@@ -67,6 +67,13 @@ def predict(
6767 description = "Input prompt." ,
6868 default = "Add character to the scene" ,
6969 ),
70+ negative_prompt : str = Input (
71+ description = "Input negative prompt." ,
72+ default = "Bad, low quality, deformed, distorted, distorted, ugly" ,
73+ ),
74+ should_optimise_reference : bool = Input (
75+ description = "Should optimise reference?" , default = None , choices = [True , False , None ]
76+ ),
7077 num_inference_steps : int = Input (
7178 description = "Number of denoising steps" , ge = 1 , le = 150 , default = 20
7279 ),
@@ -137,14 +144,13 @@ def predict(
137144 reference_image = reference_image .resize ((width , height ), Image .LANCZOS )
138145
139146 try :
140- if has_reference :
141- optimised_reference , new_reference_delta = optimise_image_condition (reference_image , delta )
147+ if should_optimise_reference is None :
148+ should_optimise_reference = delta [0 ] == 1
149+ if has_reference and should_optimise_reference :
150+ print ("optimising reference" )
151+ reference_image , delta = optimise_image_condition (reference_image , delta )
142152 try :
143- print ("optimised_reference: " , optimised_reference )
144- print ("new_reference_delta: " , new_reference_delta )
145- o = "/tmp/optimised_reference.png"
146- optimised_reference .save (o )
147- print ("saved optimised_reference to: " , Path (o ))
153+ print ("delta: " , delta )
148154 except Exception as e :
149155 print ("Error saving optimised reference: " , e )
150156
@@ -159,6 +165,7 @@ def predict(
159165 print ("guidance_scale: " , guidance_scale )
160166 result_img = self .pipe (
161167 prompt = prompt ,
168+ negative_prompt = negative_prompt ,
162169 image = image ,
163170 reference = reference_image if has_reference else None ,
164171 reference_delta = delta if has_reference else None ,
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