UI update
Browse files
app.py
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@@ -5,28 +5,6 @@ from PIL import Image
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from model import *
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# SAFETY_CHECKER = os.environ.get("SAFETY_CHECKER", "0") == "1"
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# Constants
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# base = "stabilityai/stable-diffusion-xl-base-1.0"
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# repo = "ByteDance/SDXL-Lightning"
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# checkpoints = {
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# "1-Step" : ["sdxl_lightning_1step_unet_x0.safetensors", 1],
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# "2-Step" : ["sdxl_lightning_2step_unet.safetensors", 2],
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# "4-Step" : ["sdxl_lightning_4step_unet.safetensors", 4],
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# "8-Step" : ["sdxl_lightning_8step_unet.safetensors", 8],
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# }
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# loaded = None
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# Ensure model and scheduler are initialized in GPU-enabled function
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# if torch.cuda.is_available():
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# pipe = StableDiffusionXLPipeline.from_pretrained(base, torch_dtype=torch.float16, variant="fp16").to("cuda")
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# Function
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# @spaces.GPU(enable_queue=True)
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def generate_image(prompt):
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return prompt_to_img(prompt)[0]
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# Gradio Interface
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description = """
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This demo utilizes
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"""
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with gr.Blocks(css="style.css") as demo:
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gr.HTML("<h1><center>
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gr.Markdown(description)
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with gr.Group():
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with gr.Row():
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prompt = gr.Textbox(label='Enter your prompt
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ckpt = gr.Dropdown(label='Select inference steps',choices=['1-Step', '2-Step', '4-Step', '8-Step'], value='4-Step', interactive=True)
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submit = gr.Button(scale=1, variant='primary')
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img = gr.Image(label='
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prompt.submit(fn=generate_image,
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inputs=[prompt],
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from model import *
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def generate_image(prompt):
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return prompt_to_img(prompt)[0]
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# Gradio Interface
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description = """
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This demo utilizes a specialized variant of the Stable Diffusion model designed for multilingual text-to-image synthesis. In response to the observed underperformance of existing models on languages beyond English, this project introduces the Multilingual Stable Diffusion, providing a more inclusive solution for diverse linguistic contexts.
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Link to Github repo: https://github.com/NajlaaNawaii/Multilingual-Stable-Diffusion-Towards-more-Inclusive-Text-To-Image-Synthesis
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"""
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with gr.Blocks(css="style.css") as demo:
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gr.HTML("<h1><center>Multilingual Stable Diffusion 🧨</center></h1>")
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gr.Markdown(description)
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with gr.Group():
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with gr.Row():
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prompt = gr.Textbox(label='Enter your prompt', scale=8)
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submit = gr.Button(scale=1, variant='primary')
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img = gr.Image(label='Generated Image')
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prompt.submit(fn=generate_image,
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inputs=[prompt],
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