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31 lines
839 B
Python
31 lines
839 B
Python
import gradio as gr
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import pathlib
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current_dir = pathlib.Path(__file__).parent
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images = [str(current_dir / "cheetah1.jpeg"), str(current_dir / "cheetah1.jpg"), str(current_dir / "lion.jpg")]
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img_classifier = gr.load(
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"models/google/vit-base-patch16-224", examples=images, cache_examples=False
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)
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def func(img, text):
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return img_classifier(img), text
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using_img_classifier_as_function = gr.Interface(
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func,
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[gr.Image(type="filepath"), "text"],
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["label", "text"],
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examples=[
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[str(current_dir / "cheetah1.jpeg"), None],
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[str(current_dir / "cheetah1.jpg"), "cheetah"],
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[str(current_dir / "lion.jpg"), "lion"],
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],
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cache_examples=False,
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api_name="predict"
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)
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demo = gr.TabbedInterface([using_img_classifier_as_function, img_classifier])
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if __name__ == "__main__":
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demo.launch()
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