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# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
# %% auto 0
__all__ = ['learn', 'categories', 'train_csv', 'n_inp', 'image', 'label', 'examples', 'iface', 'label_func', 'classify_image']
# %% app.ipynb 1
import gradio as gr
from fastai.vision.all import *
from fastai.data.all import *
def label_func(item):
rel_path = str(item.relative_to('dataset/train'))
return train_csv[train_csv['image_ID']==rel_path]["label"].values[0]
# %% app.ipynb 2
learn = load_learner('model.pkl')
# %% app.ipynb 3
categories = ('Badminton', 'Cricket', 'Karate', 'Soccer', 'Swimming', 'Tennis', 'Wrestling')
# %% app.ipynb 5
def classify_image(img):
pred, idx, probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
# %% app.ipynb 6
image = gr.Image(height=224, width=224)
label = gr.Label()
examples = ['Badminton.jpg', 'Cricket.jpg', 'Karate.jpg', 'Soccer.jpg', 'Swimming.jpg', 'Tennis.jpg', 'Wrestling.jpg']
# %% app.ipynb 7
iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
iface.launch(inline=False)
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