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

# laod model
learn = load_learner('export.pkl')

# function to classify image
classes = ('Happy human face', 'Sad human face')
def predict(img):
    pred,pred_idx,probs = learn.predict(img)
    return dict(zip(classes, map(float, probs)))

# building gradio interface
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ['computer_vision man.jpg', 'crying.png']

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