# %%
#|export
from fastai.vision.all import *
import gradio as gr

def is_bird(x): return x[0].isupper()

# %%
im = PILImage.create('dog.jpeg')
im.thumbnail((192,192))
im

# %%
##temp = pathlib.PosixPath
#pathlib.PosixPath = pathlib.WindowsPath

# %%
#|export
learn = load_learner('birdclassifiermodel.pkl')

# %%
learn.predict(im)

# %%
#|export
categories = ('bird','not a bird')

def classify_image(img):
    pred,idx,probs = learn.predict(img)
    return dict(zip(categories, map(float,probs)))


# %%
classify_image(im)

# %%
#|export
image = gr.inputs.Image(shape =(192,192))
label = gr.outputs.Label()
examples = ['dog.jpeg','bird1.jpg', 'bird2.jpg', 'forest1.jpg', 'forest2.jpg']

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

# %%


# %% [markdown]
#