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Upload app.py

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  1. app.py +38 -0
app.py ADDED
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+ from googletrans import Translator
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+ from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
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+ import torch
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+ import gradio as gr
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+
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+ translator = Translator()
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+
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+ model_id = "stabilityai/stable-diffusion-2-1"
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+ access_token="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"
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+
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+ pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16, use_auth_token=access_token
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+ )
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+
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+ pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
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+ pipe = pipe.to("cuda")
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+
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+ def generate(prompt, inference_steps, guidance_scale, neg_prompt):
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+ if not neg_prompt:
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+ neg_prompt = ""
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+
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+ prompt_eng = translator.translate(prompt, dest='en').text
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+ image = pipe(prompt_eng, guidance_scale= int(guidance_scale), num_inference_steps = int(inference_steps), negative_prompt = neg_prompt).images[0]
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+ return image
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+
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+ gr.Interface(
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+ generate,
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+ title = 'Image to Image using Diffusers',
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+ inputs=[
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+ gr.Textbox(label="Prompt"),
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+ gr.Slider(50, 700, value=50, label ="Inference steps"),
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+ gr.Slider(1, 10, value=5, label ="Guidance scale"),
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+ gr.Textbox(label="Negative prompt (include things you DO NOT want in the image")
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+ ],
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+ outputs = [
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+ gr.Image(elem_id="output-image"),
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+
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+ ], css = "#output-image, #input-image, #image-preview {border-radius: 40px !important; background-color : gray !important;} "
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+ ).launch()