| import gradio as gr | |
| from fastai.vision.all import * | |
| import pathlib | |
| plt = platform.system() | |
| if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath | |
| learn = load_learner('model.pkl') | |
| categories = ('Flower','Sunflower') | |
| def classify(img): | |
| pred,_,probs = learn.predict(img) | |
| return dict(zip(categories, map(float,probs))) | |
| image = gr.inputs.Image(shape=(192,192)) | |
| label = gr.outputs.Label() | |
| examples = ['images/0.png','images/1.png','images/2.png','images/3.png','images/4.png','images/5.png','images/6.png','images/7.png','images/8.png','images/9.png'] | |
| iface = gr.Interface(fn=classify, inputs=image, outputs=label, examples=examples) | |
| iface.launch() |