import gradio as gr import json import spacy import re import string import pandas as pd import os import requests os.system('python -m spacy download en_core_web_sm') nlp = spacy.load("en_core_web_sm") nlp.add_pipe('sentencizer') def read_gs(sheet_url): s_url = sheet_url.replace('/edit#gid=', '/export?format=csv&gid=') df = pd.read_csv(s_url) return df def download_and_save_file(URL, audio_dir): headers = { 'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/72.0.3626.121 Safari/537.36', 'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8', 'referer': 'https://www.google.com/', 'accept-encoding': 'gzip, deflate, br', 'accept-language': 'en-US,en;q=0.9,', 'cookie': 'prov=6bb44cc9-dfe4-1b95-a65d-5250b3b4c9fb; _ga=GA1.2.1363624981.1550767314; __qca=P0-1074700243-1550767314392; notice-ctt=4%3B1550784035760; _gid=GA1.2.1415061800.1552935051; acct=t=4CnQ70qSwPMzOe6jigQlAR28TSW%2fMxzx&s=32zlYt1%2b3TBwWVaCHxH%2bl5aDhLjmq4Xr', } doc = requests.get(URL, headers=headers) file_name = URL.split('/')[-1].split('?')[0] audio_path = f'{audio_dir}/{file_name}' with open(audio_path, 'wb') as f: f.write(doc.content) return audio_path def select_samples(): df = read_gs('https://docs.google.com/spreadsheets/d/17QG4puJRXN8V5froIv8YrJIMsns0GTt4/edit#gid=1020901598') audio_dir = 'AUDIO' os.makedirs(audio_dir, exist_ok=True) df = df.sample(1) audio_url = df.url.values[0] audio_path = download_and_save_file(audio_url, audio_dir) return audio_path, df['text'].values[0] title = '🎵 Annotate audio' description = '''Choose a sentence that describes audio the best if there's no such sentence please choose `No audio description`''' audio_path, full_text = select_samples() full_text = full_text.translate(str.maketrans('', '', string.punctuation)) sents = [re.sub(r'###audio###\d###', '', s.text) for s in nlp(full_text).sents] sents.append('No audio description') def audio_demo(text, audio, audio_id): with open('data.json', 'w') as f: data = { 'audio':audio_id, 'text':text } json.dump(data, f) return 'success!' iface = gr.Interface( audio_demo, inputs=[gr.Dropdown(sents, label='audio description'), gr.Audio(audio_path, type="filepath"), gr.Textbox(value=audio_path, visible=False)], outputs=[gr.Textbox(label="output")], allow_flagging="never", title=title, description=description, ) if __name__ == "__main__": iface.launch(show_error=True, debug=True)