Update app.py

app.py

@@ -7,15 +7,6 @@ Original file is located at
     https://colab.research.google.com/drive/1H-R9L74rpYOoQJOnTLLbUpcNpd9Tty_D
 """
 import streamlit as st
-st.markdown("This is a image classification program, please enter the image that you would like to process.")
-st.markdown("Please keep in mind that the dataset is very small (around 100-2000 imgs only")
-path = ['Coretta_Scott_King','Saddam_Hussein','Augustin_Calleri','Peter_Hunt']
-
-select_path = st.selectbox('Which of the three photos would you like to process', options = path)
-st.write("You've select", select_path)
-
-# !wget http://vis-www.cs.umass.edu/lfw/lfw.tgz
-# !tar -xvf /content/lfw.tgz
 import tensorflow as tf
 from sklearn.datasets import load_sample_image
 import os
@@ -26,6 +17,16 @@ import numpy as np
 from PIL import Image
 from sklearn.neighbors import NearestNeighbors
 
+st.markdown("This is a image classification program, please enter the image that you would like to process.")
+st.markdown("Please keep in mind that the dataset is very small (around 100-2000 imgs only")
+path = ['Coretta_Scott_King','Saddam_Hussein','Augustin_Calleri','Peter_Hunt']
+
+select_path = st.selectbox('Which of the three photos would you like to process', options = path)
+st.write("You've select", select_path)
+
+# !wget http://vis-www.cs.umass.edu/lfw/lfw.tgz
+# !tar -xvf /content/lfw.tgz
+
 directory = '/content/lfw'
 model = resnet50.ResNet50(weights='imagenet', include_top=False, pooling='avg')
 feature_dict = {}