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

def label_func(f): return f[0] == 'p'
def acc_camvid(*_): pass
def get_y(*_): pass

learner = load_learner('my_export.pkl')

categories = ('Poison Ivy', 'Not Poison Ivy')


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 = ["pepe.jpg"]



demo = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
demo.launch(inline=False)