sayedM commited on
Commit
284934e
·
1 Parent(s): b88406a

Update app.py

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Files changed (1) hide show
  1. app.py +25 -6
app.py CHANGED
@@ -59,12 +59,12 @@ def get_results(image, prompt):
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  # Define the input components for Gradio (adding a new input for the prompt)
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- image_input = gr.inputs.Image()
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- text_input = gr.inputs.Textbox(label="Prompt") # New input for the text prompt
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- # Define the output components for Gradio (including both image and text)
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- outputs = gr.Image(type="numpy", label="Output Image")
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  # Define the text description within an HTML <div> element
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  description_html = """
@@ -105,16 +105,29 @@ title = "autoannotation"
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  description = "This is a project description. It demonstrates how to use Gradio with an image and text input to interact with an API."
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  # Create a Blocks object and use it as a context manager
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  with gr.Blocks() as demo:
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  gr.Markdown(
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  """
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  # Tuba Autoannotation Demo
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- This is your private demo for [Tuba Autoannotation](https://Tuba.ai),
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- a simple and controllable model for music generation
 
 
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  """
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  )
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  # Define the input components and add them to the layout
 
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  with gr.Row():
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  image_input = gr.inputs.Image()
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  output = gr.Image(type="numpy", label="Output Image")
@@ -128,6 +141,12 @@ with gr.Blocks() as demo:
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  # Define the event listener that connects the input and output components and triggers the function
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  button.click(fn=get_results, inputs=[image_input, text_input], outputs=output, api_name="get_results")
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  # Add the description below the layout
 
 
 
 
 
 
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  gr.Markdown(description_html)
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  # Launch the app
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  demo.launch(share=False)
 
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  # Define the input components for Gradio (adding a new input for the prompt)
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+ # image_input = gr.inputs.Image()
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+ # text_input = gr.inputs.Textbox(label="Prompt") # New input for the text prompt
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+ # # Define the output components for Gradio (including both image and text)
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+ # outputs = gr.Image(type="numpy", label="Output Image")
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  # Define the text description within an HTML <div> element
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  description_html = """
 
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  description = "This is a project description. It demonstrates how to use Gradio with an image and text input to interact with an API."
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+ import os
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+ examples = [
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+ ["3000.jpeg",'person,car,traffic sign,traffic light'],
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+ ["original (8).jpg", 'person,car,traffic sign,traffic light'],
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+ ["traffic.jpg", 'person,car,traffic sign,traffic light'],
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+ ]
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+
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+
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+
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+
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  # Create a Blocks object and use it as a context manager
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  with gr.Blocks() as demo:
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  gr.Markdown(
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  """
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  # Tuba Autoannotation Demo
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+
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+ This is your private demo for [Tuba Autoannotation](https://Tuba.ai)
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+
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+ A prompt based controllable model for auto annotation
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  """
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  )
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  # Define the input components and add them to the layout
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+
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  with gr.Row():
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  image_input = gr.inputs.Image()
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  output = gr.Image(type="numpy", label="Output Image")
 
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  # Define the event listener that connects the input and output components and triggers the function
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  button.click(fn=get_results, inputs=[image_input, text_input], outputs=output, api_name="get_results")
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  # Add the description below the layout
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+ gr.Examples(
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+ fn=get_results,
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+ examples=examples,
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+ inputs=[image_input, text_input],
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+ outputs=[outputs]
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+ )
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  gr.Markdown(description_html)
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  # Launch the app
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  demo.launch(share=False)