Merge pull request #53 from ahmetoner/add-new-large-model-v2

Add new large model v2

README.md

@@ -34,7 +34,7 @@ docker run -d -p 9000:9000 -e ASR_MODEL=base onerahmet/openai-whisper-asr-webser
 # Interactive Swagger API documentation is available at http://localhost:9000/docs
 ```
 
-Available ASR_MODELs are `tiny`, `base`, `small`, `medium` and `large`
+Available ASR_MODELs are `tiny`, `base`, `small`, `medium`, `large`, `large-v1` and `large-v2`. Please note that `large` and `large-v2` are the same model.
 
 For English-only applications, the `.en` models tend to perform better, especially for the `tiny.en` and `base.en` models. We observed that the difference becomes less significant for the `small.en` and `medium.en` models.
 
@@ -64,7 +64,7 @@ poetry install
 Starting the Webservice:
 
 ```sh
-gunicorn --bind 0.0.0.0:9000 --workers 1 --timeout 0 app.webservice:app -k uvicorn.workers.UvicornWorker
+gunicorn --bind 0.0.0.0:9001 --workers 1 --timeout 0 app.webservice:app -k uvicorn.workers.UvicornWorker
 ```
 
 ## Quick start

app/languages.py

@@ -1,120 +0,0 @@
-#from whisper/tokenizer.py
-LANGUAGES = {
-    "en": "english",
-    "zh": "chinese",
-    "de": "german",
-    "es": "spanish",
-    "ru": "russian",
-    "ko": "korean",
-    "fr": "french",
-    "ja": "japanese",
-    "pt": "portuguese",
-    "tr": "turkish",
-    "pl": "polish",
-    "ca": "catalan",
-    "nl": "dutch",
-    "ar": "arabic",
-    "sv": "swedish",
-    "it": "italian",
-    "id": "indonesian",
-    "hi": "hindi",
-    "fi": "finnish",
-    "vi": "vietnamese",
-    "iw": "hebrew",
-    "uk": "ukrainian",
-    "el": "greek",
-    "ms": "malay",
-    "cs": "czech",
-    "ro": "romanian",
-    "da": "danish",
-    "hu": "hungarian",
-    "ta": "tamil",
-    "no": "norwegian",
-    "th": "thai",
-    "ur": "urdu",
-    "hr": "croatian",
-    "bg": "bulgarian",
-    "lt": "lithuanian",
-    "la": "latin",
-    "mi": "maori",
-    "ml": "malayalam",
-    "cy": "welsh",
-    "sk": "slovak",
-    "te": "telugu",
-    "fa": "persian",
-    "lv": "latvian",
-    "bn": "bengali",
-    "sr": "serbian",
-    "az": "azerbaijani",
-    "sl": "slovenian",
-    "kn": "kannada",
-    "et": "estonian",
-    "mk": "macedonian",
-    "br": "breton",
-    "eu": "basque",
-    "is": "icelandic",
-    "hy": "armenian",
-    "ne": "nepali",
-    "mn": "mongolian",
-    "bs": "bosnian",
-    "kk": "kazakh",
-    "sq": "albanian",
-    "sw": "swahili",
-    "gl": "galician",
-    "mr": "marathi",
-    "pa": "punjabi",
-    "si": "sinhala",
-    "km": "khmer",
-    "sn": "shona",
-    "yo": "yoruba",
-    "so": "somali",
-    "af": "afrikaans",
-    "oc": "occitan",
-    "ka": "georgian",
-    "be": "belarusian",
-    "tg": "tajik",
-    "sd": "sindhi",
-    "gu": "gujarati",
-    "am": "amharic",
-    "yi": "yiddish",
-    "lo": "lao",
-    "uz": "uzbek",
-    "fo": "faroese",
-    "ht": "haitian creole",
-    "ps": "pashto",
-    "tk": "turkmen",
-    "nn": "nynorsk",
-    "mt": "maltese",
-    "sa": "sanskrit",
-    "lb": "luxembourgish",
-    "my": "myanmar",
-    "bo": "tibetan",
-    "tl": "tagalog",
-    "mg": "malagasy",
-    "as": "assamese",
-    "tt": "tatar",
-    "haw": "hawaiian",
-    "ln": "lingala",
-    "ha": "hausa",
-    "ba": "bashkir",
-    "jw": "javanese",
-    "su": "sundanese",
-}
-
-# language code lookup by name, with a few language aliases
-TO_LANGUAGE_CODE = {
-    **{language: code for code, language in LANGUAGES.items()},
-    "burmese": "my",
-    "valencian": "ca",
-    "flemish": "nl",
-    "haitian": "ht",
-    "letzeburgesch": "lb",
-    "pushto": "ps",
-    "panjabi": "pa",
-    "moldavian": "ro",
-    "moldovan": "ro",
-    "sinhalese": "si",
-    "castilian": "es",
-}
-
-LANGUAGE_CODES = sorted(list(LANGUAGES.keys()))

app/webservice.py

@@ -4,12 +4,12 @@ from fastapi.staticfiles import StaticFiles
 from fastapi.openapi.docs import get_swagger_ui_html
 import whisper
 from whisper.utils import write_srt, write_vtt
+from whisper import tokenizer
 import os
 from os import path
 from pathlib import Path
 import ffmpeg
 from typing import BinaryIO, Union
-from .languages import LANGUAGES, LANGUAGE_CODES
 import numpy as np
 from io import StringIO
 from threading import Lock
@@ -18,6 +18,7 @@ import fastapi_offline_swagger_ui
 import importlib.metadata 
 
 SAMPLE_RATE=16000
+LANGUAGE_CODES=sorted(list(tokenizer.LANGUAGES.keys()))
 
 projectMetadata = importlib.metadata.metadata('whisper-asr-webservice')
 app = FastAPI(
@@ -101,7 +102,7 @@ def language_detection(
         _, probs = model.detect_language(mel)
     detected_lang_code = max(probs, key=probs.get)
     
-    result = { "detected_language": LANGUAGES[detected_lang_code],
+    result = { "detected_language": tokenizer.LANGUAGES[detected_lang_code],
               "langauge_code" : detected_lang_code }
 
     return result

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "whisper-asr-webservice"
-version = "1.0.4"
+version = "1.0.5"
 description = "Whisper ASR Webservice is a general-purpose speech recognition webservice."
 homepage  = "https://github.com/ahmetoner/whisper-asr-webservice/"
 license = "https://github.com/ahmetoner/whisper-asr-webservice/blob/main/LICENCE"
@@ -16,7 +16,7 @@ python = "^3.9"
 unidecode = "^1.3.4"
 uvicorn = { extras = ["standard"], version = "^0.18.2" }
 gunicorn = "^20.1.0"
-whisper = {git = "https://github.com/openai/whisper.git", rev="eff383b27b783e280c089475852ba83f20f64998"}
+whisper = {git = "https://github.com/openai/whisper.git", rev="b9265e5796f5d80c18d1f9231ab234225676780b"}
 tqdm = "^4.64.1"
 transformers = "^4.22.1"
 python-multipart = "^0.0.5"