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

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

# cell
learn = load_learner('model2.pkl')

# cell
categories = ['Dog', 'Cat']

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

# cell

#image = gr.inputs.image(shape=(192, 192))
#label = gr.outputs.Label()
#examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']

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

#cell
#import gradio as gr
#gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)