Create app.py

app.py

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+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)