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import streamlit as st | |
from fastai.vision.all import * | |
from PIL import Image | |
import pathlib | |
import urllib.request | |
temp = pathlib.PosixPath | |
plt = platform.system() | |
if plt == 'Windows': pathlib.PosixPath = pathlib.WindowsPath | |
# MODEL_URL = "https://drive.google.com/uc?export=download&id=1cH5nY1T5oykEcLyWtjA8Wv-Xn8vO20BS" | |
# urllib.request.urlretrieve(MODEL_URL, "model.pkl") | |
path = Path() | |
path.ls(file_exts='.pkl') | |
learn_inf = load_learner(path/'export.pkl', cpu=True) | |
# out_pl = st.image(load_image(image), width=250) | |
def load_image(img_file): | |
img = PILImage.create(img_file) | |
return img | |
def on_click_classify(image): | |
# load_image(image) | |
out_pl = st.image(load_image(image), width=250) | |
pred, pred_idx, probs = learn_inf.predict(load_image(image)) | |
st.write('Prediction: ', str(pred)[10:], '; Probability: ', float(probs[pred_idx])) | |
st.title('Dog Classifier') | |
st.header('Choose your Dog!!') | |
image = st.file_uploader(label=' ', type=['png', 'jpg'], key='img', help='upload an img of dog') | |
# picture = st.camera_input(label='Click your dog!') | |
# btn_run.on_change(on_click_classify) | |
btn_run = st.button(label='Classify') | |
if btn_run: | |
on_click_classify(image) | |
st.markdown('#### Created by **Umang Kaushik**') | |
st.markdown('##### **[Github](https://github.com/Umang-10)**') | |