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from fastai.vision.all import * | |
import gradio as gr | |
def is_cat(x): return x[0].isupper() | |
# cell | |
learn = load_learner('model.pkl') | |
# cell | |
categories = ['Cat', 'Dog'] | |
def classify_image(img): | |
pred,idx,probs = learn.predict(img) | |
return dict(zip(categories, map(float, probs))) | |
# cell | |
#image = gr.inputs.image(shape=(192, 192)) | |
#label = gr.outputs.Label() | |
#examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg'] | |
intf = gr.Interface(fn=classify_image, inputs="image", outputs="label") | |
#intf = gr.Interface(fn=classify_image, inputs="image", outputs="label", examples="examples") | |
intf.launch(inline=False) | |
#cell | |
#import gradio as gr | |
#gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True) | |