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from fastai.vision.all import *
import gradio as gr
# from fastbook import *
# from fastdownload import download_url
# def greet(name):
# return "Hello " + name + "!!"
# iface = gr.Interface(fn=greet, inputs="text", outputs="text")
# iface.launch()
def is_cat(x): return x[0].isupper()
learn = load_learner("model.pkl")
categories = ('Dog', '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()
example = ['cat.jpg', 'dog.jpg']
intr = gr.Interface(fn = classify_image, inputs=image, outputs=label, examples=example)
intr.launch(inline=False) |