| __all__ = ['classify_image', 'image', 'label', 'example', 'intf', 'cat', 'learn', 'fastbook'] | |
| from fastai.vision.widgets import * | |
| from fastcore.all import * | |
| from fastbook import * | |
| from fastai.vision.widgets import * | |
| import fastbook | |
| import gradio as gr | |
| fastbook.setup_book() | |
| from fastai import * | |
| import pathlib | |
| plt = platform.system() | |
| if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath | |
| mod = Path('car_model.pkl') | |
| learn = load_learner(mod) | |
| cat = ('sedan', 'suv') | |
| def classify_image(img): | |
| pred,idx,probs= learn.predict(img) | |
| return dict(zip(cat, map(float, probs))) | |
| image = gr.inputs.Image(shape=(200,200)) | |
| label = gr.components.Label() | |
| example = ['sedan.jpg','suv.jpg'] | |
| intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=example) | |
| intf.launch(inline=False) | |