PDLLesson2 / app.py
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#!/usr/bin/env python
# coding: utf-8
# ! [ -e /content ] && pip install -Uqq fastbook
import fastbook
fastbook.setup_book()
#hide
from fastbook import *
from fastai.vision.widgets import *
import gradio as gr
#import pathlib
#temp = pathlib.PosixPath
#pathlib.PosixPath = pathlib.WindowsPath
def is_cat(x): return x[0].isupper() # Presquite code for the model to run
learn_inf = load_learner('model.pkl')
learn_inf.dls.vocab # Reminds us of the categories
categories = learn_inf.dls.vocab
def classify_image(img):
pred, idx, probs = learn_inf.predict(img)
return dict(zip(categories, map(float,probs)))
image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = ["Example 1.jpeg","Example 2.jpeg"]
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False)