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  1. app.py +18 -8
app.py CHANGED
@@ -18,7 +18,6 @@ else:
18
  model = OwlViTForObjectDetection.from_pretrained("google/owlvit-large-patch14").to(device)
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  model.eval()
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  processor = OwlViTProcessor.from_pretrained("google/owlvit-large-patch14")
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- print(os.listdir())
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  def query_image(img, text_queries, score_threshold):
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  text_queries = text_queries.split(",")
@@ -64,11 +63,12 @@ with gr.Blocks() as demo:
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  with gr.Row():
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  with gr.Column():
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- gr.Markdown("""Insert an image above and add text descriptions of what you are looking for.""")
 
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  inputf1 = gr.Image(source="upload")
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  inputf2 = gr.Textbox()
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  gr.Markdown("""
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- \n You can also use the score threshold slider to set a threshold to filter out low probability predictions.
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  """)
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  inputf3 = gr.Slider(0, 1, value=0.1)
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@@ -80,9 +80,13 @@ with gr.Blocks() as demo:
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  with gr.Tab("Capture image with webcam"):
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  with gr.Row():
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  with gr.Column():
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-
 
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  inputweb1 = gr.Image(source="webcam")
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  inputweb2 = gr.Textbox()
 
 
 
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  inputweb3 = gr.Slider(0, 1, value=0.1)
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  inputs_web = [inputweb1, inputweb2, inputweb3]
@@ -90,8 +94,8 @@ with gr.Blocks() as demo:
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  web_output = gr.Image()
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- submit_btn.click(fn=query_image, inputs= inputs_file, outputs = im_output)
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- submit_btn_web.click(fn=query_image, inputs= inputs_web, outputs = web_output)
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  #gr.Markdown("## Image Examples")
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  #examples= [os.path.join(os.path.dirname(__file__), "IMGP0178.jpg")]
@@ -101,5 +105,11 @@ with gr.Blocks() as demo:
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  # outputs=[im_output],
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  # fn=query_image
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  # )
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-
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- demo.launch()
 
 
 
 
 
 
 
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  model = OwlViTForObjectDetection.from_pretrained("google/owlvit-large-patch14").to(device)
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  model.eval()
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  processor = OwlViTProcessor.from_pretrained("google/owlvit-large-patch14")
 
21
 
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  def query_image(img, text_queries, score_threshold):
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  text_queries = text_queries.split(",")
 
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  with gr.Row():
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  with gr.Column():
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+ gr.Markdown("""Insert an image below and add text descriptions of what you are looking for.
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+ If you wish for assistance to find the right text queries you can ask for help from [ChatBRD](https://chatbrd.novonordisk.com/#/) but remember you need to log on novos VPN before you can use it.""")
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  inputf1 = gr.Image(source="upload")
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  inputf2 = gr.Textbox()
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  gr.Markdown("""
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+ \n You can also use the score threshold slider to set a threshold to filter out lower probability predictions.
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  """)
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  inputf3 = gr.Slider(0, 1, value=0.1)
74
 
 
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  with gr.Tab("Capture image with webcam"):
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  with gr.Row():
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  with gr.Column():
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+ gr.Markdown("""Insert an image below and add text descriptions of what you are looking for.
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+ If you wish for assistance to find the right text queries you can ask for help from [ChatBRD](https://chatbrd.novonordisk.com/#/) but remember you need to log on novos VPN before you can use it.""")
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  inputweb1 = gr.Image(source="webcam")
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  inputweb2 = gr.Textbox()
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+ gr.Markdown("""
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+ \n You can also use the score threshold slider to set a threshold to filter out lower probability predictions.
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+ """)
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  inputweb3 = gr.Slider(0, 1, value=0.1)
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  inputs_web = [inputweb1, inputweb2, inputweb3]
 
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  web_output = gr.Image()
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+ submit_btn.click(fn=query_image, inputs= inputs_file, outputs = im_output, queue=True)
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+ submit_btn_web.click(fn=query_image, inputs= inputs_web, outputs = web_output, queue=True)
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100
  #gr.Markdown("## Image Examples")
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  #examples= [os.path.join(os.path.dirname(__file__), "IMGP0178.jpg")]
 
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  # outputs=[im_output],
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  # fn=query_image
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  # )
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+ if __name__ == "__main__":
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+
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+ demo.queue(
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+ concurrency_count=40, # When you increase the concurrency_count parameter in queue(), max_threads() in launch() is automatically increased as well.
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+ max_size=25, # Maximum number of requests that the queue processes
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+ api_open = False # When creating a Gradio demo, you may want to restrict all traffic to happen through the user interface as opposed to the programmatic API that is automatically created for your Gradio demo.
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+ )
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+ demo.launch(auth=("novouser", "bstad2023"))