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from fastai.vision.all import *
import gradio as gr
def is_cat(x): return x[0].isupper()
learn = load_learner('model.pkl')
categories = ('Dog', 'Cat')
def classify_image(img):
pred,idx,probs = learn.predict(img)
return dict(zip(categories, map(float,probs)))
demo = gr.Interface(
fn=classify_image,
inputs=gr.Image(type="pil"), # Image uploader
#outputs=gr.Textbox(label="Classification Result"), # Textbox for the output
outputs=gr.Label(label="Classification Result"), # Bar chart and label for the output
examples=['dog.jpg', 'cat.jpg', 'dunno.jpg'] # Example images
)
demo.launch(inline=False,share=True) |