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from turtle import title |
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import gradio as gr |
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from transformers import pipeline |
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import numpy as np |
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from PIL import Image |
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pipes = { |
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"ViT/B-16": pipeline("zero-shot-image-classification", model="OFA-Sys/chinese-clip-vit-base-patch16") |
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} |
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inputs = [ |
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gr.inputs.Image(type='pil', |
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label="Image 输入图片"), |
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gr.inputs.Textbox(lines=1, |
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label="Candidate Labels 候选分类标签"), |
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gr.inputs.Radio(choices=["ViT/B-16"], type="value", default="ViT/B-16", label="Model 模型规模"), |
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gr.inputs.Textbox(lines=1, label="Prompt Template Prompt模板 ({}指代候选标签)", default="一张{}的图片。"), |
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] |
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images="festival.jpg" |
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def shot(image, labels_text, model_name, hypothesis_template): |
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labels = [label.strip(" ") for label in labels_text.strip(" ").split(",")] |
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res = pipes[model_name](images=image, |
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candidate_labels=labels, |
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hypothesis_template=hypothesis_template) |
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return {dic["label"]: dic["score"] for dic in res} |
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iface = gr.Interface(shot, |
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inputs, |
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"label", |
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examples=[["festival.jpg", "灯笼, 鞭炮, 对联", "ViT/B-16", "一张{}的图片。"]], |
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description="""To play with this demo, add a picture and a list of labels in Chinese separated by commas. 上传图片,并输入多个分类标签,用英文逗号分隔。可点击页面最下方示例参考。""", |
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title="Zero-shot Image Classification (中文零样本图像分类)") |
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iface.launch() |