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from fastai.vision.all import * | |
learn = load_learner('export.pkl') | |
# searches = 'steve minecraft','herobrine minecraft' | |
def sanity_check(): | |
for o in searches: | |
category,_,probs = learn.predict(PILImage.create(f'{o}.jpg')) | |
print(f"This is a: {category}.") | |
print(f"Probability it's a {category}: {probs[0]:.4f}") | |
# sanity_check() | |
labels = learn.dls.vocab | |
def predict(img): | |
img = PILImage.create(img) | |
pred, pred_idx, probs = learn.predict(img) | |
return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
import os | |
os.system("pip install --upgrade --force-reinstall gradio==3.50") | |
import gradio as gr | |
gr.Interface( | |
fn=predict, | |
inputs=gr.inputs.Image(shape=(512, 512)), | |
examples = [ 'steve minecraft.jpg', 'herobrine minecraft.jpg' ], | |
interpertation='default', | |
outputs=gr.outputs.Label(num_top_classes=3) | |
).launch(share=True) | |