init
Changes made (not exhaustive): - changed defaults - whisper.cpp submodule set to 1.2.0 - removed `requests` dependency - models dir can be changed in constructor - added support for setting params - added back support for `large-v1` model - added support for english-only models
This commit is contained in:
lightmare
parent
e2581c8aad
commit
af035ea355
40
.github/workflows/build_wheels.yml
vendored
40
.github/workflows/build_wheels.yml
vendored
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@ -1,40 +0,0 @@
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name: build_wheels
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run-name: ${{ github.actor }} is building wheels
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on: [push]
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jobs:
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build_wheels:
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runs-on: ${{ matrix.os }}
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strategy:
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matrix:
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os: [ubuntu-latest, macos-latest, windows-latest]
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steps:
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- uses: actions/checkout@v2
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- name: Checkout submodules
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run: |
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git submodule update --init --recursive
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- uses: actions/setup-python@v2
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with:
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python-version: '3.10'
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- name: Setup pip
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run: |
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python -m pip install --upgrade pip
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python -m pip install cibuildwheel==1.6.4
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- name: Install
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run: |
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if [ "$RUNNER_OS" == "Linux" ]; then
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sudo apt-get update
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sudo apt-get install gcc g++
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fi
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shell: bash
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- name: Build wheel
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run: python -m cibuildwheel --output-dir dist/
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env:
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CIBW_BUILD: cp36-* cp37-* cp38-*
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- uses: actions/upload-artifact@v2
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with:
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path: ./dist/*.whl
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2
.gitignore
vendored
2
.gitignore
vendored
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@ -127,3 +127,5 @@ dmypy.json
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# Pyre type checker
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.pyre/
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whispercpp.cpp
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1
.gitmodules
vendored
1
.gitmodules
vendored
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@ -1,3 +1,4 @@
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[submodule "whisper.cpp"]
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path = whisper.cpp
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url = https://github.com/ggerganov/whisper.cpp
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branch = b2083c5d02db9a1e6dbb3d58254fd65ebfff4b5d
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26
README.md
26
README.md
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@ -1,16 +1,36 @@
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Python bindings for whisper.cpp
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===============================
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`pip install git+https://github.com/o4dev/whispercpp.py`
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```
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git clone --recurse-submodules https://git.ecker.tech/lightmare/whispercpp.py
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cd whispercpp.py
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pip install .
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```
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or
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```
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git clone https://git.ecker.tech/lightmare/whispercpp.py
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cd whispercpp.py
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git submodule update --init
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pip install .
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```
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```python
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from whispercpp import Whisper
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w = Whisper('tiny')
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w = Whisper('tiny', models_dir='./models/', language=b'en')
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result = w.transcribe("myfile.mp3")
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text = w.extract_text(result)
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```
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Note: default parameters might need to be tweaked.
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Note: default parameters might need to be tweaked.
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See Whispercpp.pyx.
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Changes made (not exhaustive):
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- changed defaults
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- whisper.cpp submodule set to 1.2.0
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- removed `requests` dependency
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- models dir can be changed in constructor
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- added support for setting params
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- added back support for `large-v1` model
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- added support for english-only models
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|
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3
requirements.txt
Normal file
3
requirements.txt
Normal file
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@ -0,0 +1,3 @@
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Cython
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numpy
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ffmpeg-python
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3
setup.py
3
setup.py
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@ -34,7 +34,6 @@ setup(
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include_dirs = ['./whisper.cpp/', numpy.get_include()],
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install_requires=[
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'numpy',
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'ffmpeg-python',
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'requests'
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'ffmpeg-python'
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],
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)
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210
whispercpp.pxd
210
whispercpp.pxd
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@ -3,111 +3,111 @@
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from libc.stdint cimport int64_t
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cdef nogil:
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int WHISPER_SAMPLE_RATE = 16000
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int WHISPER_N_FFT = 400
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int WHISPER_N_MEL = 80
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int WHISPER_HOP_LENGTH = 160
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int WHISPER_CHUNK_SIZE = 30
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int SAMPLE_RATE = 16000
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char* TEST_FILE = b'test.wav'
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char* DEFAULT_MODEL = b'ggml-tiny.bin'
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char* LANGUAGE = b'fr'
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ctypedef struct audio_data:
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float* frames;
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int n_frames;
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int WHISPER_SAMPLE_RATE = 16000
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int WHISPER_N_FFT = 400
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int WHISPER_N_MEL = 80
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int WHISPER_HOP_LENGTH = 160
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int WHISPER_CHUNK_SIZE = 30
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int SAMPLE_RATE = 16000
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char* TEST_FILE = b'test.wav'
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char* DEFAULT_MODEL = b'ggml-base.bin'
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char* LANGUAGE = b'en'
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ctypedef struct audio_data:
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float* frames;
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int n_frames;
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cdef extern from "whisper.h" nogil:
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enum whisper_sampling_strategy:
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WHISPER_SAMPLING_GREEDY = 0,
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WHISPER_SAMPLING_BEAM_SEARCH,
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ctypedef bint _Bool
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ctypedef void (*whisper_new_segment_callback)(whisper_context*, int, void*)
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ctypedef _Bool whisper_encoder_begin_callback(whisper_context*, void*)
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ctypedef int whisper_token
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ctypedef struct whisper_token_data:
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whisper_token id
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whisper_token tid
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float p
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float pt
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float ptsum
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int64_t t0
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int64_t t1
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float vlen
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ctypedef struct whisper_context:
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pass
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ctypedef struct anon_2:
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int n_past
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ctypedef struct anon_3:
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int n_past
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int beam_width
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int n_best
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ctypedef struct whisper_full_params:
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int strategy
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int n_threads
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int n_max_text_ctx
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int offset_ms
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int duration_ms
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_Bool translate
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_Bool no_context
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_Bool single_segment
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_Bool print_special
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_Bool print_progress
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_Bool print_realtime
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_Bool print_timestamps
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_Bool token_timestamps
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float thold_pt
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float thold_ptsum
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int max_len
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int max_tokens
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_Bool speed_up
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int audio_ctx
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whisper_token* prompt_tokens
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int prompt_n_tokens
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char* language
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anon_2 greedy
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anon_3 beam_search
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whisper_new_segment_callback new_segment_callback
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void* new_segment_callback_user_data
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whisper_encoder_begin_callback encoder_begin_callback
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void* encoder_begin_callback_user_data
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whisper_full_params whisper_full_default_params(whisper_sampling_strategy)
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cdef whisper_context* whisper_init(char*)
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cdef void whisper_free(whisper_context*)
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cdef int whisper_pcm_to_mel(whisper_context*, float*, int, int)
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cdef int whisper_set_mel(whisper_context*, float*, int, int)
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cdef int whisper_encode(whisper_context*, int, int)
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cdef int whisper_decode(whisper_context*, whisper_token*, int, int, int)
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cdef whisper_token_data whisper_sample_best(whisper_context*)
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cdef whisper_token whisper_sample_timestamp(whisper_context*)
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cdef int whisper_lang_id(char*)
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cdef int whisper_n_len(whisper_context*)
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cdef int whisper_n_vocab(whisper_context*)
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cdef int whisper_n_text_ctx(whisper_context*)
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cdef int whisper_is_multilingual(whisper_context*)
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cdef float* whisper_get_probs(whisper_context*)
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# Unknown CtypesSpecial name='c_char_p'
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cdef whisper_token whisper_token_eot(whisper_context*)
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cdef whisper_token whisper_token_sot(whisper_context*)
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cdef whisper_token whisper_token_prev(whisper_context*)
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cdef whisper_token whisper_token_solm(whisper_context*)
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cdef whisper_token whisper_token_not(whisper_context*)
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cdef whisper_token whisper_token_beg(whisper_context*)
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cdef whisper_token whisper_token_translate()
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cdef whisper_token whisper_token_transcribe()
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cdef void whisper_print_timings(whisper_context*)
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cdef void whisper_reset_timings(whisper_context*)
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# Unsupported base Klass='CtypesEnum'
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cdef int whisper_full(whisper_context*, whisper_full_params, float*, int)
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cdef int whisper_full_parallel(whisper_context*, whisper_full_params, float*, int, int)
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cdef int whisper_full_n_segments(whisper_context*)
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cdef int64_t whisper_full_get_segment_t0(whisper_context*, int)
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cdef int64_t whisper_full_get_segment_t1(whisper_context*, int)
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# Unknown CtypesSpecial name='c_char_p'
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cdef int whisper_full_n_tokens(whisper_context*, int)
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# Unknown CtypesSpecial name='c_char_p'
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cdef whisper_token whisper_full_get_token_id(whisper_context*, int, int)
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cdef whisper_token_data whisper_full_get_token_data(whisper_context*, int, int)
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cdef float whisper_full_get_token_p(whisper_context*, int, int)
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const char* whisper_print_system_info()
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const char* whisper_full_get_segment_text(whisper_context*, int)
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enum whisper_sampling_strategy:
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WHISPER_SAMPLING_GREEDY = 0,
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WHISPER_SAMPLING_BEAM_SEARCH,
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ctypedef bint _Bool
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ctypedef void (*whisper_new_segment_callback)(whisper_context*, int, void*)
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ctypedef _Bool whisper_encoder_begin_callback(whisper_context*, void*)
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ctypedef int whisper_token
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ctypedef struct whisper_token_data:
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whisper_token id
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whisper_token tid
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float p
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float pt
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float ptsum
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int64_t t0
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||||
int64_t t1
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float vlen
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ctypedef struct whisper_context:
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pass
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ctypedef struct anon_2:
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int n_past
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ctypedef struct anon_3:
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int n_past
|
||||
int beam_width
|
||||
int n_best
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ctypedef struct whisper_full_params:
|
||||
int strategy
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||||
int n_threads
|
||||
int n_max_text_ctx
|
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int offset_ms
|
||||
int duration_ms
|
||||
_Bool translate
|
||||
_Bool no_context
|
||||
_Bool single_segment
|
||||
_Bool print_special
|
||||
_Bool print_progress
|
||||
_Bool print_realtime
|
||||
_Bool print_timestamps
|
||||
_Bool token_timestamps
|
||||
float thold_pt
|
||||
float thold_ptsum
|
||||
int max_len
|
||||
int max_tokens
|
||||
_Bool speed_up
|
||||
int audio_ctx
|
||||
whisper_token* prompt_tokens
|
||||
int prompt_n_tokens
|
||||
char* language
|
||||
anon_2 greedy
|
||||
anon_3 beam_search
|
||||
whisper_new_segment_callback new_segment_callback
|
||||
void* new_segment_callback_user_data
|
||||
whisper_encoder_begin_callback encoder_begin_callback
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void* encoder_begin_callback_user_data
|
||||
whisper_full_params whisper_full_default_params(whisper_sampling_strategy)
|
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cdef whisper_context* whisper_init(char*)
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cdef void whisper_free(whisper_context*)
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||||
cdef int whisper_pcm_to_mel(whisper_context*, float*, int, int)
|
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cdef int whisper_set_mel(whisper_context*, float*, int, int)
|
||||
cdef int whisper_encode(whisper_context*, int, int)
|
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cdef int whisper_decode(whisper_context*, whisper_token*, int, int, int)
|
||||
cdef whisper_token_data whisper_sample_best(whisper_context*)
|
||||
cdef whisper_token whisper_sample_timestamp(whisper_context*)
|
||||
cdef int whisper_lang_id(char*)
|
||||
cdef int whisper_n_len(whisper_context*)
|
||||
cdef int whisper_n_vocab(whisper_context*)
|
||||
cdef int whisper_n_text_ctx(whisper_context*)
|
||||
cdef int whisper_is_multilingual(whisper_context*)
|
||||
cdef float* whisper_get_probs(whisper_context*)
|
||||
# Unknown CtypesSpecial name='c_char_p'
|
||||
cdef whisper_token whisper_token_eot(whisper_context*)
|
||||
cdef whisper_token whisper_token_sot(whisper_context*)
|
||||
cdef whisper_token whisper_token_prev(whisper_context*)
|
||||
cdef whisper_token whisper_token_solm(whisper_context*)
|
||||
cdef whisper_token whisper_token_not(whisper_context*)
|
||||
cdef whisper_token whisper_token_beg(whisper_context*)
|
||||
cdef whisper_token whisper_token_translate()
|
||||
cdef whisper_token whisper_token_transcribe()
|
||||
cdef void whisper_print_timings(whisper_context*)
|
||||
cdef void whisper_reset_timings(whisper_context*)
|
||||
# Unsupported base Klass='CtypesEnum'
|
||||
cdef int whisper_full(whisper_context*, whisper_full_params, float*, int)
|
||||
cdef int whisper_full_parallel(whisper_context*, whisper_full_params, float*, int, int)
|
||||
cdef int whisper_full_n_segments(whisper_context*)
|
||||
cdef int64_t whisper_full_get_segment_t0(whisper_context*, int)
|
||||
cdef int64_t whisper_full_get_segment_t1(whisper_context*, int)
|
||||
# Unknown CtypesSpecial name='c_char_p'
|
||||
cdef int whisper_full_n_tokens(whisper_context*, int)
|
||||
# Unknown CtypesSpecial name='c_char_p'
|
||||
cdef whisper_token whisper_full_get_token_id(whisper_context*, int, int)
|
||||
cdef whisper_token_data whisper_full_get_token_data(whisper_context*, int, int)
|
||||
cdef float whisper_full_get_token_p(whisper_context*, int, int)
|
||||
const char* whisper_print_system_info()
|
||||
const char* whisper_full_get_segment_text(whisper_context*, int)
|
||||
|
||||
|
|
|
|||
212
whispercpp.pyx
212
whispercpp.pyx
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|
@ -3,113 +3,167 @@
|
|||
|
||||
import ffmpeg
|
||||
import numpy as np
|
||||
import requests
|
||||
import urllib.request
|
||||
import os
|
||||
from pathlib import Path
|
||||
|
||||
MODELS_DIR = str(Path('~/.ggml-models').expanduser())
|
||||
print("Saving models to:", MODELS_DIR)
|
||||
|
||||
|
||||
cimport numpy as cnp
|
||||
|
||||
cdef int SAMPLE_RATE = 16000
|
||||
cdef char* TEST_FILE = 'test.wav'
|
||||
cdef char* DEFAULT_MODEL = 'tiny'
|
||||
cdef char* LANGUAGE = b'fr'
|
||||
cdef char* DEFAULT_MODEL = 'base'
|
||||
cdef char* LANGUAGE = b'en'
|
||||
cdef int N_THREADS = os.cpu_count()
|
||||
cdef _Bool PRINT_REALTIME = False
|
||||
cdef _Bool PRINT_PROGRESS = False
|
||||
cdef _Bool TRANSLATE = False
|
||||
|
||||
|
||||
MODELS = {
|
||||
'ggml-tiny.bin': 'https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-tiny.bin',
|
||||
'ggml-base.bin': 'https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-base.bin',
|
||||
'ggml-small.bin': 'https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-small.bin',
|
||||
'ggml-medium.bin': 'https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-medium.bin',
|
||||
'ggml-large.bin': 'https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-large.bin',
|
||||
'ggml-tiny.bin': 'https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-tiny.bin',
|
||||
'ggml-tiny.en.bin': 'https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-tiny.en.bin',
|
||||
'ggml-base.bin': 'https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-base.bin',
|
||||
'ggml-base.en.bin': 'https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin',
|
||||
'ggml-small.bin': 'https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-small.bin',
|
||||
'ggml-small.en.bin': 'https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-small.en.bin',
|
||||
'ggml-medium.bin': 'https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-medium.bin',
|
||||
'ggml-medium.en.bin': 'https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-medium.en.bin',
|
||||
'ggml-large-v1.bin': 'https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-large-v1.bin',
|
||||
'ggml-large.bin': 'https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-large.bin',
|
||||
}
|
||||
|
||||
def model_exists(model):
|
||||
return os.path.exists(Path(MODELS_DIR).joinpath(model))
|
||||
def model_exists(model, models_dir=MODELS_DIR):
|
||||
return os.path.exists(Path(models_dir).joinpath(model))
|
||||
|
||||
def download_model(model):
|
||||
if model_exists(model):
|
||||
return
|
||||
def download_model(model, models_dir=MODELS_DIR):
|
||||
"""Downloads ggml model with the given identifier
|
||||
|
||||
print(f'Downloading {model}...')
|
||||
url = MODELS[model]
|
||||
r = requests.get(url, allow_redirects=True)
|
||||
os.makedirs(MODELS_DIR, exist_ok=True)
|
||||
with open(Path(MODELS_DIR).joinpath(model), 'wb') as f:
|
||||
f.write(r.content)
|
||||
The filenames mirror the ones given in ggerganov's repos.
|
||||
e.g. 'small' becomes 'ggml-small.bin'
|
||||
|
||||
Args:
|
||||
model: The model identifier
|
||||
models_dir: The path where the file is written to
|
||||
"""
|
||||
if model_exists(model, models_dir=models_dir):
|
||||
return
|
||||
|
||||
print(f'Downloading {model} to {models_dir}...')
|
||||
url = MODELS[model]
|
||||
os.makedirs(models_dir, exist_ok=True)
|
||||
with urllib.request.urlopen(url) as r:
|
||||
with open(Path(models_dir).joinpath(model), 'wb') as f:
|
||||
f.write(r.read())
|
||||
|
||||
|
||||
cdef cnp.ndarray[cnp.float32_t, ndim=1, mode="c"] load_audio(bytes file, int sr = SAMPLE_RATE):
|
||||
try:
|
||||
out = (
|
||||
ffmpeg.input(file, threads=0)
|
||||
.output(
|
||||
"-", format="s16le",
|
||||
acodec="pcm_s16le",
|
||||
ac=1, ar=sr
|
||||
)
|
||||
.run(
|
||||
cmd=["ffmpeg", "-nostdin"],
|
||||
capture_stdout=True,
|
||||
capture_stderr=True
|
||||
)
|
||||
)[0]
|
||||
except:
|
||||
raise RuntimeError(f"File '{file}' not found")
|
||||
try:
|
||||
out = (
|
||||
ffmpeg.input(file, threads=0)
|
||||
.output(
|
||||
"-", format="s16le",
|
||||
acodec="pcm_s16le",
|
||||
ac=1, ar=sr
|
||||
)
|
||||
.run(
|
||||
cmd=["ffmpeg", "-nostdin"],
|
||||
capture_stdout=True,
|
||||
capture_stderr=True
|
||||
)
|
||||
)[0]
|
||||
except Exception:
|
||||
raise RuntimeError(f"File '{file}' not found")
|
||||
|
||||
cdef cnp.ndarray[cnp.float32_t, ndim=1, mode="c"] frames = (
|
||||
np.frombuffer(out, np.int16)
|
||||
.flatten()
|
||||
.astype(np.float32)
|
||||
) / pow(2, 15)
|
||||
cdef cnp.ndarray[cnp.float32_t, ndim=1, mode="c"] frames = (
|
||||
np.frombuffer(out, np.int16)
|
||||
.flatten()
|
||||
.astype(np.float32)
|
||||
) / pow(2, 15)
|
||||
|
||||
return frames
|
||||
|
||||
cdef whisper_full_params default_params() nogil:
|
||||
cdef whisper_full_params params = whisper_full_default_params(
|
||||
whisper_sampling_strategy.WHISPER_SAMPLING_GREEDY
|
||||
)
|
||||
params.print_realtime = True
|
||||
params.print_progress = True
|
||||
params.translate = False
|
||||
params.language = <const char *> LANGUAGE
|
||||
n_threads = N_THREADS
|
||||
return params
|
||||
return frames
|
||||
|
||||
cdef whisper_full_params set_params(_Bool print_realtime, _Bool print_progress, _Bool translate, char* language, int n_threads) nogil:
|
||||
cdef whisper_full_params params = whisper_full_default_params(
|
||||
whisper_sampling_strategy.WHISPER_SAMPLING_GREEDY
|
||||
)
|
||||
params.print_realtime = print_realtime
|
||||
params.print_progress = print_progress
|
||||
params.translate = translate
|
||||
params.language = <const char *> language
|
||||
n_threads = n_threads
|
||||
return params
|
||||
|
||||
cdef class Whisper:
|
||||
cdef whisper_context * ctx
|
||||
cdef whisper_full_params params
|
||||
cdef whisper_context * ctx
|
||||
cdef whisper_full_params params
|
||||
|
||||
def __init__(self, model=DEFAULT_MODEL, pb=None):
|
||||
model_fullname = f'ggml-{model}.bin'.encode('utf8')
|
||||
download_model(model_fullname)
|
||||
model_path = Path(MODELS_DIR).joinpath(model_fullname)
|
||||
cdef bytes model_b = str(model_path).encode('utf8')
|
||||
self.ctx = whisper_init(model_b)
|
||||
self.params = default_params()
|
||||
whisper_print_system_info()
|
||||
def __init__(self, model = DEFAULT_MODEL, models_dir = MODELS_DIR, _Bool print_realtime = PRINT_REALTIME, _Bool print_progress = PRINT_PROGRESS, _Bool translate = TRANSLATE, char* language = LANGUAGE, int n_threads = N_THREADS, _Bool print_system_info = False): # not pretty, look for a way to use kwargs?
|
||||
"""Constructor for Whisper class.
|
||||
|
||||
def __dealloc__(self):
|
||||
whisper_free(self.ctx)
|
||||
Automatically checks for model and downloads it if necessary.
|
||||
|
||||
def transcribe(self, filename=TEST_FILE):
|
||||
print("Loading data..")
|
||||
cdef cnp.ndarray[cnp.float32_t, ndim=1, mode="c"] frames = load_audio(<bytes>filename)
|
||||
Args:
|
||||
model: Model identifier, e.g. 'base' (see MODELS)
|
||||
models_dir: The path where the models should be stored
|
||||
print_realtime: whisper.cpp's real time transcription output
|
||||
print_progress: whisper.cpp's progress indicator
|
||||
translate: whisper.cpp's translation option
|
||||
language: Which language to use. Must be a byte string.
|
||||
n_threads: Amount of threads to use
|
||||
print_system_info: whisper.cpp's system info output
|
||||
"""
|
||||
model_fullname = f'ggml-{model}.bin' #.encode('utf8')
|
||||
download_model(model_fullname, models_dir=models_dir)
|
||||
model_path = Path(models_dir).joinpath(model_fullname)
|
||||
cdef bytes model_b = str(model_path).encode('utf8')
|
||||
self.ctx = whisper_init(model_b)
|
||||
self.params = set_params(print_realtime, print_progress, translate, language, n_threads)
|
||||
if print_system_info:
|
||||
whisper_print_system_info()
|
||||
|
||||
print("Transcribing..")
|
||||
return whisper_full(self.ctx, self.params, &frames[0], len(frames))
|
||||
|
||||
def extract_text(self, int res):
|
||||
print("Extracting text...")
|
||||
if res != 0:
|
||||
raise RuntimeError
|
||||
cdef int n_segments = whisper_full_n_segments(self.ctx)
|
||||
return [
|
||||
whisper_full_get_segment_text(self.ctx, i).decode() for i in range(n_segments)
|
||||
]
|
||||
def __dealloc__(self):
|
||||
whisper_free(self.ctx)
|
||||
|
||||
def transcribe(self, filename = TEST_FILE):
|
||||
"""Transcribes from given file.
|
||||
|
||||
Args:
|
||||
filename: Path to file
|
||||
|
||||
Returns:
|
||||
A result id for extract_text(...)
|
||||
|
||||
Raises:
|
||||
RuntimeError: The given file could not be found
|
||||
"""
|
||||
|
||||
#print(f"Loading data from '{filename}'...")
|
||||
cdef cnp.ndarray[cnp.float32_t, ndim=1, mode="c"] frames = load_audio(<bytes>filename)
|
||||
|
||||
#print("Transcribing..")
|
||||
return whisper_full(self.ctx, self.params, &frames[0], len(frames))
|
||||
|
||||
def extract_text(self, int res):
|
||||
"""Extracts the text from a transcription.
|
||||
|
||||
Args:
|
||||
res: A result id from transcribe(...)
|
||||
|
||||
Results:
|
||||
A list of transcribed strings.
|
||||
|
||||
Raises:
|
||||
RuntimeError: The given result id was invalid.
|
||||
"""
|
||||
#print("Extracting text...")
|
||||
if res != 0:
|
||||
raise RuntimeError
|
||||
cdef int n_segments = whisper_full_n_segments(self.ctx)
|
||||
return [
|
||||
whisper_full_get_segment_text(self.ctx, i).decode() for i in range(n_segments)
|
||||
]
|
||||
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user