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from turtle import title
import gradio as gr
from transformers import pipeline
import numpy as np
from PIL import Image

pipes = {
    "ViT/B-16": pipeline("zero-shot-image-classification", model="OFA-Sys/chinese-clip-vit-base-patch16")
}

inputs = [
    gr.inputs.Image(type='pil', 
                    label="Image 输入图片"),
    gr.inputs.Textbox(lines=1, 
                      label="Candidate Labels 候选分类标签"),
    gr.inputs.Radio(choices=["ViT/B-16"], type="value", default="ViT/B-16", label="Model 模型规模"), 
    gr.inputs.Textbox(lines=1, label="Prompt Template Prompt模板 ({}指代候选标签)", default="一张{}的图片。"),
]
images="festival.jpg"

def shot(image, labels_text, model_name, hypothesis_template):
    labels = [label.strip(" ") for label in labels_text.strip(" ").split(",")]
    res = pipes[model_name](images=image, 
           candidate_labels=labels,
           hypothesis_template=hypothesis_template)
    return {dic["label"]: dic["score"] for dic in res}

iface = gr.Interface(shot, 
            inputs, 
            "label", 
            examples=[["festival.jpg", "灯笼, 鞭炮, 对联", "ViT/B-16", "一张{}的图片。"]],
            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。""",
            title="Zero-shot Image Classification (中文零样本图像分类)")

iface.launch()