# AUTOGENERATED! DO NOT EDIT! File to edit: ../fastai_lesson_2_bearsInference_colab.ipynb.

# %% auto 0
__all__ = ['learn', 'image', 'label', 'examples', 'intf', 'classify_image']

# %% ../fastai_lesson_2_bearsInference_colab.ipynb 1
#Imports

import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

#hide
[ -e /content ] 
pip install -Uqq fastbook

import fastbook
fastbook.setup_book()

#hide
from fastbook import *
from fastai.vision.widgets import *

#pip install fastai

# %% ../fastai_lesson_2_bearsInference_colab.ipynb 3
from fastai.vision.all import *
import gradio as gr

# %% ../fastai_lesson_2_bearsInference_colab.ipynb 12
learn = load_learner('/bearClassifier.pkl')

# %% ../fastai_lesson_2_bearsInference_colab.ipynb 15
def classify_image(img):
  pred,idx,probs = learn.predict(img)
  return dict(zip(categories, map(float,probs)))

# %% ../fastai_lesson_2_bearsInference_colab.ipynb 18
#create gradio interface
image = gr.inputs.Image(shape=(128,128))
label = gr.outputs.Label()
examples = ['grizzlyBearA.jpg', 'blackBearA.jpg', 'teddyBearA.jpg']

intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples )
intf.launch(inline=False)