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Create app.py
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app.py
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import torch
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from diffusers import StableDiffusionPipeline
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from diffusers import AutoPipelineForText2Image
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import gradio as gr
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img_generator1 = AutoPipelineForText2Image.from_pretrained("kandinsky-community/kandinsky-2-2-decoder", torch_dtype=torch.float16)
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img_generator1.to("cuda" if torch.cuda.is_available() else "cpu")
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# Chargement du modèle Stable Diffusion v1.4 depuis Hugging Face
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img_generator2 = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4",torch_dtype=torch.float16)
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img_generator2.to("cuda" if torch.cuda.is_available() else "cpu")
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# Fonction de génération d’image à partir du texte
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def text_to_image(prompt, model_name):
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if model_name == 'kandinsky-2-2-decoder':
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return img_generator1(prompt=prompt).images[0]
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else:
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return img_generator2(prompt=prompt).images[0]
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# Interface Gradio simple
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gr.Interface(
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fn=text_to_image,
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inputs= [gr.Textbox(label="Entrez une description (prompt)"),
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gr.Dropdown(choices =['kandinsky-2-2-decoder', 'stable-diffusion-v1-4'], label = 'Model Name')],
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outputs=gr.Image(type="pil", label="Image générée"),
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title="Générateur d'Images à partir de Texte",
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description="Entrez un texte pour générer une image"
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).launch()
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