app.py

# AUTOGENERATED! DO NOT EDIT! File to edit: ../methane-plume-classification-yes-or-no.ipynb.

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

# %% ../methane-plume-classification-yes-or-no.ipynb 2
import warnings
warnings.filterwarnings('ignore')

# %% ../methane-plume-classification-yes-or-no.ipynb 3
import pathlib
temp = pathlib.PosixPath
pathlib.PosixPath = pathlib.WindowsPath

# %% ../methane-plume-classification-yes-or-no.ipynb 4
import fastbook
import pandas as pd
import numpy as np
import os 

from fastbook import *
from fastai.vision.widgets import *
import gradio as gr

# %% ../methane-plume-classification-yes-or-no.ipynb 20
categories = ('No Plume', 'Plume')

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

# %% ../methane-plume-classification-yes-or-no.ipynb 22
image = gr.inputs.Image(shape = (152, 152))
label = gr.outputs.Label()
examples = ['plume1.png', 'plume2.png', 'noplume1.png', 'noplume2.png']

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