| #__all__=['learn','categories','classify_image','image','label','examples','iface'] | |
| import gradio as gr | |
| from fastai import * | |
| #load_learner is in here | |
| #widget suppressed | |
| from fastai.vision.all import * | |
| learn=load_learner('export.pkl') | |
| categories=('Black','Grizzly','Teddy') | |
| def classify_image(img): | |
| pred,idx,probs=learn.predict(img) | |
| #map needed because output (tensor) is not handled by gradio | |
| return dict(zip(categories,map(float,probs))) | |
| image=gr.inputs.Image(shape=(224,224)) | |
| label = gr.outputs.Label() | |
| examples=['black.jpg','grizzly.jpg','teddy.jpg'] | |
| iface=gr.Interface(fn=classify_image,inputs=image,outputs=label,example=examples) | |
| iface.launch() | |
| #Can be autogenerated from cells preceded by #|export | |
| # Using | |
| #|default_exp <name off the created .py> | |
| #from nbdev.export import notebook2script | |
| #notebook2script('notebookname.ipynb') |