Spaces:
Runtime error
Runtime error
File size: 2,728 Bytes
7faf1c4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 |
import os
import streamlit as st
from PIL import Image
from inference import get_predictions
st.title('Person characteristic prediction Demo')
sample_files = os.listdir('./data/sample_images')
tot_index = len(sample_files)
sample_path = './data/sample_images'
if 'image_index' not in st.session_state:
st.session_state['image_index'] = 4
if 'which_button' not in st.session_state:
st.session_state['which_button'] = 'sample_button'
stream_col, upload_col, sample_col = st.tabs(['Take picture', 'Upload file', 'Select from sample images'])
with stream_col:
picture = st.camera_input("Take a picture")
if picture is not None:
captured_img = Image.open(picture)
st.image(captured_img, caption='Captured Image')
use_captured_image = st.button('Use this captured image')
if use_captured_image is True:
st.session_state['which_button'] = 'captured_button'
with upload_col:
uploaded_file = st.file_uploader("Select a picture from your computer(png/jpg) :", type=['png', 'jpg', 'jpeg'])
if uploaded_file is not None:
img = Image.open(uploaded_file)
st.image(img, caption='Uploaded Image')
use_uploaded_image = st.button("Use uploaded image")
if use_uploaded_image is True:
st.session_state['which_button'] = 'upload_button'
with sample_col:
st.write("Select one from these available samples: ")
current_index = st.session_state['image_index']
current_image = Image.open(os.path.join(sample_path, sample_files[current_index]))
# next = st.button('next_image')
prev_button, next_button = st.columns(2)
with prev_button:
prev = st.button('prev_image')
with next_button:
next = st.button('next_image')
if prev:
current_index = (current_index - 1) % tot_index
if next:
current_index = (current_index + 1) % tot_index
st.session_state['image_index'] = current_index
sample_image = Image.open(os.path.join(sample_path, sample_files[current_index]))
st.image(sample_image, caption='Chosen image')
use_sample_image = st.button("Use this Sample")
if use_sample_image is True:
st.session_state['which_button'] = 'sample_button'
predict_clicked = st.button("Get prediction")
if predict_clicked:
which_button = st.session_state['which_button']
if which_button == 'sample_button':
predictions = get_predictions(sample_image)
elif which_button == 'upload_button':
predictions = get_predictions(img)
elif which_button == 'captured_button':
predictions = get_predictions(captured_img)
st.markdown('**The model predictions along with their probabilities are :**')
st.table(predictions)
|