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import gradio
class Model:
def __init__(self, name, path="", prefix=""):
self.name = name
self.path = path
self.prefix = prefix
models = [
Model("Marvel","models/ItsJayQz/Marvel_WhatIf_Diffusion", "whatif style"),
Model("Cyberpunk Anime Diffusion", "models/DGSpitzer/Cyberpunk-Anime-Diffusion", "dgs illustration style"),
Model("Portrait plus", "models/wavymulder/portraitplus", "portrait+ style"),
Model("CF25", "models/gsdf/Counterfeit-V2.5", "anime style"),
Model("vintedois", "models/22h/vintedois-diffusion-v0-1", "vintedois style"),
Model("dreamlike", "models/dreamlike-art/dreamlike-diffusion-1.0","dreamlike style"),
#Model("Orange Mix","models/WarriorMama777/OrangeMixs", "OrangeMixs style"),
Model("GTA5","models/ItsJayQz/GTA5_Artwork_Diffusion", "GTA5 style")
]
model1=[]
model2=[]
model3=[]
for i in range(len(models)):
model3.append(models[i].name)
model1.append(gradio.Interface.load(models[i].path))
model2.append(models[i].prefix)
def process1(prompt, modelSelected):
if (modelSelected==''):
modelSelected = "Marvel"
model_idx=model3.index(modelSelected)
prompt+=", in "+model2[model_idx]
image_return = model1[model_idx](prompt)
return image_return
sandbox = gradio.Interface(fn=process1,
inputs=[gradio.Textbox(label="Enter Prompt:"), gradio.Dropdown(model3)],
outputs=[gradio.Image(label="Produced Image")],
title='Text to Image')
sandbox.queue(concurrency_count=20).launch()
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