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from fastai.vision.all import * | |
import gradio as gr | |
# import pathlib | |
# temp = pathlib.PosixPath | |
# pathlib.PosixPath = pathlib.WindowsPath | |
cap_labels = ( | |
'balaclava cap', | |
'baseball cap', | |
'beanie cap', | |
'boater hat', | |
'bowler hat', | |
'bucket hat', | |
'cowboy hat', | |
'fedora cap', | |
'flat cap', | |
'ivy cap', | |
'kepi cap', | |
'newsboy cap', | |
'pork pie hat', | |
'rasta cap', | |
'sun hat', | |
'taqiyah cap', | |
'top hat', | |
'trucker cap', | |
'turban cap', | |
'visor cap' | |
) | |
model = load_learner('models/cap-recognizer-v1.pkl') | |
def recognize_image(image): | |
pred, idx, probs = model.predict(image) | |
return dict(zip(cap_labels, map(float, probs))) | |
image = gr.inputs.Image(shape=(192,192)) | |
label = gr.outputs.Label(num_top_classes=5) | |
examples = [ | |
'unknown_00.jpg', | |
'unknown_01.jpg', | |
'unknown_02.jpg', | |
'unknown_03.jpg' | |
] | |
iface = gr.Interface(fn=recognize_image, inputs=image, outputs=label, examples=examples) | |
iface.launch(inline=False) |