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2d5e6d5 7c0e851 ce91d74 2d5e6d5 ce91d74 2d5e6d5 ce91d74 2d5e6d5 ce91d74 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | # AUTOGENERATED! DO NOT EDIT! File to edit: ../app.ipynb.
# %% auto 0
__all__ = ['plt', 'learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image']
# %% ../app.ipynb 2
import sys
import subprocess
subprocess.check_call([sys.executable, '-m', 'pip', 'install', 'gradio==3.50'])
subprocess.check_call([sys.executable, '-m', 'pip', 'install', 'fastai'])
subprocess.check_call([sys.executable, '-m', 'pip', 'install', 'ipywidgets'])
from fastai.vision.all import *
import gradio as gr
import pathlib as pl
plt = platform.system()
def is_cat(x): return x[0].isupper()
# %% ../app.ipynb 4
if plt == 'Linux' : pl.WindowsPath = pl.PosixPath
learn = load_learner('model.pkl')
# %% ../app.ipynb 6
categories = ('Dog', 'Cat')
def classify_image(img):
pred,idx,probs = learn.predict(img)
return dict(zip(categories, map(float,probs)))
# %% ../app.ipynb 8
image = gr.Image(height=192, width = 192)
label = gr.Label()
examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']
intf = gr.Interface(fn=classify_image, inputs = image, outputs=label, examples = examples)
intf.launch(inline=False)
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