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Update app.py
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app.py
CHANGED
@@ -483,17 +483,16 @@ async def on_message(message):
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e = await message.reply(embed=embed)
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if imgp != "":
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-
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np = ""
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st = time.time()
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if imageModel == "Stable Diffusion 2-1":
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image, m = (await SD.text_to_image(imgp, negative_prompt=np), "Stable Diffusion 2-1")
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elif imageModel == "stable-diffusion-xl-base-1.0":
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image, m = (await SDXL.text_to_image(imgp, negative_prompt=np, num_inference_steps=8), "stable-diffusion-xl-base-1.0")
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elif imageModel == "sdxl-turbo":
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image, m = (await SDXLT.text_to_image(imgp, negative_prompt=np, num_inference_steps=
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elif imageModel == "sd-turbo":
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image, m = (await SDT.text_to_image(imgp, negative_prompt=np, num_inference_steps=
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elif imageModel == "Proteus v0.2":
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image, m = (await PT.text_to_image(imgp, negative_prompt=np), "Proteus v0.2")
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else:
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@@ -507,7 +506,7 @@ async def on_message(message):
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)
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await e.edit(embed=embed, attachments=[file])
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gt = time.time()
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image, r = (await RF.image_to_image("image.png", num_inference_steps=
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rt = time.time()
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embed.set_footer(
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text=
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e = await message.reply(embed=embed)
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if imgp != "":
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np = """lowres, error, cropped, worst quality, low quality, ugly, duplicate, morbid, mutilated, out of frame, blurry, watermark, signature"""
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st = time.time()
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if imageModel == "Stable Diffusion 2-1":
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image, m = (await SD.text_to_image(imgp, negative_prompt=np), "Stable Diffusion 2-1")
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elif imageModel == "stable-diffusion-xl-base-1.0":
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image, m = (await SDXL.text_to_image(imgp, negative_prompt=np, num_inference_steps=8), "stable-diffusion-xl-base-1.0")
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elif imageModel == "sdxl-turbo":
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image, m = (await SDXLT.text_to_image(imgp, negative_prompt=np, num_inference_steps=4, guidance_scale=0.0), "sdxl-turbo")
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elif imageModel == "sd-turbo":
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image, m = (await SDT.text_to_image(imgp, negative_prompt=np, num_inference_steps=4, guidance_scale=0.0), "sd-turbo")
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elif imageModel == "Proteus v0.2":
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image, m = (await PT.text_to_image(imgp, negative_prompt=np), "Proteus v0.2")
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else:
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)
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await e.edit(embed=embed, attachments=[file])
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gt = time.time()
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image, r = (await RF.image_to_image("image.png", num_inference_steps=8, prompt=imgp, negative_prompt=np), "stable-diffusion-xl-refiner-1.0")
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rt = time.time()
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embed.set_footer(
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text=
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