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from fastai.vision.all import *
import gradio as gr
# Import trained model
learn = load_learner("model.pkl")
# Define an object with labels (keys) and tensors (values)
categories = {"Dog", "Cat"}
def classify_image(img):
pred,_,probs = learn.predict(img)
return dict(zip(categories, map(float,probs)))
# Build the Gradio interface
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ["examples/max.jpg", "examples/nymo.jpg"]
intf = gr.Interface(
fn=classify_image,
inputs=image,
outputs=label,
examples=examples
)
# Start the server
intf.launch(inline=False) |