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| """ | |
| # Copyright (c) 2022, salesforce.com, inc. | |
| # All rights reserved. | |
| # SPDX-License-Identifier: BSD-3-Clause | |
| # For full license text, see the LICENSE file in the repo root or https://opensource.org/licenses/BSD-3-Clause | |
| """ | |
| import streamlit as st | |
| from app import load_demo_image, device | |
| from app.utils import load_model_cache | |
| from lavis.processors import load_processor | |
| from PIL import Image | |
| def app(): | |
| model_type = st.sidebar.selectbox("Model:", ["BLIP"]) | |
| # ===== layout ===== | |
| st.markdown( | |
| "<h1 style='text-align: center;'>Visual Question Answering</h1>", | |
| unsafe_allow_html=True, | |
| ) | |
| instructions = """Try the provided image or upload your own:""" | |
| file = st.file_uploader(instructions) | |
| col1, col2 = st.columns(2) | |
| col1.header("Image") | |
| if file: | |
| raw_img = Image.open(file).convert("RGB") | |
| else: | |
| raw_img = load_demo_image() | |
| w, h = raw_img.size | |
| scaling_factor = 720 / w | |
| resized_image = raw_img.resize((int(w * scaling_factor), int(h * scaling_factor))) | |
| col1.image(resized_image, use_column_width=True) | |
| col2.header("Question") | |
| user_question = col2.text_input("Input your question!", "What are objects there?") | |
| qa_button = st.button("Submit") | |
| col2.header("Answer") | |
| # ===== event ===== | |
| vis_processor = load_processor("blip_image_eval").build(image_size=480) | |
| text_processor = load_processor("blip_question").build() | |
| if qa_button: | |
| if model_type.startswith("BLIP"): | |
| model = load_model_cache( | |
| "blip_vqa", model_type="vqav2", is_eval=True, device=device | |
| ) | |
| img = vis_processor(raw_img).unsqueeze(0).to(device) | |
| question = text_processor(user_question) | |
| vqa_samples = {"image": img, "text_input": [question]} | |
| answers = model.predict_answers(vqa_samples, inference_method="generate") | |
| col2.write("\n".join(answers), use_column_width=True) | |