Spaces:
Runtime error
Runtime error
| import io | |
| import streamlit as st | |
| from model import * | |
| # # TODO: | |
| # - Reformat the model introduction | |
| # - Make the iterative text generation | |
| def gen_show_caption(sub_prompt=None, cap_prompt=""): | |
| with st.spinner("Generating Caption"): | |
| subreddit, caption = virtexModel.predict( | |
| image_dict, sub_prompt=sub_prompt, prompt=cap_prompt | |
| ) | |
| st.markdown( | |
| f""" | |
| <style> | |
| red{{ | |
| color:#c62828 | |
| }} | |
| blue{{ | |
| color:#2a72d5 | |
| }} | |
| mono{{ | |
| font-family: "Inconsolata"; | |
| }} | |
| </style> | |
| ### <red> r/{subreddit} </red> <blue> {cap_prompt} </blue> {caption} | |
| """, | |
| unsafe_allow_html=True, | |
| ) | |
| _, center, _ = st.columns([1, 8, 1]) | |
| with center: | |
| st.title("Image Captioning Demo from RedCaps") | |
| st.sidebar.markdown( | |
| """ | |
| ### Image Captioning Model from VirTex trained on RedCaps | |
| Use this page to caption your own images or try out some of our samples. | |
| You can also generate captions as if they are from specific subreddits, | |
| as if they start with a particular prompt, or even both. | |
| Share your results on twitter with #redcaps or with a friend*. | |
| """ | |
| ) | |
| # st.markdown(footer,unsafe_allow_html=True) | |
| with st.spinner("Loading Model"): | |
| virtexModel, imageLoader, sample_images, valid_subs = create_objects() | |
| select_idx = None | |
| st.sidebar.title("Select a sample image") | |
| if st.sidebar.button("Random Sample Image"): | |
| select_idx = get_rand_idx(sample_images) | |
| sample_image = sample_images[0 if select_idx is None else select_idx] | |
| uploaded_image = None | |
| # with st.sidebar.form("file-uploader-form", clear_on_submit=True): | |
| uploaded_file = st.sidebar.file_uploader("Choose a file") | |
| # submitted = st.form_submit_button("Submit") | |
| if uploaded_file is not None: # and submitted: | |
| uploaded_image = Image.open(io.BytesIO(uploaded_file.getvalue())) | |
| select_idx = None # set this to help rewrite the cache | |
| # class OnChange(): | |
| # def __init__(self, idx): | |
| # self.idx = idx | |
| # def __call__(self): | |
| # st.write(f"the idx is: {self.idx}") | |
| # st.write(f"the sample_image is {sample_image}") | |
| # sample_image = st.sidebar.selectbox( | |
| # "", | |
| # sample_images, | |
| # index = 0 if select_idx is None else select_idx, | |
| # on_change=OnChange(0 if select_idx is None else select_idx) | |
| # ) | |
| st.sidebar.title("Select a Subreddit") | |
| sub = st.sidebar.selectbox( | |
| "Type below to condition on a subreddit. Select None for a predicted subreddit", | |
| valid_subs, | |
| ) | |
| st.sidebar.title("Write a Custom Prompt") | |
| cap_prompt = st.sidebar.text_input("Write the start of your caption below", value="") | |
| _ = st.sidebar.button("Regenerate Caption") | |
| st.sidebar.write("Advanced Options:") | |
| num_captions = st.sidebar.select_slider( | |
| "Number of Captions to Predict", options=[1, 2, 3, 4, 5], value=1 | |
| ) | |
| nuc_size = st.sidebar.slider( | |
| "Nucelus Size:\nLarger values lead to more diverse captions", | |
| min_value=0.0, | |
| max_value=1.0, | |
| value=0.8, | |
| step=0.05, | |
| ) | |
| virtexModel.model.decoder.nucleus_size = nuc_size | |
| image_file = sample_image | |
| # LOAD AND CACHE THE IMAGE | |
| if uploaded_image is not None: | |
| image = uploaded_image | |
| elif select_idx is None and "image" in st.session_state: | |
| image = st.session_state["image"] | |
| else: | |
| image = Image.open(image_file) | |
| image = image.convert("RGB") | |
| st.session_state["image"] = image | |
| image_dict = imageLoader.transform(image) | |
| show_image = imageLoader.show_resize(image) | |
| with center: | |
| show = st.image(show_image) | |
| show.image(show_image) | |
| if sub is None and imageLoader.text_transform(cap_prompt) is not "": | |
| st.write("Without a specified subreddit we default to /r/pics") | |
| for i in range(num_captions): | |
| gen_show_caption(sub, imageLoader.text_transform(cap_prompt)) | |
| st.sidebar.markdown( | |
| """ | |
| *Please note that this model was explicitly not trained on images of people, and as a result is not designed to caption images with humans. | |
| This demo accompanies our paper RedCaps. | |
| Created by Karan Desai, Gaurav Kaul, Zubin Aysola, Justin Johnson | |
| """ | |
| ) | |