wendys-llc commited on
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2ee2100
1 Parent(s): 1c2d63b

Update app.py

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  1. app.py +2 -10
app.py CHANGED
@@ -50,17 +50,9 @@ def query_image(img, text_queries, score_threshold):
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  description = """
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- Gradio demo for <a href="https://huggingface.co/docs/transformers/main/en/model_doc/owlvit">OWL-ViT</a>,
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- introduced in <a href="https://arxiv.org/abs/2205.06230">Simple Open-Vocabulary Object Detection
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- with Vision Transformers</a>.
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- \n\nYou can use OWL-ViT to query images with text descriptions of any object.
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  To use it, simply upload an image and enter comma separated text descriptions of objects you want to query the image for. You
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- 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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- \n\nOWL-ViT is trained on text templates,
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- hence you can get better predictions by querying the image with text templates used in training the original model: *"photo of a star-spangled banner"*,
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- *"image of a shoe"*. Refer to the <a href="https://arxiv.org/abs/2103.00020">CLIP</a> paper to see the full list of text templates used to augment the training data.
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- \n\n<a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/zeroshot_object_detection_with_owlvit.ipynb">Colab demo</a>
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  """
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  demo = gr.Interface(
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  query_image,
 
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  description = """
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+ You can use OWL-ViT to query images with text descriptions of any object.
 
 
 
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  To use it, simply upload an image and enter comma separated text descriptions of objects you want to query the image for. You
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+ can also use the score threshold slider to set a threshold to filter out low probability predictions. <a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/zeroshot_object_detection_with_owlvit.ipynb">Colab demo</a>
 
 
 
 
 
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  """
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  demo = gr.Interface(
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  query_image,