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from fastai.vision.all import *
import gradio as gr
#def is_cat(x): return x[0].isupper()
# Cell
learn = load_learner('persimmon_model.pkl')
# Cell
categories = ('persimmon', 'tomato')
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 = ['persimmon.jpg', 'tomato.jpg', 'persimmontree.jpg',
'tomatoplant.jpg', 'cat.jpg', 'tomatoplant2.jpg']
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples,
title="Persimmon or Tomato?", description="Trained on only persimmon and tomato images auto-retrieved from a DDG search using resnet18. Provide an image or select from one below.")
intf.launch(inline=False)
#def greet(name):
# return "Howdy " + name + "!!"
#iface = gr.Interface(fn=greet, inputs="text", outputs="text")
#iface.launch()
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