alfredplpl commited on
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c8d73ef
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1 Parent(s): 114766c

Update app.py

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Files changed (1) hide show
  1. app.py +13 -4
app.py CHANGED
@@ -5,16 +5,25 @@ import spaces
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  import torch
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  import os
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  model_id = "aipicasso/emi-2"
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  token=os.environ["TOKEN"]
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  scheduler = EulerAncestralDiscreteScheduler.from_pretrained(model_id,subfolder="scheduler",token=token)
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  pipe_normal = StableDiffusionXLPipeline.from_pretrained(model_id, scheduler=scheduler, torch_dtype=torch.bfloat16,token=token)
 
 
 
 
 
 
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  pipe_normal.to("cuda")
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  @spaces.GPU
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- def run_normal(prompt, negative_prompt="", guidance_scale=7, progress=gr.Progress(track_tqdm=True)):
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- return pipe_normal(prompt, negative_prompt=negative_prompt, guidance_scale=guidance_scale, num_inference_steps=20).images[0]
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  css = '''
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  .gradio-container{
@@ -23,14 +32,14 @@ margin: 0 auto;
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  }
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  '''
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- normal_examples = ["portrait photo of a girl, photograph, highly detailed face, depth of field, moody light, golden hour, style by Dan Winters, Russell James, Steve McCurry, centered, extremely detailed, Nikon D850, award winning photography", "backlit photography of a dog", "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k", "A photo of beautiful mountain with realistic sunset and blue lake, highly detailed, masterpiece"]
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  with gr.Blocks(css=css) as demo:
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  gr.Markdown('''# Emi 2
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  Official demo for Emi 2
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  ''')
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  with gr.Group():
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  with gr.Row():
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- prompt_normal = gr.Textbox(show_label=False, scale=4, placeholder="Your prompt, e.g.: backlit photography of a dog")
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  button_normal = gr.Button("Generate", min_width=120)
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  output_normal = gr.Image(label="Your result image", interactive=False)
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  with gr.Accordion("Advanced Settings", open=False):
 
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  import torch
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  import os
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+ from huggingface_hub import hf_hub_download
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+
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  model_id = "aipicasso/emi-2"
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  token=os.environ["TOKEN"]
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  scheduler = EulerAncestralDiscreteScheduler.from_pretrained(model_id,subfolder="scheduler",token=token)
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  pipe_normal = StableDiffusionXLPipeline.from_pretrained(model_id, scheduler=scheduler, torch_dtype=torch.bfloat16,token=token)
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+
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+ negative_ti_file = hf_hub_download(repo_id="Aikimi/unaestheticXL_Negative_TI", filename="unaestheticXLv31.safetensors")
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+ state_dict = load_file(negative_ti_file)
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+ pipe.load_textual_inversion(state_dict["clip_g"], token="unaestheticXLv31", text_encoder=pipe.text_encoder_2, tokenizer=pipe.tokenizer_2)
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+ pipe.load_textual_inversion(state_dict["clip_l"], token="unaestheticXLv31", text_encoder=pipe.text_encoder, tokenizer=pipe.tokenizer)
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+
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  pipe_normal.to("cuda")
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+
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  @spaces.GPU
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+ def run_normal(prompt, negative_prompt="", guidance_scale=7.5, progress=gr.Progress(track_tqdm=True)):
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+ return pipe_normal(prompt, negative_prompt="unaestheticXLv31"+negative_prompt, guidance_scale=guidance_scale, num_inference_steps=20).images[0]
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  css = '''
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  .gradio-container{
 
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  }
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  '''
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+ normal_examples = ["1girl, face, brown bob short hair, brown eyes, looking at viewer"]
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  with gr.Blocks(css=css) as demo:
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  gr.Markdown('''# Emi 2
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  Official demo for Emi 2
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  ''')
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  with gr.Group():
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  with gr.Row():
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+ prompt_normal = gr.Textbox(show_label=False, scale=4, placeholder="Your prompt, e.g.: 1girl, face, brown bob short hair, brown eyes, looking at viewer")
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  button_normal = gr.Button("Generate", min_width=120)
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  output_normal = gr.Image(label="Your result image", interactive=False)
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  with gr.Accordion("Advanced Settings", open=False):