CameraTrap / Image_Classification.py
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Create Image_Classification.py
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learn = load_learner('CameraTrap_model.pkl')
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 gradio as gr
gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=2)).launch(share=True)