Jaikinator
102 lines
2.9 KiB
Python
102 lines
2.9 KiB
Python
from dash import Dash, dcc, html, dash_table, Input, Output, State, callback
|
|
|
|
import base64
|
|
from scraibe.app.qtfaststart import process
|
|
from scraibe import AutoTranscribe
|
|
import io
|
|
import subprocess as sp
|
|
import numpy as np
|
|
from scraibe.audio import SAMPLE_RATE
|
|
|
|
# Setup auto-transcript
|
|
autot = AutoTranscribe() # whisper_model="tiny", whisper_kwargs={"local" : False}
|
|
|
|
# Setup FFmpeg
|
|
PROBLEMATIC_FILE_TYPES : tuple = "mov","mp4","m4a","3gp","3g2","mj2"
|
|
|
|
|
|
# Setup Dash
|
|
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
|
|
|
|
app = Dash(__name__, external_stylesheets=external_stylesheets)
|
|
|
|
app.layout = html.Div([
|
|
dcc.Upload(
|
|
id='upload-data',
|
|
children=html.Div([
|
|
'Drag and Drop or ',
|
|
html.A('Select Files')
|
|
]),
|
|
style={
|
|
'width': '100%',
|
|
'height': '60px',
|
|
'lineHeight': '60px',
|
|
'borderWidth': '1px',
|
|
'borderStyle': 'dashed',
|
|
'borderRadius': '5px',
|
|
'textAlign': 'center',
|
|
'margin': '10px'
|
|
},
|
|
# Allow multiple files to be uploaded
|
|
multiple=True
|
|
),
|
|
html.Div(id='output-data-upload'),
|
|
])
|
|
|
|
def parse_contents(contents, filename, date):
|
|
content_type, content_string = contents.split(',')
|
|
|
|
decoded = base64.b64decode(content_string)
|
|
file = io.BytesIO(decoded).read()
|
|
|
|
if filename.endswith(PROBLEMATIC_FILE_TYPES):
|
|
# mp4 and other files need to be processed with qtfaststart
|
|
# since theire metadata is at the end of the file
|
|
# and we need it at the beginning
|
|
file = process(file)
|
|
|
|
cmd = [
|
|
"ffmpeg",
|
|
"-nostdin",
|
|
"-threads", "0",
|
|
"-i",'pipe:',
|
|
"-f", "s16le",
|
|
'-hide_banner',
|
|
'-loglevel', 'error',
|
|
"-c", "copy",
|
|
"-vn",
|
|
"-ac", "1",
|
|
"-acodec", "pcm_s16le",
|
|
"-ar", str(SAMPLE_RATE),
|
|
"-"
|
|
]
|
|
|
|
proc = sp.Popen(cmd, stdout=sp.PIPE, stdin=sp.PIPE)
|
|
|
|
out = proc.communicate(input=file)[0]
|
|
out = np.frombuffer(out, np.int16).flatten().astype(np.float32) / 32768.0
|
|
out = np.array([out, SAMPLE_RATE])
|
|
|
|
transcript = str(autot.transcribe(out))
|
|
|
|
return html.Div([
|
|
html.H5(f"File Name: {filename} \n" \
|
|
"Transcript: \n"
|
|
),
|
|
html.P(transcript)
|
|
])
|
|
|
|
@callback(Output('output-data-upload', 'children'),
|
|
Input('upload-data', 'contents'),
|
|
State('upload-data', 'filename'),
|
|
State('upload-data', 'last_modified'))
|
|
def update_output(list_of_contents, list_of_names, list_of_dates):
|
|
if list_of_contents is not None:
|
|
children = [
|
|
parse_contents(c, n, d) for c, n, d in
|
|
zip(list_of_contents, list_of_names, list_of_dates)]
|
|
return children
|
|
|
|
if __name__ == '__main__':
|
|
app.run_server()
|