app.py

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

# %% auto 0
__all__ = ['learn', 'categories', 'im_size', 'examples', 'intf', 'classify_image']

#importing
from fastai.vision.all import *
import gradio as gr
import pathlib
plt = platform.system()
if plt == 'Windows': pathlib.WindowsPath = pathlib.PosixPath


# %% ../app.ipynb 4
learn = load_learner('ft_resnet18_10epochs.pkl')

# %% ../app.ipynb 6
categories = ['city','town','countryside','ocean']

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

# %% ../app.ipynb 8
im_size = 192

#image = gr.inputs.Image(shape=(im_size,im_size))
#label = gr.outputs.Label()
examples = ['images/test/035cd8f1-2c9c-45ac-9d67-e0b80043ef22.jpg',
            'images/test/b8f604be-44c2-4ad1-badd-f9c2ed0b2b13.jpg',
            'images/test/92358e88-e4cd-4cd8-87dd-bfa90d0a861e.jpg',
            'images/test/a9614023-dae6-437e-ae88-4677e9035a1d.jpg']

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