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| import streamlit as st | |
| from PIL import Image | |
| import torch | |
| from model import ModelColorization | |
| from utils import process_gs_image, inverse_transform_cs | |
| # create the model | |
| model = ModelColorization().from_pretrained("sebastiansarasti/AutoEncoderImageColorization") | |
| # create the streamlit app | |
| st.title("Image Colorization App") | |
| st.write("This is an app to colorize black and white images.") | |
| # create a botton to upload the image | |
| uploaded_file = st.file_uploader("Choose an image...", type="jpg") | |
| # check if the image is uploaded | |
| if uploaded_file is not None: | |
| # display the image | |
| image = Image.open(uploaded_file) | |
| st.image(image, caption="Uploaded Image.", use_container_width=True) | |
| # create a button to colorize the image | |
| if st.button("Colorize"): | |
| # process the grayscale image | |
| image, original_size = process_gs_image(image) | |
| # run the model | |
| model.eval() | |
| with torch.no_grad(): | |
| result = model(image) | |
| # colorize the image | |
| colorized_image = inverse_transform_cs(result.squeeze(0), original_size) | |
| # display the colorized image | |
| st.image(colorized_image, caption="Colorized Image.", use_container_width=True) |