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# credit: https://huggingface.co/spaces/jph00/testing/tree/main
# AUTOGENERATED! DO NOT EDIT! File to edit: . (unless otherwise specified).
__all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
# Cell
from fastai.vision.all import *
import gradio as gr
def is_cat(x): return x[0].isupper()
# Cell
learn = load_learner('model.pkl')
# Cell
categories = ('Dog', 'Cat')
def classify_image(img):
pred,idx,probs = learn.predict(img)
if probs[0]>probs[1]:
pred_class = 'This is Dog'
else:
pred_class = 'This is Cat'
return pred_class, dict(zip(categories, map(float,probs)))
# Cell
image = gr.inputs.Image(shape=(192, 192))
set_label = gr.outputs.Textbox(label="Predicted Class")
set_prob = gr.outputs.Label(num_top_classes=2, label="Predicted Probability Per Class")
examples = ['test1.jpg', 'test2.jpg', 'test3.jpeg', 'test4.jpeg', 'test5.jpeg', 'test6.jpeg', 'test7.jpeg', 'test8.jpeg', 'test9.jpeg', 'test10.jpeg']
intf = gr.Interface(fn=classify_image,
inputs=image,
outputs=[set_label, set_prob],
examples_per_page = 2,
examples=examples,
title="CSCI4750/5750 Demo 2: Pet classification",
description= "Click examples below for a quick demo",
theme = 'huggingface',
layout = 'vertical')
intf.launch(inline=False,debug=True) |