mikr commited on
Commit
7c78da4
1 Parent(s): 1031935

upgrade interface

Browse files
Files changed (1) hide show
  1. app.py +70 -15
app.py CHANGED
@@ -1,26 +1,24 @@
 
 
1
  import gradio as gr
2
  import soundfile as sf
3
- import torch
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  import numpy as np
 
5
  import librosa
6
  from transformers import AutoProcessor, Wav2Vec2BertForCTC
7
- import spaces
8
 
9
  MODEL_NAME = "mikr/w2v-bert-2.0-czech-colab-cv16"
10
 
11
- device = 0 if torch.cuda.is_available() else "cpu"
12
 
13
- print("device:",device)
14
 
15
  processor = AutoProcessor.from_pretrained(MODEL_NAME)
16
  model = Wav2Vec2BertForCTC.from_pretrained(MODEL_NAME).to(device)
17
 
18
 
19
  @spaces.GPU
20
- def transcribe(audio_path):
21
  a, s = librosa.load(audio_path, sr=16_000)
22
-
23
- # inputs = processor(a, sampling_rate=s, return_tensors="pt")
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  input_values = processor(a, sampling_rate=s, return_tensors="pt").input_features
25
 
26
  with torch.no_grad():
@@ -30,23 +28,80 @@ def transcribe(audio_path):
30
 
31
  # transcribe speech
32
  transcription = processor.batch_decode(predicted_ids)
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- return transcription[0]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
34
 
35
 
36
- iface = gr.Interface(
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
37
  fn=transcribe,
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  inputs=[
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- gr.Audio(sources="upload", type="filepath", label="Upload Audio File"), # Audio file upload
 
40
  ],
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  outputs="text",
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- theme="huggingface",
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- title="Czech W2V-BERT 2.0 speech encoder demo - transcribe Czech Audio",
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  description=(
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- "Transcribe audio inputs with the click of a button! Demo uses the fine-tuned"
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- f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) from Facebook W2V-BERT 2.0 speech encoder "
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  "and 🤗 Transformers to transcribe audio files of arbitrary length."
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  ),
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  allow_flagging="never",
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  )
51
 
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- iface.launch(server_name="0.0.0.0")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import torch
2
+ import spaces
3
  import gradio as gr
4
  import soundfile as sf
 
5
  import numpy as np
6
+ import pytube as pt
7
  import librosa
8
  from transformers import AutoProcessor, Wav2Vec2BertForCTC
 
9
 
10
  MODEL_NAME = "mikr/w2v-bert-2.0-czech-colab-cv16"
11
 
 
12
 
13
+ device = 0 if torch.cuda.is_available() else "cpu"
14
 
15
  processor = AutoProcessor.from_pretrained(MODEL_NAME)
16
  model = Wav2Vec2BertForCTC.from_pretrained(MODEL_NAME).to(device)
17
 
18
 
19
  @spaces.GPU
20
+ def text_from_audio(audio_path):
21
  a, s = librosa.load(audio_path, sr=16_000)
 
 
22
  input_values = processor(a, sampling_rate=s, return_tensors="pt").input_features
23
 
24
  with torch.no_grad():
 
28
 
29
  # transcribe speech
30
  transcription = processor.batch_decode(predicted_ids)
31
+ text = transcription[0]
32
+ return text
33
+
34
+
35
+ def transcribe(microphone, file_upload):
36
+ warn_output = ""
37
+ if (microphone is not None) and (file_upload is not None):
38
+ warn_output = (
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+ "WARNING: You've uploaded an audio file and used the microphone. "
40
+ "The recorded file from the microphone will be used and the uploaded audio will be discarded.\n"
41
+ )
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+
43
+ elif (microphone is None) and (file_upload is None):
44
+ return "ERROR: You have to either use the microphone or upload an audio file"
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+
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+ audio_path = microphone if microphone is not None else file_upload
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+
48
+ text = text_from_audio(audio_path)
49
+
50
+ return warn_output + text
51
 
52
 
53
+ def _return_yt_html_embed(yt_url):
54
+ video_id = yt_url.split("?v=")[-1]
55
+ HTML_str = (
56
+ f'<center> <iframe width="500" height="320" src="https://www.youtube.com/embed/{video_id}"> </iframe>'
57
+ " </center>"
58
+ )
59
+ return HTML_str
60
+
61
+
62
+ def yt_transcribe(yt_url):
63
+ yt = pt.YouTube(yt_url)
64
+ html_embed_str = _return_yt_html_embed(yt_url)
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+ stream = yt.streams.filter(only_audio=True)[0]
66
+ stream.download(filename="audio.mp3")
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+
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+ text = text_from_audio("audio.mp3")
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+
70
+ return html_embed_str, text
71
+
72
+
73
+ demo = gr.Blocks()
74
+
75
+ mf_transcribe = gr.Interface(
76
  fn=transcribe,
77
  inputs=[
78
+ gr.Audio(sources="microphone", type="filepath"),
79
+ gr.Audio(sources="upload", type="filepath"),
80
  ],
81
  outputs="text",
82
+ title="W2V Bert 2.0 Demo: Transcribe Czech Audio",
 
83
  description=(
84
+ "Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the fine-tuned"
85
+ f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) "
86
  "and 🤗 Transformers to transcribe audio files of arbitrary length."
87
  ),
88
  allow_flagging="never",
89
  )
90
 
91
+ yt_transcribe = gr.Interface(
92
+ fn=yt_transcribe,
93
+ inputs=[gr.Textbox(lines=1, placeholder="Paste the URL to a YouTube video here", label="YouTube URL")],
94
+ outputs=["html", "text"],
95
+ title="W2V Bert 2.0 Demo: Transcribe Czech YouTube Video",
96
+ description=(
97
+ "Transcribe long-form YouTube videos with the click of a button! Demo uses the the fine-tuned checkpoint:"
98
+ f" [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files of"
99
+ " arbitrary length."
100
+ ),
101
+ allow_flagging="never",
102
+ )
103
+
104
+ with demo:
105
+ gr.TabbedInterface([mf_transcribe, yt_transcribe], ["Transcribe Audio", "Transcribe YouTube"])
106
+
107
+ demo.launch(server_name="0.0.0.0")