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import gradio as gr |
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title="Swin Transformer" |
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description="Gradio Demo for Swin Transformer: Hierarchical Vision Transformer using Shifted Windows. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below." |
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2103.14030' target='_blank'>Swin Transformer: Hierarchical Vision Transformer using Shifted Windows</a> | <a href='https://github.com/microsoft/Swin-Transformer' target='_blank'>Github Repo</a></p>" |
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io1 = gr.Interface.load("huggingface/microsoft/swin-large-patch4-window12-384-in22k") |
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def inference(image, model): |
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if model == "swin-large-patch4-window12-384-in22k": |
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outtext = io1(image) |
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else: |
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outtext = io2(image) |
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return outtext |
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examples=[['tiger.jpeg','swin-large-patch4-window12-384-in22k']] |
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gr.Interface( |
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inference, |
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[gr.inputs.Image(label="Input Image",type='filepath'),gr.inputs.Dropdown(choices=["swin-large-patch4-window12-384-in22k"], type="value", default="swin-large-patch4-window12-384-in22k", label="model") |
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], |
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gr.outputs.Label(label="Classification"), |
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examples=examples, |
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article=article, |
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title=title, |
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description=description).launch(enable_queue=True,cache_examples=True) |