File size: 6,749 Bytes
6a308c6
8d120bf
 
05a2178
3fadc6e
8d120bf
3fadc6e
 
8d120bf
 
 
 
 
05a2178
8d120bf
05a2178
3fadc6e
7ce6041
 
4514e2e
7ce6041
533d92e
 
 
6a308c6
 
 
93c4867
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
05a2178
 
 
 
71950a8
 
 
05a2178
8d120bf
 
533d92e
 
 
 
 
 
 
 
 
 
 
 
 
71950a8
533d92e
 
 
71950a8
533d92e
 
 
 
6a308c6
 
 
 
 
 
 
71950a8
533d92e
 
 
71950a8
533d92e
 
 
 
3fadc6e
533d92e
3fadc6e
533d92e
 
 
 
 
3fadc6e
8d120bf
6a308c6
 
 
 
 
 
 
 
 
8d120bf
 
 
 
 
 
 
 
 
6a308c6
8d120bf
 
3fadc6e
 
 
 
 
 
 
 
6a308c6
3fadc6e
7ce6041
3fadc6e
6a308c6
3fadc6e
6a308c6
3fadc6e
 
05a2178
3fadc6e
 
8d120bf
05a2178
d5154e9
71950a8
05a2178
71950a8
 
 
05a2178
71950a8
 
93c4867
71950a8
 
 
8d120bf
71950a8
 
 
3fadc6e
8d120bf
3fadc6e
8d120bf
3fadc6e
7ce6041
d5154e9
05a2178
71950a8
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
import re
from typing import Iterator

from io import StringIO
import os
import pathlib
import tempfile

# External programs
import whisper
import ffmpeg

# UI
import gradio as gr
from download import downloadUrl

from utils import slugify, write_srt, write_vtt

# Limitations (set to -1 to disable)
DEFAULT_INPUT_AUDIO_MAX_DURATION = 600 # seconds

# Whether or not to automatically delete all uploaded files, to save disk space
DELETE_UPLOADED_FILES = True

# Gradio seems to truncate files without keeping the extension, so we need to truncate the file prefix ourself 
MAX_FILE_PREFIX_LENGTH = 17

LANGUAGES = [ 
 "English", "Chinese", "German", "Spanish", "Russian", "Korean", 
 "French", "Japanese", "Portuguese", "Turkish", "Polish", "Catalan", 
 "Dutch", "Arabic", "Swedish", "Italian", "Indonesian", "Hindi", 
 "Finnish", "Vietnamese", "Hebrew", "Ukrainian", "Greek", "Malay", 
 "Czech", "Romanian", "Danish", "Hungarian", "Tamil", "Norwegian", 
 "Thai", "Urdu", "Croatian", "Bulgarian", "Lithuanian", "Latin", 
 "Maori", "Malayalam", "Welsh", "Slovak", "Telugu", "Persian", 
 "Latvian", "Bengali", "Serbian", "Azerbaijani", "Slovenian", 
 "Kannada", "Estonian", "Macedonian", "Breton", "Basque", "Icelandic", 
 "Armenian", "Nepali", "Mongolian", "Bosnian", "Kazakh", "Albanian",
 "Swahili", "Galician", "Marathi", "Punjabi", "Sinhala", "Khmer", 
 "Shona", "Yoruba", "Somali", "Afrikaans", "Occitan", "Georgian", 
 "Belarusian", "Tajik", "Sindhi", "Gujarati", "Amharic", "Yiddish", 
 "Lao", "Uzbek", "Faroese", "Haitian Creole", "Pashto", "Turkmen", 
 "Nynorsk", "Maltese", "Sanskrit", "Luxembourgish", "Myanmar", "Tibetan",
 "Tagalog", "Malagasy", "Assamese", "Tatar", "Hawaiian", "Lingala", 
 "Hausa", "Bashkir", "Javanese", "Sundanese"
]

model_cache = dict()

class UI:
    def __init__(self, inputAudioMaxDuration):
        self.inputAudioMaxDuration = inputAudioMaxDuration

    def transcribeFile(self, modelName, languageName, urlData, uploadFile, microphoneData, task):
        source, sourceName = getSource(urlData, uploadFile, microphoneData)
        
        try:
            selectedLanguage = languageName.lower() if len(languageName) > 0 else None
            selectedModel = modelName if modelName is not None else "base"

            if self.inputAudioMaxDuration > 0:
                # Calculate audio length
                audioDuration = ffmpeg.probe(source)["format"]["duration"]
                
                if float(audioDuration) > self.inputAudioMaxDuration:
                    return ("[ERROR]: Maximum audio file length is " + str(self.inputAudioMaxDuration) + "s, file was " + str(audioDuration) + "s"), "[ERROR]"

            model = model_cache.get(selectedModel, None)
            
            if not model:
                model = whisper.load_model(selectedModel)
                model_cache[selectedModel] = model

            # The results
            result = model.transcribe(source, language=selectedLanguage, task=task)

            text = result["text"]

            language = result["language"]
            languageMaxLineWidth = getMaxLineWidth(language)

            print("Max line width " + str(languageMaxLineWidth))
            vtt = getSubs(result["segments"], "vtt", languageMaxLineWidth)
            srt = getSubs(result["segments"], "srt", languageMaxLineWidth)

            # Files that can be downloaded
            downloadDirectory = tempfile.mkdtemp()
            filePrefix = slugify(sourceName, allow_unicode=True)

            download = []
            download.append(createFile(srt, downloadDirectory, filePrefix + "-subs.srt"));
            download.append(createFile(vtt, downloadDirectory, filePrefix + "-subs.vtt"));
            download.append(createFile(text, downloadDirectory, filePrefix + "-transcript.txt"));

            return download, text, vtt

        finally:
            # Cleanup source
            if DELETE_UPLOADED_FILES:
                print("Deleting source file " + source)
                os.remove(source)


def getMaxLineWidth(language: str) -> int:
    if (language == "ja" or language == "zh"):
        # Chinese characters and kana are wider, so limit line length to 40 characters
        return 40
    else:
        # TODO: Add more languages
        # 80 latin characters should fit on a 1080p/720p screen
        return 80

def getSource(urlData, uploadFile, microphoneData):
    if urlData:
        # Download from YouTube
        source = downloadUrl(urlData)
    else:
        # File input
        source = uploadFile if uploadFile is not None else microphoneData

    file_path = pathlib.Path(source)
    sourceName = file_path.stem[:MAX_FILE_PREFIX_LENGTH] + file_path.suffix

    return source, sourceName

def createFile(text: str, directory: str, fileName: str) -> str:
    # Write the text to a file
    with open(os.path.join(directory, fileName), 'w+', encoding="utf-8") as file:
        file.write(text)

    return file.name

def getSubs(segments: Iterator[dict], format: str, maxLineWidth: int) -> str:
    segmentStream = StringIO()

    if format == 'vtt':
        write_vtt(segments, file=segmentStream, maxLineWidth=maxLineWidth)
    elif format == 'srt':
        write_srt(segments, file=segmentStream, maxLineWidth=maxLineWidth)
    else:
        raise Exception("Unknown format " + format)

    segmentStream.seek(0)
    return segmentStream.read()
    

def createUi(inputAudioMaxDuration, share=False, server_name: str = None):
    ui = UI(inputAudioMaxDuration)

    ui_description = "Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse " 
    ui_description += " audio and is also a multi-task model that can perform multilingual speech recognition "
    ui_description += " as well as speech translation and language identification. "

    if inputAudioMaxDuration > 0:
        ui_description += "\n\n" + "Max audio file length: " + str(inputAudioMaxDuration) + " s"

    demo = gr.Interface(fn=ui.transcribeFile, description=ui_description, inputs=[
        gr.Dropdown(choices=["tiny", "base", "small", "medium", "large"], value="medium", label="Model"),
        gr.Dropdown(choices=sorted(LANGUAGES), label="Language"),
        gr.Text(label="URL (YouTube, etc.)"),
        gr.Audio(source="upload", type="filepath", label="Upload Audio"), 
        gr.Audio(source="microphone", type="filepath", label="Microphone Input"),
        gr.Dropdown(choices=["transcribe", "translate"], label="Task"),
    ], outputs=[
        gr.File(label="Download"),
        gr.Text(label="Transcription"), 
        gr.Text(label="Segments")
    ])

    demo.launch(share=share, server_name=server_name)   

if __name__ == '__main__':
    createUi(DEFAULT_INPUT_AUDIO_MAX_DURATION)