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from fastai.vision.all import *
import gradio as gr
import logging
EXAMPLES_PATH = Path('./examples')
learn = load_learner('watersports.pkl')
categories = learn.dls.vocab
def classify_image(img):
logging.warning('Watch out!!!') # will print a message to the console
print('Classifying: ', img)
pred,idx,probs = learn.predict(img)
return( dict(zip(categories, map(float,probs))))
interface_options = {
"title": "Which Watersport? Compare your guess to the machine inference.",
"description": "Click an image. Click Submit. Click Clear. Other images can be dragged directly from a google search. \nNote, the machine classifier relies purely on vision, of the image pixels - no other info used.",
"examples": [f'{EXAMPLES_PATH}/{f.name}' for f in EXAMPLES_PATH.iterdir()],
"examples_per_page": "100"
}
iface = gr.Interface(fn=classify_image,
inputs=gr.inputs.Image(shape=(192,192)),
outputs=gr.outputs.Label(),
**interface_options)
iface.launch(inline=False)
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