Update presets_to_add.py

presets_to_add.py

@@ -1,4 +1,4 @@
-from .custom_samplers import distance_wrap
+from .custom_samplers import distance_wrap, perp_step_wrap
 
 extra_samplers = {}
 
@@ -11,18 +11,37 @@ extra_samplers["the_name_that_you_want"] = distance_wrap(resample=3,resample_end
 "resample" is the starting value, how many more inferences it will use. More is slower.
 For resample_end "-1" means constant.
 Constant resample at 0 gives Euler, 1 gives Heun.
-cfgpp will determin if you want it or not. True or False.
-
+Other variables:
+ - use_negative: will use the negative prediction to prepare the distance scores. This tends to give images with less errors from my testing.
+ - cfgpp: will determin if you want it or not. True or False.
+ - use_slerp: will slerp the predictions instead of doing a weighted average. The difference is more obvious when using use_negative.
+ - use_softmax: rather than using a min/max normalization and an exponent will use a softmax instead.
+ - sharpen: not recommanded, attempts to sharpen the results but instead tends to make things fuzzy.
+ - smooth: not recommanded, will make everything brighter. Not smoother.
+ - perp step: experimental, not yet recommanded.
+PerpStep is a test sampler, uncomment if you want to try.
 """
 
-extra_samplers["distance_fast"] = distance_wrap(resample=3,resample_end=1,cfgpp=False) # s3e1
-extra_samplers["distance_s4e1"] = distance_wrap(resample=4,resample_end=1,cfgpp=False)
-# extra_samplers["distance_step1"] = distance_wrap(resample=-1,resample_end=1,cfgpp=False)
-# extra_samplers["distance_step0"] = distance_wrap(resample=-1,resample_end=1,cfgpp=False)
+# Codename is Distance_fast_slerp_n
+extra_samplers["Distance"] = distance_wrap(resample=3,resample_end=1,cfgpp=False,sharpen=False,use_slerp=True,use_negative=True)
 
-extra_samplers["distance_fast_cfg_pp"] = distance_wrap(resample=3,resample_end=1,cfgpp=True)
-extra_samplers["distance_s4e1_cfg_pp"] = distance_wrap(resample=4,resample_end=1,cfgpp=True)
-# extra_samplers["distance_c2_cfg_pp"] = distance_wrap(resample=2,resample_end=-1,cfgpp=True)
+# extra_samplers["PerpStep"] = perp_step_wrap(s=0.5)
+# extra_samplers["euler_test"] = distance_wrap(resample=0,resample_end=-1)
+# extra_samplers["heun_test"] = distance_wrap(resample=1,resample_end=1)
+# extra_samplers["Distance_fast"] = distance_wrap(resample=3,resample_end=1,cfgpp=False,sharpen=False)
+# extra_samplers["Distance_fast_n"] = distance_wrap(resample=3,resample_end=1,cfgpp=False,sharpen=False,use_negative=True)
+# extra_samplers["Distance_fast_slerp"] = distance_wrap(resample=3,resample_end=1,cfgpp=False,sharpen=False,use_slerp=True)
+# extra_samplers["Distance_fast_slerp_n"] = distance_wrap(resample=3,resample_end=1,cfgpp=False,sharpen=False,use_slerp=True,use_negative=True)
+# extra_samplers["Distance_fast_slerp_p"] = distance_wrap(resample=3,resample_end=1,cfgpp=False,sharpen=False,use_slerp=True,perp_step=True)
+# extra_samplers["Distance_fast_slerp_np"] = distance_wrap(resample=3,resample_end=1,cfgpp=False,sharpen=False,use_slerp=True,use_negative=True,perp_step=True)
+
+# # constant
+# extra_samplers["distance_c2"] = distance_wrap(resample=2,resample_end=-1,cfgpp=False,sharpen=False)
+# extra_samplers["distance_c3"] = distance_wrap(resample=3,resample_end=-1,cfgpp=False,sharpen=False)
+# extra_samplers["distance_c4"] = distance_wrap(resample=4,resample_end=-1,cfgpp=False,sharpen=False)
+# extra_samplers["Distance_cfgpp"] = distance_wrap(resample=4,resample_end=-1,sharpen=False,cfgpp=True)
+
+# cfgpp
 # extra_samplers["distance_step_cfg_pp"] = distance_wrap(resample=-1,resample_end=1,cfgpp=True)
-
+extra_samplers["euler_cfg_pp_alt"] = distance_wrap(resample=0,cfgpp=True)
 extra_samplers["heun_cfg_pp"] = distance_wrap(resample=1,cfgpp=True)