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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) |