multimodalart HF staff commited on
Commit
511ace8
1 Parent(s): 94b944a

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +12 -12
app.py CHANGED
@@ -25,13 +25,14 @@ transformer = FluxTransformer2DModel.from_pretrained(
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  subfolder="transformer",
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  torch_dtype=torch.bfloat16
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  )
 
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  pipe = FluxPipeline.from_pretrained(
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  "black-forest-labs/FLUX.1-dev",
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  transformer=transformer,
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  torch_dtype=torch.bfloat16
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  )
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- ip_model = IPAdapter(pipe, image_encoder_path, ipadapter_path, device="cuda", num_tokens=128)
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  def resize_img(image, max_size=1024):
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  width, height = image.size
@@ -95,12 +96,19 @@ with gr.Blocks(css=css) as demo:
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  label="Input Image",
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  type="pil"
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  )
 
 
 
 
 
 
 
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  prompt = gr.Text(
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  label="Prompt",
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  max_lines=1,
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  placeholder="Enter your prompt",
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  )
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- run_button = gr.Button("Process", variant="primary")
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  with gr.Column():
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  result = gr.Image(label="Result")
@@ -122,7 +130,7 @@ with gr.Blocks(css=css) as demo:
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  minimum=256,
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  maximum=MAX_IMAGE_SIZE,
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  step=32,
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- value=960,
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  )
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  height = gr.Slider(
@@ -130,16 +138,8 @@ with gr.Blocks(css=css) as demo:
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  minimum=256,
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  maximum=MAX_IMAGE_SIZE,
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  step=32,
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- value=1280,
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  )
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-
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- scale = gr.Slider(
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- label="Scale",
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- minimum=0.0,
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- maximum=1.0,
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- step=0.1,
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- value=0.7,
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- )
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  run_button.click(
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  fn=process_image,
 
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  subfolder="transformer",
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  torch_dtype=torch.bfloat16
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  )
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+
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  pipe = FluxPipeline.from_pretrained(
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  "black-forest-labs/FLUX.1-dev",
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  transformer=transformer,
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  torch_dtype=torch.bfloat16
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  )
 
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+ ip_model = IPAdapter(pipe, image_encoder_path, ipadapter_path, device="cuda", num_tokens=128)
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  def resize_img(image, max_size=1024):
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  width, height = image.size
 
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  label="Input Image",
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  type="pil"
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  )
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+ scale = gr.Slider(
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+ label="Image Scale",
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+ minimum=0.0,
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+ maximum=1.0,
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+ step=0.1,
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+ value=0.7,
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+ )
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  prompt = gr.Text(
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  label="Prompt",
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  max_lines=1,
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  placeholder="Enter your prompt",
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  )
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+ run_button = gr.Button("Generate", variant="primary")
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  with gr.Column():
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  result = gr.Image(label="Result")
 
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  minimum=256,
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  maximum=MAX_IMAGE_SIZE,
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  step=32,
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+ value=1024,
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  )
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  height = gr.Slider(
 
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  minimum=256,
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  maximum=MAX_IMAGE_SIZE,
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  step=32,
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+ value=1024,
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  )
 
 
 
 
 
 
 
 
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  run_button.click(
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  fn=process_image,