import streamlit as st import io import sys import time sys.path.append("./virtex/") st.title("Image Captioning Demo from Redcaps") st.sidebar.markdown( """ Image Captioning Model from VirTex trained on Redcaps """ ) with st.spinner("Loading Model"): st.write("DEBUG PRINTING ==========") start = time.time() from model import * st.write(f"Import TIME: {time.time()-start}") sample_images = get_samples() start = time.time() download_files() st.write(f"download TIME: {time.time()-start}") start = time.time() virtexModel = VirTexModel() imageLoader = ImageLoader() st.write(f"model TIME: {time.time()-start}") random_image = get_rand_img(sample_images) st.sidebar.title("Select a sample image") sample_image = st.sidebar.selectbox( "", sample_images ) if st.sidebar.button("Random Sample Image"): random_image = get_rand_img(sample_images) sample_image = None uploaded_image = None with st.sidebar.form("file-uploader-form", clear_on_submit=True): uploaded_file = st.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())) if uploaded_image is None and submitted: st.write("Please select a file to upload") else: image_file = sample_image if sample_image is not None else random_image image = uploaded_image if uploaded_image is not None else Image.open(image_file) image_dict = imageLoader.transform(image) image = imageLoader.to_image(image_dict["image"].squeeze(0)) show = st.image(image) show.image(image, "Your Image") with st.spinner("Generating Caption"): subreddit, caption = virtexModel.predict(image_dict) st.header("Predicted Caption:\n\n") st.subheader(f"Subreddit: {subreddit}\n") st.subheader(f"Caption: {caption}\n") image.close() # from model import * # download_files() # sample_images = get_samples() # v, il = VirTexModel(), ImageLoader() # for s in sample_images: # subreddit, caption = v.predict(il.load(s)) # print("=====================") # print(subreddit) # print(caption)