|
|
|
|
|
|
|
__all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf'] |
|
|
|
|
|
from fastai.vision.all import * |
|
import gradio as gr |
|
|
|
def is_cat(x): return x[0].isupper() |
|
|
|
|
|
learn = load_learner('model.pkl') |
|
|
|
|
|
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))) |
|
|
|
|
|
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) |
