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| import streamlit as st | |
| from PIL import Image | |
| from bokeh.models.widgets import Button | |
| from bokeh.models import CustomJS | |
| from streamlit_bokeh_events import streamlit_bokeh_events | |
| import subprocess | |
| def show(): | |
| st.title('Visual Question Answering - Audiobot') | |
| st.markdown(''' | |
| <h4 style='text-align: center; color: #B2BEB5;'> | |
| <i>Hi, I am a Visual Audiobot, capable of answering a sequence of questions about images. | |
| Please upload image and fire away! | |
| </i></h4> | |
| ''', unsafe_allow_html=True) | |
| upload_pic = st.file_uploader('Choose an image...', type=[ | |
| 'jpg', 'png', 'jpeg'], accept_multiple_files=False) | |
| if upload_pic is not None: | |
| st.session_state.image = Image.open(upload_pic) | |
| st.image(upload_pic, use_column_width='auto') | |
| else: | |
| st.session_state.image = None | |
| # Speech recognition based in streamlit based on | |
| # https://discuss.streamlit.io/t/speech-to-text-on-client-side-using-html5-and-streamlit-bokeh-events/7888 | |
| stt_button = Button(label='Ask', width=100) | |
| stt_button.js_on_event('button_click', CustomJS(code=''' | |
| var recognition = new webkitSpeechRecognition(); | |
| recognition.continuous = false; | |
| recognition.interimResults = false; | |
| recognition.onresult = function (e) { | |
| var value = ''; | |
| for (var i = e.resultIndex; i < e.results.length; ++i) { | |
| if (e.results[i].isFinal) { | |
| value += e.results[i][0].transcript; | |
| } | |
| } | |
| if ( value != '') { | |
| document.dispatchEvent(new CustomEvent('GET_TEXT', {detail: value})); | |
| } | |
| } | |
| recognition.start(); | |
| ''')) | |
| result = streamlit_bokeh_events( | |
| stt_button, | |
| events='GET_TEXT', | |
| key='listen', | |
| refresh_on_update=False, | |
| override_height=75, | |
| debounce_time=0) | |
| if result: | |
| if 'GET_TEXT' in result: | |
| answer = st.session_state.predictor.predict_answer_from_text( | |
| st.session_state.image, result.get('GET_TEXT')) | |
| subprocess.check_output(['say', answer]) | |