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comdoleger
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•
a88c47f
1
Parent(s):
94ded9c
Update app.py
Browse files
app.py
CHANGED
@@ -15,7 +15,7 @@ from enum import Enum
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api_key = os.getenv("FAI_API_KEY")
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api = os.getenv("FAI_API")
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-
#api_anime = os.getenv("ANIME_API")
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rmbgkey = os.getenv("RMBGKEY")
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#fore, prompt, intensity, mode, refprompt, isrmbg
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@@ -216,9 +216,9 @@ def resize_to_fit(max_size, original_size):
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def process_generate(fore, prompt, intensity, mode, refprompt, isrmbg, model_type, steps, control_strength):
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max_size = (
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if prompt in prompt_list:
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max_size = (
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if isrmbg:
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try:
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rmbgfore = rmbg(fore)
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@@ -233,12 +233,12 @@ def process_generate(fore, prompt, intensity, mode, refprompt, isrmbg, model_typ
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image_width = size[0]
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image_height = size[1]
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if size[0]*size[1]<=(
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gr.Warning("ℹ️ The input image resolution is low, it might lead to some deformation!")
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if size[0]*size[1]>(max_size[0]*max_size[1]):
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gr.Warning("ℹ️ The input image size is too big, I will lower it!")
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image_width, image_height = resize_to_fit((
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fore.resize(max_size)
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@@ -250,17 +250,17 @@ def process_generate(fore, prompt, intensity, mode, refprompt, isrmbg, model_typ
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"prompt" : prompt,
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"mode" : mode,
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"intensity" : float(intensity),
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"width" :
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"height" :
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"refprompt" : refprompt,
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"first_stage_steps" : int(steps),
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"first_stage_strength" : float(control_strength),
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-
"second_stage_steps" :
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}
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# Select the endpoint based on the model type
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if model_type == "anime":
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-
api_endpoint =
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elif model_type == "realistic":
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api_endpoint = api
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else:
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api_key = os.getenv("FAI_API_KEY")
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api = os.getenv("FAI_API")
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+
api_anime = os.getenv("FAI_API_2") #api_anime = os.getenv("ANIME_API")
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rmbgkey = os.getenv("RMBGKEY")
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#fore, prompt, intensity, mode, refprompt, isrmbg
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def process_generate(fore, prompt, intensity, mode, refprompt, isrmbg, model_type, steps, control_strength):
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max_size = (768,768)
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if prompt in prompt_list:
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max_size = (768,768)
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if isrmbg:
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try:
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rmbgfore = rmbg(fore)
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image_width = size[0]
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image_height = size[1]
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if size[0]*size[1]<=(512*512):
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gr.Warning("ℹ️ The input image resolution is low, it might lead to some deformation!")
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if size[0]*size[1]>(max_size[0]*max_size[1]):
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gr.Warning("ℹ️ The input image size is too big, I will lower it!")
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image_width, image_height = resize_to_fit((768,768), (image_width, image_height))
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fore.resize(max_size)
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"prompt" : prompt,
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"mode" : mode,
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"intensity" : float(intensity),
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"width" : 1000,
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"height" : 1000,
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"refprompt" : refprompt,
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"first_stage_steps" : int(steps),
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"first_stage_strength" : float(control_strength),
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"second_stage_steps" : 20
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}
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# Select the endpoint based on the model type
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if model_type == "anime":
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api_endpoint = api_anime #to change to api_anime
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elif model_type == "realistic":
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api_endpoint = api
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else:
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