Ryu-m0m commited on
Commit
be0aedc
1 Parent(s): baf85d9

update path

Browse files
Files changed (1) hide show
  1. app.py +4 -7
app.py CHANGED
@@ -1,15 +1,9 @@
1
  import streamlit as st
2
  import pandas as pd
3
- from io import StringIO
4
  from fastai import *
5
  from fastai.vision.all import *
6
- import bz2file as bz2
7
  import pickle
8
 
9
- import pathlib
10
- plt = platform.system()
11
- if plt == 'Windows': pathlib.WindowsPath = pathlib.PosixPath
12
-
13
  header = st.container()
14
  inference = st.container()
15
 
@@ -18,14 +12,17 @@ with header:
18
  st.text("Is your food Italian, French, Chinese, Indian, or Japanese?")
19
 
20
  with inference:
 
 
21
 
22
- learn_inf = load_learner('export.pkl')
23
 
24
  st.header('Show me your food pic!')
25
  st.text("(I currently accept Italian, French, Chinese, Indian, or Japanese. Otherwise, I guesss wildly!)")
26
  uploaded_file = st.file_uploader("Show me your food pic!")
27
  if uploaded_file is not None:
28
  img = load_image(uploaded_file)
 
29
  pred, pred_idx, probs = learn_inf.predict(img)
30
  prob_value = probs[pred_idx].item()
31
  rounded_prob_percentage = round(prob_value * 100)
 
1
  import streamlit as st
2
  import pandas as pd
 
3
  from fastai import *
4
  from fastai.vision.all import *
 
5
  import pickle
6
 
 
 
 
 
7
  header = st.container()
8
  inference = st.container()
9
 
 
12
  st.text("Is your food Italian, French, Chinese, Indian, or Japanese?")
13
 
14
  with inference:
15
+ path = Path()
16
+ path.ls(file_exts='.pkl')
17
 
18
+ learn_inf = load_learner(path/'export.pkl')
19
 
20
  st.header('Show me your food pic!')
21
  st.text("(I currently accept Italian, French, Chinese, Indian, or Japanese. Otherwise, I guesss wildly!)")
22
  uploaded_file = st.file_uploader("Show me your food pic!")
23
  if uploaded_file is not None:
24
  img = load_image(uploaded_file)
25
+ #img = PILImage.create(uploaded_file)
26
  pred, pred_idx, probs = learn_inf.predict(img)
27
  prob_value = probs[pred_idx].item()
28
  rounded_prob_percentage = round(prob_value * 100)