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import streamlit as st | |
import pandas as pd | |
from fastai import * | |
from fastai.vision.all import * | |
import pickle | |
import pathlib | |
header = st.container() | |
inference = st.container() | |
with header: | |
st.title("Cuisine Classifier") | |
st.text("Is your food Italian, French, Chinese, Indian, or Japanese?") | |
with inference: | |
plt = platform.system() | |
if plt == 'Linux': | |
pathlib.WindowsPath = pathlib.PosixPath | |
if plt == 'Windows': | |
pathlib.PosixPath = pathlib.WindowsPath | |
path = Path() | |
path.ls(file_exts='.pkl') | |
learn_inf = load_learner(path/'export.pkl') | |
st.header('Show me your food pic!') | |
st.text("(I currently accept Italian, French, Chinese, Indian, or Japanese. Otherwise, I guesss wildly!)") | |
uploaded_file = st.file_uploader("Show me your food pic!") | |
if uploaded_file is not None: | |
img = load_image(uploaded_file) | |
#img = PILImage.create(uploaded_file) | |
pred, pred_idx, probs = learn_inf.predict(img) | |
prob_value = probs[pred_idx].item() | |
rounded_prob_percentage = round(prob_value * 100) | |
st.text(f"This is {pred}, isn't it? Believe me, I am {rounded_prob_percentage}% sure!") |