from fastai.vision.all import * import gradio as gr import os from pathlib import Path import pathlib def is_cat(x): return x[0].isupper() temp = pathlib.PosixPath pathlib.PosixPath = pathlib.WindowsPath path = Path(os.path.dirname(os.path.abspath(__file__))) model_path = path / 'model.pkl' # Construct the Windows-style path learn = load_learner(model_path) categories = ('Dog', 'Cat') def classify_image(img): pred, idx, probs = learn.predict(img) return dict(zip(categories, map(float, probs))) input_component = gr.components.Image(shape=(192,192)) output_component = gr.components.Label() example = ['dog.jpg'] intf = gr.Interface(fn=classify_image, inputs=input_component, outputs=output_component, examples=example) intf.launch(share=True)