from fastai.vision.all import *
import gradio as gr

def is_cat(x): 
    return x[0].isupper()

# Gradio执行一个函数
def classify_image(img):
    pred, idx, probs = learn.predict(img)
    return dict(zip(categories, map(float,probs)))  # 不能处理tensor，转为float

learn = load_learner('model/model.pkl')
categories = ('Dog', 'Cat')
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ['sample/dog.jpg', 'sample/cat.jpg']

# 创建并启动
intf = gr.Interface(fn=classify_image,
                    inputs=image,
                    outputs=label,
                    examples=examples)

intf.launch(inline=False)