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

def greet(name):
    return "Hello " + name + "!!"

learn = load_learner("model.pkl");

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


categories = {"No_Cat","Cat"}
def classify_image(img):
    pred,idx,probs = learn.predict(img)
    return dict(zip(categories, map(float,probs)))

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = ["WX20240713-091831@2x.png","WX20240713-091821@2x.png","WX20240713-091430@2x.png","WX20240713-090252@2x.png"]
intf = gr.Interface(fn=classify_image,inputs = image,outputs = label,examples = examples)
intf.launch(inline=False)


demo = gr.Interface(fn=greet, inputs="text", outputs="text")
demo.launch()