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from fastai.vision.all import load_learner
import gradio as gr
cap_labels = cap_labels = {
'baseball cap',
'beanie cap',
'fedora cap',
'cowboy hat',
'kepi cap',
'flat cap',
'trucker cap',
# 'newsboy cap'
'pork pie hat',
'bowler hat',
'top hat',
'sun hat',
'boater hat',
# 'ivy cap',
'bucket hat',
'balaclava cap',
'turban cap',
'taqiyah cap',
'rasta cap',
'visor cap'
}
version = 1
model_path = f"cap-recognizer-v{version}.pkl"
model = load_learner(model_path)
def recognize_image(image):
pred, idx, probs = model.predict(image)
return dict(zip(sorted(cap_labels), map(float, probs)))
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = [
'test_images/test_0.jpg',
'test_images/test_1.jpg',
'test_images/test_2.jpg',
'test_images/test_3.jpg',
'test_images/test_4.jpg',
'test_images/test_5.jpg']
iface = gr.Interface(fn=recognize_image, inputs=image, outputs=label, examples=examples)
iface.launch(inline=False) |