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import gradio as gr
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from PIL import Image
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from transformers import BeitImageProcessor, BeitForImageClassification
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from PIL import Image
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def inference(img):
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return model.config.id2label[predicted_class_idx]
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title = "beit-base-patch16-224-pt22k-ft22k"
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title = "Image classification:beit-base-patch16-224-pt22k-ft22k"
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description = "Gradio Demo for beit-base-patch16-224-pt22k-ft22k. To use it, simply upload your image, or click one of the examples to load them."
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article = "<p style='text-align: center'><a href='https://github.com/bryandlee/animegan2-pytorch' target='_blank'>Github Repo Pytorch</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_animegan' alt='visitor badge'></center></p>"
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examples=[['example_cat.jpg'],['Masahiro.png']]
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img,output,flag,username,timestamp
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D:\workspace\py\image_classification\beit_base_patch16_224_pt22k_ft22k\flagged\img\tmpcm8vuiq9.png,,,,2023-03-30 10:03:06.225359
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D:\workspace\py\image_classification\beit_base_patch16_224_pt22k_ft22k\flagged\img\tmpbfwv5bbb.png,,,,2023-03-30 10:03:08.489673
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D:\workspace\py\image_classification\beit_base_patch16_224_pt22k_ft22k\flagged\img\tmp4d3jvm17.jpg,,,,2023-03-30 10:03:11.483544
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