from fastai.vision.all import * import gradio as gr import pathlib plt = platform.system() if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath learn = load_learner('export.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))} title = "Bear Classifier" description = "A bear classifier trained on downloaded images of bear dataset with fastai." article="
" exa = [['grizzly.jpg'],['teddy.jpg']] interpretation='default' enable_queue=True gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3), title=title,description=description,article=article,examples=exa, interpretation=interpretation, enable_queue=enable_queue).launch()