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from fastai.vision.all import *
import gradio as gr
# import pathlib
# temp = pathlib.PosixPath
# pathlib.PosixPath = pathlib.WindowsPath
model = load_learner('models/sport-recognizer-v3.pkl')
equipment_labels = model.dls.vocab
def recognize_image(image):
pred, idx, probs = model.predict(image)
return dict(zip(equipment_labels, map(float, probs)))
#!export
image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label(num_top_classes=5)
examples = [
'test_images/unknown_00.jpg',
'test_images/unknown_01.jpg',
'test_images/unknown_02.jpg',
'test_images/unknown_03.jpg',
'test_images/unknown_04.jpg',
'test_images/unknown_05.jpg'
]
iface = gr.Interface(fn=recognize_image, inputs=image, outputs=label, examples=examples)
iface.launch(inline=False, share=True) |