# AUTOGENERATED! DO NOT EDIT! File to edit: ../drive/MyDrive/Colab Notebooks/room classifier to app.ipynb.

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

# %% ../drive/MyDrive/Colab Notebooks/room classifier to app.ipynb 2
import platform

import fastbook
import fastai
from fastai.vision.widgets import *
from fastai.callback.preds import load_learner
from fastai.vision.all import *

fastbook.setup_book()

# %% ../drive/MyDrive/Colab Notebooks/room classifier to app.ipynb 3
if platform.system().lower() == "windows":
    import pathlib
    posix_path = pathlib.PosixPath
    pathlib.PosixPath = pathlib.WindowsPath
learner = load_learner("room_classifier.pk1")
if platform.system().lower() == "windows":
    pathlib.PosixPath = posix_path


# %% ../drive/MyDrive/Colab Notebooks/room classifier to app.ipynb 14
def classify_image(img):
    pred, idx, probs = learner.predict(img)
    return dict(zip(learner.dls.vocab, map(float, probs)))



# %% ../drive/MyDrive/Colab Notebooks/room classifier to app.ipynb 16
import gradio as gr

image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
out_pl = widgets.Output()

examples = ["examples/test_bathroom.jfif", "examples/test_living_room.jfif", "examples/test_building.jfif"]
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch()