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Runtime error
salmanmapkar
commited on
Commit
•
eb43d71
1
Parent(s):
502d612
Update app.py
Browse files
app.py
CHANGED
@@ -1,5 +1,6 @@
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from __future__ import unicode_literals
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import youtube_dl
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from pydub import AudioSegment
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from pyannote.audio import Pipeline
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import re
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@@ -24,12 +25,6 @@ import contextlib
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from sklearn.cluster import AgglomerativeClustering
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import numpy as np
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model = whisper.load_model("medium")
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embedding_model = PretrainedSpeakerEmbedding(
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"speechbrain/spkrec-ecapa-voxceleb",
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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)
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__FILES = set()
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@@ -49,7 +44,7 @@ def RemoveAllFiles():
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def Transcribe_V1(NumberOfSpeakers, SpeakerNames="", audio="temp_audio.wav"):
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SPEAKER_DICT = {}
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SPEAKERS = [speaker.strip() for speaker in SpeakerNames.split(',')]
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def GetSpeaker(sp):
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speaker = sp
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@@ -109,7 +104,7 @@ def Transcribe_V1(NumberOfSpeakers, SpeakerNames="", audio="temp_audio.wav"):
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return f"dz_{audio}.wav", dzList, segments
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def transcribe(dz_audio):
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model = whisper.load_model("
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result = model.transcribe(dz_audio)
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# for _ in result['segments']:
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# print(_['start'], _['end'], _['text'])
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@@ -144,8 +139,13 @@ def Transcribe_V1(NumberOfSpeakers, SpeakerNames="", audio="temp_audio.wav"):
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def Transcribe_V2(num_speakers, speaker_names, audio="temp_audio.wav"):
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SPEAKER_DICT = {}
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SPEAKERS = [speaker.strip() for speaker in speaker_names.split(',')]
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def GetSpeaker(sp):
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speaker = sp
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if sp not in list(SPEAKER_DICT.keys()):
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@@ -223,6 +223,7 @@ def Transcribe_V2(num_speakers, speaker_names, audio="temp_audio.wav"):
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# return output
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def AudioTranscribe(NumberOfSpeakers=None, SpeakerNames="", audio="", retries=5):
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if retries:
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# subprocess.call(['ffmpeg', '-i', audio,'temp_audio.wav'])
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try:
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@@ -268,7 +269,7 @@ def YoutubeTranscribe(NumberOfSpeakers=None, SpeakerNames="", URL="", retries =
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}],
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}
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try:
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with
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ydl.download([URL])
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except:
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return YoutubeTranscribe(NumberOfSpeakers, SpeakerNames, URL, retries-1)
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@@ -295,5 +296,43 @@ at = gr.Interface(
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outputs=[gr.Textbox(label="Transcribed Text", lines=15), gr.JSON(label="Transcribed JSON")]
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)
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demo = gr.TabbedInterface([ut, vt, at], ["Youtube URL", "Video", "Audio"])
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demo.launch()
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from __future__ import unicode_literals
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import youtube_dl
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import yt_dlp
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from pydub import AudioSegment
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from pyannote.audio import Pipeline
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import re
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from sklearn.cluster import AgglomerativeClustering
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import numpy as np
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__FILES = set()
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def Transcribe_V1(NumberOfSpeakers, SpeakerNames="", audio="temp_audio.wav"):
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SPEAKER_DICT = {}
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SPEAKERS = [speaker.strip() for speaker in SpeakerNames.split(',') if len(speaker)]
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def GetSpeaker(sp):
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speaker = sp
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return f"dz_{audio}.wav", dzList, segments
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def transcribe(dz_audio):
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model = whisper.load_model("medium")
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result = model.transcribe(dz_audio)
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# for _ in result['segments']:
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# print(_['start'], _['end'], _['text'])
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def Transcribe_V2(num_speakers, speaker_names, audio="temp_audio.wav"):
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model = whisper.load_model("medium")
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embedding_model = PretrainedSpeakerEmbedding(
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"speechbrain/spkrec-ecapa-voxceleb",
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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)
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SPEAKER_DICT = {}
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SPEAKERS = [speaker.strip() for speaker in speaker_names.split(',') if len(speaker)]
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def GetSpeaker(sp):
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speaker = sp
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if sp not in list(SPEAKER_DICT.keys()):
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# return output
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def AudioTranscribe(NumberOfSpeakers=None, SpeakerNames="", audio="", retries=5):
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print(f"{NumberOfSpeakers}, {SpeakerNames}, {retries}")
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if retries:
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# subprocess.call(['ffmpeg', '-i', audio,'temp_audio.wav'])
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try:
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}],
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}
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try:
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with yt_dlp.YoutubeDL(ydl_opts) as ydl:
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ydl.download([URL])
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except:
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return YoutubeTranscribe(NumberOfSpeakers, SpeakerNames, URL, retries-1)
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outputs=[gr.Textbox(label="Transcribed Text", lines=15), gr.JSON(label="Transcribed JSON")]
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)
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# demo = gr.TabbedInterface([ut, vt, at], ["Youtube URL", "Video", "Audio"])
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# demo.launch()
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with gr.Blocks() as yav_ui:
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with gr.Tab("Input"):
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with gr.Tab("Youtube", id=1):
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yinput_nos = gr.Number(label="Number of Speakers", placeholder="2")
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yinput_sn = gr.Textbox(label="Name of the Speakers (ordered by the time they speak and separated by comma)", placeholder="If Speaker 1 is first to speak followed by Speaker 2 then -> Speaker 1, Speaker 2")
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yinput = gr.Textbox(label="Youtube Link", placeholder="https://www.youtube.com/watch?v=GECcjrYHH8w")
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ybutton_transcribe = gr.Button("Transcribe")
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with gr.Tab("Video", id=2):
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vinput_nos = gr.Number(label="Number of Speakers", placeholder="2")
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vinput_sn = gr.Textbox(label="Name of the Speakers (ordered by the time they speak and separated by comma)", placeholder="If Speaker 1 is first to speak followed by Speaker 2 then -> Speaker 1, Speaker 2")
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vinput = gr.Video(label="Video")
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vbutton_transcribe = gr.Button("Transcribe")
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with gr.Tab("Audio", id=3):
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ainput_nos = gr.Number(label="Number of Speakers", placeholder="2")
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ainput_sn = gr.Textbox(label="Name of the Speakers (ordered by the time they speak and separated by comma)", placeholder="If Speaker 1 is first to speak followed by Speaker 2 then -> Speaker 1, Speaker 2")
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ainput = gr.Audio(label="Audio")
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abutton_transcribe = gr.Button("Transcribe")
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with gr.Tab("Output"):
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with gr.Tab("Text"):
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output_textbox = gr.Textbox(label="Transcribed Text", lines=15)
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with gr.Tab("JSON"):
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output_json = gr.JSON(label="Transcribed JSON")
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ybutton_transcribe.click(
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fn=YoutubeTranscribe,
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inputs=[yinput_nos,yinput_sn,yinput],
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outputs=[output_textbox,output_json]
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)
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abutton_transcribe.click(
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fn=AudioTranscribe,
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inputs=[ainput_nos,ainput_sn,ainput],
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outputs=[output_textbox,output_json]
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)
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vbutton_transcribe.click(
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fn=VideoTranscribe,
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inputs=[vinput_nos,vinput_sn,vinput],
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outputs=[output_textbox,output_json]
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)
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yav_ui.launch(debug=True)
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