thomasgauthier commited on
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cb2237b
1 Parent(s): ea9e4b8

updated markdown

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Files changed (1) hide show
  1. gradio_interface.py +3 -2
gradio_interface.py CHANGED
@@ -12,7 +12,7 @@ def create_gradio_interface(process_and_generate):
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  def gradio_process_and_generate(input_image, prompt, num_images, cfg_weight):
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  return process_and_generate(input_image, prompt, num_images, cfg_weight)
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- explanation = """Janus 1.3B uses a differerent visual encoder for understanding and generation.
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  ![Janus Model Architecture](https://huggingface.co/spaces/thomasgauthier/HowJanusSeesItself/raw/main/images/janus_architecture.svg)
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@@ -25,6 +25,8 @@ Here, by feeding the model an image and then asking it to generate that same ima
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  with gr.Row():
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  input_image = gr.Image(type="filepath", label="Input Image")
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  output_images = gr.Gallery(label="Generated Images", columns=2, rows=2)
 
 
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  prompt = gr.Textbox(label="Prompt", value="Exactly what is shown in the image.")
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  num_images = gr.Slider(minimum=1, maximum=12, value=12, step=1, label="Number of Images to Generate")
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  cfg_weight = gr.Slider(minimum=1, maximum=10, value=5, step=0.1, label="CFG Weight")
@@ -40,6 +42,5 @@ Here, by feeding the model an image and then asking it to generate that same ima
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  inputs=[input_image, dummy]
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  )
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- gr.Markdown(explanation)
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  return demo
 
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  def gradio_process_and_generate(input_image, prompt, num_images, cfg_weight):
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  return process_and_generate(input_image, prompt, num_images, cfg_weight)
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+ explanation = """[Janus 1.3B](https://huggingface.co/deepseek-ai/Janus-1.3B) uses differerent visual encoders for understanding and generation.
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  ![Janus Model Architecture](https://huggingface.co/spaces/thomasgauthier/HowJanusSeesItself/raw/main/images/janus_architecture.svg)
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  with gr.Row():
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  input_image = gr.Image(type="filepath", label="Input Image")
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  output_images = gr.Gallery(label="Generated Images", columns=2, rows=2)
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+
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+ gr.Markdown(explanation)
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  prompt = gr.Textbox(label="Prompt", value="Exactly what is shown in the image.")
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  num_images = gr.Slider(minimum=1, maximum=12, value=12, step=1, label="Number of Images to Generate")
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  cfg_weight = gr.Slider(minimum=1, maximum=10, value=5, step=0.1, label="CFG Weight")
 
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  inputs=[input_image, dummy]
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  )
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  return demo