devilent2 commited on
Commit
4a845d7
1 Parent(s): c8a6daa

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +17 -12
app.py CHANGED
@@ -1,11 +1,9 @@
1
  import torch
2
-
3
  import gradio as gr
4
  import spaces
5
  import yt_dlp as youtube_dl
6
  from transformers import pipeline
7
  from transformers.pipelines.audio_utils import ffmpeg_read
8
-
9
  import tempfile
10
  import os
11
 
@@ -29,8 +27,7 @@ def transcribe(inputs, task):
29
  raise gr.Error("No audio file submitted! Please upload or record an audio file before submitting your request.")
30
 
31
  text = pipe(inputs, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)["text"]
32
- return text
33
-
34
 
35
  def _return_yt_html_embed(yt_url):
36
  video_id = yt_url.split("?v=")[-1]
@@ -63,7 +60,14 @@ def download_yt_audio(yt_url, filename):
63
  file_length_hms = time.strftime("%HH:%MM:%SS", time.gmtime(file_length_s))
64
  raise gr.Error(f"Maximum YouTube length is {yt_length_limit_hms}, got {file_length_hms} YouTube video.")
65
 
66
- ydl_opts = {"outtmpl": filename, "format": "worstvideo[ext=mp4]+bestaudio[ext=m4a]/best[ext=mp4]/best"}
 
 
 
 
 
 
 
67
 
68
  with youtube_dl.YoutubeDL(ydl_opts) as ydl:
69
  try:
@@ -71,12 +75,11 @@ def download_yt_audio(yt_url, filename):
71
  except youtube_dl.utils.ExtractorError as err:
72
  raise gr.Error(str(err))
73
 
74
-
75
  def yt_transcribe(yt_url, task, max_filesize=75.0):
76
  html_embed_str = _return_yt_html_embed(yt_url)
77
 
78
  with tempfile.TemporaryDirectory() as tmpdirname:
79
- filepath = os.path.join(tmpdirname, "video.mp4")
80
  download_yt_audio(yt_url, filepath)
81
  with open(filepath, "rb") as f:
82
  inputs = f.read()
@@ -86,8 +89,7 @@ def yt_transcribe(yt_url, task, max_filesize=75.0):
86
 
87
  text = pipe(inputs, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)["text"]
88
 
89
- return html_embed_str, text
90
-
91
 
92
  demo = gr.Blocks()
93
 
@@ -131,7 +133,11 @@ yt_transcribe = gr.Interface(
131
  gr.Textbox(lines=1, placeholder="Paste the URL to a YouTube video here", label="YouTube URL"),
132
  gr.Radio(["transcribe", "translate"], label="Task", value="transcribe")
133
  ],
134
- outputs=["html", "text"],
 
 
 
 
135
  theme="huggingface",
136
  title="Whisper Large V3: Transcribe YouTube",
137
  description=(
@@ -145,5 +151,4 @@ yt_transcribe = gr.Interface(
145
  with demo:
146
  gr.TabbedInterface([mf_transcribe, file_transcribe, yt_transcribe], ["Microphone", "Audio file", "YouTube"])
147
 
148
- demo.launch()
149
-
 
1
  import torch
 
2
  import gradio as gr
3
  import spaces
4
  import yt_dlp as youtube_dl
5
  from transformers import pipeline
6
  from transformers.pipelines.audio_utils import ffmpeg_read
 
7
  import tempfile
8
  import os
9
 
 
27
  raise gr.Error("No audio file submitted! Please upload or record an audio file before submitting your request.")
28
 
29
  text = pipe(inputs, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)["text"]
30
+ return text
 
31
 
32
  def _return_yt_html_embed(yt_url):
33
  video_id = yt_url.split("?v=")[-1]
 
60
  file_length_hms = time.strftime("%HH:%MM:%SS", time.gmtime(file_length_s))
61
  raise gr.Error(f"Maximum YouTube length is {yt_length_limit_hms}, got {file_length_hms} YouTube video.")
62
 
63
+ ydl_opts = {
64
+ "outtmpl": filename,
65
+ "format": "bestaudio/best",
66
+ "postprocessors": [{
67
+ "key": "FFmpegExtractAudio",
68
+ "preferredcodec": "mp3",
69
+ }]
70
+ }
71
 
72
  with youtube_dl.YoutubeDL(ydl_opts) as ydl:
73
  try:
 
75
  except youtube_dl.utils.ExtractorError as err:
76
  raise gr.Error(str(err))
77
 
 
78
  def yt_transcribe(yt_url, task, max_filesize=75.0):
79
  html_embed_str = _return_yt_html_embed(yt_url)
80
 
81
  with tempfile.TemporaryDirectory() as tmpdirname:
82
+ filepath = os.path.join(tmpdirname, "audio.mp3")
83
  download_yt_audio(yt_url, filepath)
84
  with open(filepath, "rb") as f:
85
  inputs = f.read()
 
89
 
90
  text = pipe(inputs, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)["text"]
91
 
92
+ return html_embed_str, text, filepath
 
93
 
94
  demo = gr.Blocks()
95
 
 
133
  gr.Textbox(lines=1, placeholder="Paste the URL to a YouTube video here", label="YouTube URL"),
134
  gr.Radio(["transcribe", "translate"], label="Task", value="transcribe")
135
  ],
136
+ outputs=[
137
+ "html",
138
+ "text",
139
+ gr.Audio(label="Extracted Audio")
140
+ ],
141
  theme="huggingface",
142
  title="Whisper Large V3: Transcribe YouTube",
143
  description=(
 
151
  with demo:
152
  gr.TabbedInterface([mf_transcribe, file_transcribe, yt_transcribe], ["Microphone", "Audio file", "YouTube"])
153
 
154
+ demo.launch()