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__all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
# Cell
from fastai.vision.all import *
import gradio as gr
def is_cat(x):
return x[0].isupper()
# img = PILImage.create('dog.jpg')
# img.thumbnail((192, 192))
# img
# Cell
learn = load_learner('model.pkl')
# learn.predict(img)
# Cell
categories = ('Dog', 'Cat')
def classify_image(img):
pred, idx, probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
# classify_image(img)
# Cell
image = gr.Image(height=192, width=192)
label = gr.Label()
examples = ['dog.jpg', 'cat.jpg', 'rabbit.jpg']
intf = gr.Interface(fn= classify_image, inputs = image, outputs = label, examples = examples)
intf.launch(inline = False, share = True) |