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import gradio |
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class Model: |
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def __init__(self, name, path="", prefix=""): |
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self.name = name |
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self.path = path |
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self.prefix = prefix |
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models = [ |
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Model("Anime","models/DucHaiten/DucHaitenAnime","DucHaiten style"), |
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Model("dreamlike","models/dreamlike-art/dreamlike-diffusion-1.0","dreamlike style"), |
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Model("CF25","models/gsdf/Counterfeit-V2.5","best quality"), |
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Model("Midjourney","models/prompthero/midjourney-v4-diffusion","midjourney style"), |
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Model("PhotoReal","models/dreamlike-art/dreamlike-photoreal-2.0","photoreal style"), |
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Model("MF Base","models/MyneFactory/MF-Base","booru style"), |
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Model("Anything","models/Linaqruf/anything-v3.0", "Anything style") |
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] |
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model1=[] |
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model2=[] |
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model3=[] |
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for i in range(len(models)): |
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model3.append(models[i].name) |
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model1.append(gradio.Interface.load(models[i].path)) |
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model2.append(models[i].prefix) |
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def ProcessP(prompt, modelSelected): |
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print(prompt) |
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print(modelSelected) |
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if (modelSelected==''): |
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modelSelected = "Anything" |
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model_idx=model3.index(modelSelected) |
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prompt+=", in "+model2[model_idx] |
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image_return = model1[model_idx](prompt) |
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return image_return |
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sandbox = gradio.Interface(fn=ProcessP, |
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inputs=[gradio.Textbox(label="Enter Prompt:"), gradio.Dropdown(model3)], |
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outputs=[gradio.Image(label="Produced Image")], |
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title='AlStable Text to Image') |
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sandbox.queue(concurrency_count=20).launch(debug=True) |
