 3, "ss_num_train_images": 10, "ss_tag_frequency": 20}
 
 

extensions-builtin/Lora/network_lora.py

@@ -1,5 +1,4 @@
 import torch
-
 import diffusers.models.lora as diffusers_lora
 import lyco_helpers
 import network

modules/sd_models.py

@@ -236,8 +236,8 @@ def select_checkpoint(op='model'):
     if len(checkpoints_list) == 0:
         shared.log.warning("Cannot generate without a checkpoint")
         shared.log.info("Set system paths to use existing folders in a different location")
-        shared.log.info("  or use --models_dir <path-to-folder> to specify base folder with all models")
-        shared.log.info("  or use --ckpt_dir <path-to-folder> to specify folder with models")
+        shared.log.info("  or use --models-dir <path-to-folder> to specify base folder with all models")
+        shared.log.info("  or use --ckpt-dir <path-to-folder> to specify folder with sd models")
         shared.log.info("  or use --ckpt <path-to-checkpoint> to force using existing model")
         return None
     checkpoint_info = next(iter(checkpoints_list.values()))