|
__all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf'] |
|
|
|
|
|
import fastai |
|
from fastai.vision.all import * |
|
import gradio as gr |
|
|
|
def is_cat(x): return x[0].isupper() |
|
|
|
|
|
learn = load_learner('model.pkl') |
|
|
|
|
|
categories = ('Dog', 'Cat') |
|
|
|
def classify_image(img): |
|
pred,idx,probs = learn.predict(img) |
|
return dict(zip(categories, map(float,probs))) |
|
|
|
|
|
image = gr.inputs.Image(shape=(192, 192)) |
|
label = gr.outputs.Label() |
|
examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg'] |
|
|
|
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) |
|
intf.launch(inline=False) |