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1 Parent(s): cbd30d7

Update app.py

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  1. app.py +5 -52
app.py CHANGED
@@ -1,75 +1,28 @@
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  # ==============================
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- # Basic Interface
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- # ==============================
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-
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- #import gradio as gr
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- #demo = gr.load("mswhite/miamivice", src="models")
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- #demo.launch()
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-
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- # ==============================
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- # Detailed Interface
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  # ==============================
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  import os
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  import gradio as gr
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  import torch
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  from diffusers import DiffusionPipeline, StableDiffusionPipeline, StableDiffusionImg2ImgPipeline
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- # Nvidia GPU config
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-
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- #from diffusers import DiffusionPipeline
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- #pipe = DiffusionPipeline.from_pretrained("mswhite/nnn-model")
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-
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  pipe = StableDiffusionPipeline.from_pretrained("mswhite/bricksburg_model", torch_dtype=torch.float16) #, safety_checker=None)
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  pipe = pipe.to("cuda")
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  pipe.safety_checker = lambda images, **kwargs: (images, [False] * len(images))
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- # CPU config
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- #pipe = StableDiffusionPipeline.from_pretrained("mswhite/miamivice")
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-
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- # Optional Img2Img pipeline
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-
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- #pipe_img = StableDiffusionImg2ImgPipeline.from_pretrained("mswhite/miamivice", torch_dtype=torch.float16, safety_checker=None)
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- #pipe_img = pipe_img.to("cuda")
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-
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- # Sample Prompt - "bright clean clear illustration side profile of a woman wearing pink lipstick p_nagel"
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-
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- def nagelize(text):
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  prompt = "mini_mw_lgo" + text
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  return pipe(prompt).images[0]
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- #def nagelize_me(source_image):
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- # prompt = "p_nagel"
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- # return pipe_img(prompt, image=source_image, strength=0.6, num_inference_steps=500, guidance_scale=40.0).images[0]
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-
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- # Web Version of Blocks()
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-
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- #with gr.Blocks() as demo:
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-
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- #girl_image = gr.Image(label = None, value = os.path.join(os.path.dirname(__file__), "headshot.jpg"), visible=False)
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-
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- # with gr.Row():
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- # logo_image = gr.Image(label = None, value = os.path.join(os.path.dirname(__file__), "miami.jpg"), interactive=True).style(height=720)
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- # #gr.Markdown("<img src=https://huggingface.co/spaces/mswhite/miamivice/resolve/main/miami.jpg width=720px>")
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- # output = gr.Image(label="Output").style(height=720)
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- # with gr.Row():
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- # art_to_draw = gr.Textbox(label="Prompt to Draw: e.g. woman with red hair")
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- # flashb_btn = gr.Button("Flashback to the 80s")
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- # #back80_btn = gr.Button("Send me back to the 80s")
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-
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- # flashb_btn.click(fn=nagelize, inputs=[art_to_draw], outputs=[output])
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- # #back80_btn.click(fn=nagelize, inputs=[art_to_draw], outputs=[output])
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-
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- # Mobile Version of Blocks
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-
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  with gr.Blocks() as demo:
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  gr.Markdown("<img src=https://huggingface.co/spaces/mswhite/Bricksburg/resolve/main/Emmet.jpg width=720px>")
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  output = gr.Image(label="Output").style(width=720)
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  art_to_draw = gr.Textbox(label="Prompt to Draw: e.g. ")
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  flashb_btn = gr.Button("Everything is Awesome in Bricksburg")
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- flashb_btn.click(fn=nagelize, inputs=[art_to_draw], outputs=[output])
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  demo.launch()
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-
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-
 
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  # ==============================
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+ # Program
 
 
 
 
 
 
 
 
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  # ==============================
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+ import spaces
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  import os
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  import gradio as gr
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  import torch
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  from diffusers import DiffusionPipeline, StableDiffusionPipeline, StableDiffusionImg2ImgPipeline
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  pipe = StableDiffusionPipeline.from_pretrained("mswhite/bricksburg_model", torch_dtype=torch.float16) #, safety_checker=None)
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  pipe = pipe.to("cuda")
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  pipe.safety_checker = lambda images, **kwargs: (images, [False] * len(images))
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+ @spaces.GPU
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+ def legoize(text):
 
 
 
 
 
 
 
 
 
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  prompt = "mini_mw_lgo" + text
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  return pipe(prompt).images[0]
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  with gr.Blocks() as demo:
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  gr.Markdown("<img src=https://huggingface.co/spaces/mswhite/Bricksburg/resolve/main/Emmet.jpg width=720px>")
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  output = gr.Image(label="Output").style(width=720)
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  art_to_draw = gr.Textbox(label="Prompt to Draw: e.g. ")
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  flashb_btn = gr.Button("Everything is Awesome in Bricksburg")
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+ flashb_btn.click(fn=legoize, inputs=[art_to_draw], outputs=[output])
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  demo.launch()