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Runtime error
| import json | |
| import os | |
| import requests | |
| import json | |
| import streamlit as st | |
| EXAMPLE_PATH = [] | |
| for f in os.listdir('data/'): | |
| EXAMPLE_PATH.append(f) | |
| st.sidebar.image('img/love_emoji_128.png') | |
| st.sidebar.title('EMOVoice') | |
| st.sidebar.write('Welcome to EMOVoice, a tool for Speech Emotion Recognition based on the Wav2Vec2 model.') | |
| st.title('EMOVoice') | |
| st.write("This is a work in progress, stay tuned!") | |
| st.sidebar.subheader('Model input') | |
| input_mode = st.sidebar.radio('Select your input mode:', ['Upload audio', 'Select example']) | |
| file = None | |
| if input_mode == 'Upload audio': | |
| file = st.sidebar.file_uploader("Choose a file", type=['mp3', 'mp4', 'wav', 'flac']) | |
| file_size = file.size if file else None | |
| elif input_mode == 'Select example': | |
| example_selected = st.sidebar.selectbox('Choose an audio example', EXAMPLE_PATH) | |
| file = open('data/' + example_selected, 'rb') | |
| file_size = os.stat('data/' + example_selected).st_size | |
| if file is not None: | |
| st.write('Audio added!') | |
| audio_bytes = file.read() | |
| st.audio(audio_bytes) | |
| url = "https://api-inference.huggingface.co/models/ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition" | |
| payload=file | |
| headers = { | |
| 'Content-Type': 'audio/mp3', | |
| 'Authorization': 'Bearer ' + st.secrets['API_TOKEN'] | |
| } | |
| response = requests.request("POST", url, headers=headers, data=audio_bytes) | |
| response.request | |
| decoded_response = json.loads(response.text) | |
| st.write(decoded_response) | |
| file.close() | |