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from fastbook import *
from fastai.vision.widgets import *
from fastai.vision.all import *
import gradio as gr
import pathlib
plt = platform.system()
if plt == 'Linux':
pathlib.WindowsPath = pathlib.PosixPath
learn = load_learner("model.pkl")
categories = ("Cat", "Dog")
def classify_img(img):
pred, idx, probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ['dog0.jpg', 'dog1.jpg', 'dog2.jpg', 'dog3.jpg', 'dog4.jpg', 'dog5.jpg', 'dog6.jpg', 'dog7.jpg', 'dog8.jpg', 'dog9.jpg', 'cat1.jpg', 'cat2.jpg', 'cat3.jpg', 'cat4.jpg', 'cat5.jpg', 'cat6.jpg', 'cat7.jpg', 'cat8.jpg', 'cat9.jpg']
iface = gr.Interface(fn=classify_img, inputs=image, outputs=label, examples=examples)
iface.launch(inline=False) |