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from fastai.vision.all import *
import gradio as gr
learn = load_learner('model_convnext_small_in22k_version_1.pkl')
categories = ("fire", "nofire")
def classify_image(img):
pred, idx, prob = learn.predict(img)
return dict(zip(categories, map(float, prob)))
img = gr.inputs.Image(shape=(250, 250))
label = gr.outputs.Label()
gr.Interface(
fn=classify_image,
inputs="image",
outputs="label",
enable_queue=True,
examples=["after-a-bushfire.jpg", "fire_1.jpg", "forest_1.jpg", "sebastian-unrau-sp-p7uuT0tw-unsplash.jpg"],
interpretation='default').launch()