| import os |
| import streamlit as st |
| from PIL import Image |
|
|
| from inference import get_result_images |
|
|
| human_image_names = sorted([fn[:-4] for fn in os.listdir('dataset/test_img')]) |
|
|
| if st.sidebar.checkbox('Upload'): |
| human_file = st.sidebar.file_uploader("Upload a Human Image", type=["png", "jpg", "jpeg"]) |
| if human_file is None: |
| human_file = 'dataset/test_img/default.png' |
| else: |
| human_image_name = st.sidebar.selectbox("Choose a Human Image", human_image_names) |
| human_file = f'dataset/test_img/{human_image_name}.png' |
| if not os.path.exists(human_file): |
| human_file = human_file.replace('.png', '.jpg') |
| st.warning("Upload a Human Image in the sidebar for Virtual-Try-On") |
|
|
| human = Image.open(human_file) |
| human.save('dataset/test_img/input.png') |
| st.sidebar.image(human, width=300) |
|
|
| result_images = get_result_images() |
| st.image(result_images, width=600) |
