mirror of
https://github.com/chidiwilliams/buzz.git
synced 2024-06-08 03:02:12 +02:00
Add stable-ts as Python dependency (#186)
This commit is contained in:
Chidi Williams
GitHub
parent
06abf0bf36
commit
be73a0d490
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@ -2,7 +2,6 @@
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omit =
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whisper_cpp.py
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*_test.py
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stable_ts/*
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[html]
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directory = coverage/html
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9
.github/workflows/ci.yml
vendored
9
.github/workflows/ci.yml
vendored
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@ -55,7 +55,9 @@ jobs:
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with:
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token: ${{ secrets.GITHUB_TOKEN }}
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- run: poetry install
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- name: Install dependencies
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run: poetry config experimental.new-installer false && poetry install
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- name: Test
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run: poetry run make test
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@ -93,7 +95,9 @@ jobs:
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with:
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token: ${{ secrets.GITHUB_TOKEN }}
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- run: poetry install
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- name: Install dependencies
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run: poetry config experimental.new-installer false && poetry install
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- name: Bundle
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run: |
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if [ "$RUNNER_OS" == "macOS" ]; then
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@ -106,6 +110,7 @@ jobs:
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env:
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BUZZ_VERSION: ${{ github.ref_name }}
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shell: bash
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- uses: actions/upload-artifact@v3
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with:
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name: Buzz-${{ runner.os }}
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4
.gitmodules
vendored
4
.gitmodules
vendored
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@ -1,7 +1,3 @@
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[submodule "whisper.cpp"]
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path = whisper.cpp
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url = https://github.com/chidiwilliams/whisper.cpp
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[submodule "stable_ts"]
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path = stable_ts
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url = https://github.com/chidiwilliams/stable-ts
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branch = main
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76
poetry.lock
generated
76
poetry.lock
generated
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@ -311,7 +311,7 @@ setuptools = "*"
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[[package]]
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name = "numpy"
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version = "1.23.4"
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version = "1.23.5"
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description = "NumPy is the fundamental package for array computing with Python."
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category = "main"
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optional = false
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@ -632,6 +632,17 @@ CFFI = ">=1.0"
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[package.extras]
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numpy = ["NumPy"]
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[[package]]
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name = "stable-ts"
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version = "1.0.1"
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description = "Stabilizing timestamps of OpenAI's Whisper outputs down to word-level."
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category = "main"
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optional = false
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python-versions = ">=3.7"
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[package.dependencies]
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whisper = "*"
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[[package]]
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name = "tokenizers"
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version = "0.13.2"
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@ -820,7 +831,7 @@ dev = ["pytest"]
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type = "git"
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url = "https://github.com/openai/whisper.git"
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reference = "HEAD"
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resolved_reference = "9f70a352f9f8630ab3aa0d06af5cb9532bd8c21d"
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resolved_reference = "eff383b27b783e280c089475852ba83f20f64998"
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[[package]]
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name = "wrapt"
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@ -833,7 +844,7 @@ python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7"
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[metadata]
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lock-version = "1.1"
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python-versions = ">=3.9.13,<3.11"
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content-hash = "39e8e23bd707e141380bf675d7070a6a38899b607ae2246770903fab5cbd5c4e"
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content-hash = "7c3eff2da73e940a62a1da06a9310c26e599d4035c22004399c80d6304abe8e9"
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[metadata.files]
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altgraph = [
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@ -1079,34 +1090,34 @@ nodeenv = [
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{file = "nodeenv-1.7.0.tar.gz", hash = "sha256:e0e7f7dfb85fc5394c6fe1e8fa98131a2473e04311a45afb6508f7cf1836fa2b"},
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]
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numpy = [
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{file = "numpy-1.23.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:95d79ada05005f6f4f337d3bb9de8a7774f259341c70bc88047a1f7b96a4bcb2"},
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{file = "numpy-1.23.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:926db372bc4ac1edf81cfb6c59e2a881606b409ddc0d0920b988174b2e2a767f"},
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{file = "numpy-1.23.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c237129f0e732885c9a6076a537e974160482eab8f10db6292e92154d4c67d71"},
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{file = "numpy-1.23.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a8365b942f9c1a7d0f0dc974747d99dd0a0cdfc5949a33119caf05cb314682d3"},
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{file = "numpy-1.23.4-cp310-cp310-win32.whl", hash = "sha256:2341f4ab6dba0834b685cce16dad5f9b6606ea8a00e6da154f5dbded70fdc4dd"},
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{file = "numpy-1.23.4-cp310-cp310-win_amd64.whl", hash = "sha256:d331afac87c92373826af83d2b2b435f57b17a5c74e6268b79355b970626e329"},
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{file = "numpy-1.23.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:488a66cb667359534bc70028d653ba1cf307bae88eab5929cd707c761ff037db"},
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{file = "numpy-1.23.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:ce03305dd694c4873b9429274fd41fc7eb4e0e4dea07e0af97a933b079a5814f"},
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{file = "numpy-1.23.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8981d9b5619569899666170c7c9748920f4a5005bf79c72c07d08c8a035757b0"},
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{file = "numpy-1.23.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7a70a7d3ce4c0e9284e92285cba91a4a3f5214d87ee0e95928f3614a256a1488"},
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{file = "numpy-1.23.4-cp311-cp311-win32.whl", hash = "sha256:5e13030f8793e9ee42f9c7d5777465a560eb78fa7e11b1c053427f2ccab90c79"},
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{file = "numpy-1.23.4-cp311-cp311-win_amd64.whl", hash = "sha256:7607b598217745cc40f751da38ffd03512d33ec06f3523fb0b5f82e09f6f676d"},
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{file = "numpy-1.23.4-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:7ab46e4e7ec63c8a5e6dbf5c1b9e1c92ba23a7ebecc86c336cb7bf3bd2fb10e5"},
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{file = "numpy-1.23.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:a8aae2fb3180940011b4862b2dd3756616841c53db9734b27bb93813cd79fce6"},
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{file = "numpy-1.23.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8c053d7557a8f022ec823196d242464b6955a7e7e5015b719e76003f63f82d0f"},
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{file = "numpy-1.23.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a0882323e0ca4245eb0a3d0a74f88ce581cc33aedcfa396e415e5bba7bf05f68"},
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{file = "numpy-1.23.4-cp38-cp38-win32.whl", hash = "sha256:dada341ebb79619fe00a291185bba370c9803b1e1d7051610e01ed809ef3a4ba"},
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{file = "numpy-1.23.4-cp38-cp38-win_amd64.whl", hash = "sha256:0fe563fc8ed9dc4474cbf70742673fc4391d70f4363f917599a7fa99f042d5a8"},
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{file = "numpy-1.23.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:c67b833dbccefe97cdd3f52798d430b9d3430396af7cdb2a0c32954c3ef73894"},
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{file = "numpy-1.23.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f76025acc8e2114bb664294a07ede0727aa75d63a06d2fae96bf29a81747e4a7"},
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{file = "numpy-1.23.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:12ac457b63ec8ded85d85c1e17d85efd3c2b0967ca39560b307a35a6703a4735"},
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{file = "numpy-1.23.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:95de7dc7dc47a312f6feddd3da2500826defdccbc41608d0031276a24181a2c0"},
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{file = "numpy-1.23.4-cp39-cp39-win32.whl", hash = "sha256:f2f390aa4da44454db40a1f0201401f9036e8d578a25f01a6e237cea238337ef"},
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{file = "numpy-1.23.4-cp39-cp39-win_amd64.whl", hash = "sha256:f260da502d7441a45695199b4e7fd8ca87db659ba1c78f2bbf31f934fe76ae0e"},
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{file = "numpy-1.23.4-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:61be02e3bf810b60ab74e81d6d0d36246dbfb644a462458bb53b595791251911"},
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{file = "numpy-1.23.4-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:296d17aed51161dbad3c67ed6d164e51fcd18dbcd5dd4f9d0a9c6055dce30810"},
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{file = "numpy-1.23.4-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:4d52914c88b4930dafb6c48ba5115a96cbab40f45740239d9f4159c4ba779962"},
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{file = "numpy-1.23.4.tar.gz", hash = "sha256:ed2cc92af0efad20198638c69bb0fc2870a58dabfba6eb722c933b48556c686c"},
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{file = "numpy-1.23.5-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:9c88793f78fca17da0145455f0d7826bcb9f37da4764af27ac945488116efe63"},
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{file = "numpy-1.23.5-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e9f4c4e51567b616be64e05d517c79a8a22f3606499941d97bb76f2ca59f982d"},
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{file = "numpy-1.23.5-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7903ba8ab592b82014713c491f6c5d3a1cde5b4a3bf116404e08f5b52f6daf43"},
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{file = "numpy-1.23.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5e05b1c973a9f858c74367553e236f287e749465f773328c8ef31abe18f691e1"},
|
||||
{file = "numpy-1.23.5-cp310-cp310-win32.whl", hash = "sha256:522e26bbf6377e4d76403826ed689c295b0b238f46c28a7251ab94716da0b280"},
|
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{file = "numpy-1.23.5-cp310-cp310-win_amd64.whl", hash = "sha256:dbee87b469018961d1ad79b1a5d50c0ae850000b639bcb1b694e9981083243b6"},
|
||||
{file = "numpy-1.23.5-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:ce571367b6dfe60af04e04a1834ca2dc5f46004ac1cc756fb95319f64c095a96"},
|
||||
{file = "numpy-1.23.5-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:56e454c7833e94ec9769fa0f86e6ff8e42ee38ce0ce1fa4cbb747ea7e06d56aa"},
|
||||
{file = "numpy-1.23.5-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5039f55555e1eab31124a5768898c9e22c25a65c1e0037f4d7c495a45778c9f2"},
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{file = "numpy-1.23.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:58f545efd1108e647604a1b5aa809591ccd2540f468a880bedb97247e72db387"},
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{file = "numpy-1.23.5-cp311-cp311-win32.whl", hash = "sha256:b2a9ab7c279c91974f756c84c365a669a887efa287365a8e2c418f8b3ba73fb0"},
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{file = "numpy-1.23.5-cp311-cp311-win_amd64.whl", hash = "sha256:0cbe9848fad08baf71de1a39e12d1b6310f1d5b2d0ea4de051058e6e1076852d"},
|
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{file = "numpy-1.23.5-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:f063b69b090c9d918f9df0a12116029e274daf0181df392839661c4c7ec9018a"},
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{file = "numpy-1.23.5-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:0aaee12d8883552fadfc41e96b4c82ee7d794949e2a7c3b3a7201e968c7ecab9"},
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{file = "numpy-1.23.5-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:92c8c1e89a1f5028a4c6d9e3ccbe311b6ba53694811269b992c0b224269e2398"},
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{file = "numpy-1.23.5-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d208a0f8729f3fb790ed18a003f3a57895b989b40ea4dce4717e9cf4af62c6bb"},
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{file = "numpy-1.23.5-cp38-cp38-win32.whl", hash = "sha256:06005a2ef6014e9956c09ba07654f9837d9e26696a0470e42beedadb78c11b07"},
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{file = "numpy-1.23.5-cp38-cp38-win_amd64.whl", hash = "sha256:ca51fcfcc5f9354c45f400059e88bc09215fb71a48d3768fb80e357f3b457e1e"},
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{file = "numpy-1.23.5-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:8969bfd28e85c81f3f94eb4a66bc2cf1dbdc5c18efc320af34bffc54d6b1e38f"},
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{file = "numpy-1.23.5-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a7ac231a08bb37f852849bbb387a20a57574a97cfc7b6cabb488a4fc8be176de"},
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{file = "numpy-1.23.5-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bf837dc63ba5c06dc8797c398db1e223a466c7ece27a1f7b5232ba3466aafe3d"},
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{file = "numpy-1.23.5-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:33161613d2269025873025b33e879825ec7b1d831317e68f4f2f0f84ed14c719"},
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{file = "numpy-1.23.5-cp39-cp39-win32.whl", hash = "sha256:af1da88f6bc3d2338ebbf0e22fe487821ea4d8e89053e25fa59d1d79786e7481"},
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{file = "numpy-1.23.5-cp39-cp39-win_amd64.whl", hash = "sha256:09b7847f7e83ca37c6e627682f145856de331049013853f344f37b0c9690e3df"},
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{file = "numpy-1.23.5-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:abdde9f795cf292fb9651ed48185503a2ff29be87770c3b8e2a14b0cd7aa16f8"},
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{file = "numpy-1.23.5-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f9a909a8bae284d46bbfdefbdd4a262ba19d3bc9921b1e76126b1d21c3c34135"},
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{file = "numpy-1.23.5-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:01dd17cbb340bf0fc23981e52e1d18a9d4050792e8fb8363cecbf066a84b827d"},
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{file = "numpy-1.23.5.tar.gz", hash = "sha256:1b1766d6f397c18153d40015ddfc79ddb715cabadc04d2d228d4e5a8bc4ded1a"},
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]
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packaging = [
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{file = "packaging-21.3-py3-none-any.whl", hash = "sha256:ef103e05f519cdc783ae24ea4e2e0f508a9c99b2d4969652eed6a2e1ea5bd522"},
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@ -1365,6 +1376,9 @@ sounddevice = [
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{file = "sounddevice-0.4.5-py3-none-win_amd64.whl", hash = "sha256:d3216c5d3d678c3301058e9aac7000879e255140c524c9ef98730091b67ea676"},
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{file = "sounddevice-0.4.5.tar.gz", hash = "sha256:2fe0d41299e4f3037dad2acede4eff0666b34a1fa3da5335e47120373964bef5"},
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]
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stable-ts = [
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{file = "stable-ts-1.0.1.tar.gz", hash = "sha256:8242952db389043fc7715f78949d0f3f3df420912c609dca5d7bd7d25d85689d"},
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]
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tokenizers = [
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{file = "tokenizers-0.13.2-cp310-cp310-macosx_10_11_x86_64.whl", hash = "sha256:a6f36b1b499233bb4443b5e57e20630c5e02fba61109632f5e00dab970440157"},
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{file = "tokenizers-0.13.2-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:bc6983282ee74d638a4b6d149e5dadd8bc7ff1d0d6de663d69f099e0c6bddbeb"},
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@ -11,12 +11,12 @@ python = ">=3.9.13,<3.11"
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sounddevice = "^0.4.5"
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whisper = { git = "https://github.com/openai/whisper.git" }
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torch = "1.12.1"
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numpy = "^1.23.3"
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transformers = "^4.22.1"
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appdirs = "^1.4.4"
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ffmpeg-python = "^0.2.0"
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humanize = "^4.4.0"
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PyQt6 = "^6.4.0"
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stable-ts = "^1.0.1"
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[tool.poetry.group.dev.dependencies]
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autopep8 = "^1.7.0"
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@ -1 +0,0 @@
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Subproject commit 5c1966392b0a67b79a454d3f902772a2d9085d77
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@ -14,11 +14,11 @@ from typing import Callable, List, Optional
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import numpy as np
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import sounddevice
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import stable_whisper
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import whisper
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from sounddevice import PortAudioError
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from conn import pipe_stderr, pipe_stdout
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from stable_ts.stable_whisper import group_word_timestamps, modify_model
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from whispr import (ModelLoader, Segment, Stopped, Task, WhisperCpp,
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read_progress, whisper_cpp_params)
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@ -363,12 +363,14 @@ def transcribe_whisper(
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model = whisper.load_model(model_path)
|
||||
|
||||
if word_level_timings:
|
||||
modify_model(model)
|
||||
stable_whisper.modify_model(model)
|
||||
result = model.transcribe(
|
||||
audio=file_path, language=language, task=task.value, pbar=True)
|
||||
else:
|
||||
result = model.transcribe(
|
||||
audio=file_path, language=language, task=task.value, verbose=False)
|
||||
|
||||
result = model.transcribe(
|
||||
audio=file_path, language=language, task=task.value, verbose=False)
|
||||
|
||||
whisper_segments = group_word_timestamps(
|
||||
whisper_segments = stable_whisper.group_word_timestamps(
|
||||
result) if word_level_timings else result.get('segments')
|
||||
|
||||
segments = map(
|
||||
|
|
|
|||
|
|
@ -36,7 +36,7 @@ class TestFileTranscriber:
|
|||
(False, OutputFormat.TXT, 'Bienvenue dans Passe-Relle, un podcast'),
|
||||
(False, OutputFormat.SRT, '1\n00:00:00.000 --> 00:00:06.560\n Bienvenue dans Passe-Relle, un podcast pensé pour évêyer la curiosité des apprenances'),
|
||||
(False, OutputFormat.VTT, 'WEBVTT\n\n00:00:00.000 --> 00:00:06.560\n Bienvenue dans Passe-Relle, un podcast pensé pour évêyer la curiosité des apprenances'),
|
||||
(True, OutputFormat.SRT, '1\n00:00:00.040 --> 00:00:00.059\n Bienvenue\n\n2\n00:00:00.059 --> 00:00:00.359\n dans P'),
|
||||
(True, OutputFormat.SRT, '1\n00:00:00.040 --> 00:00:00.359\n Bienvenue dans\n\n2\n00:00:00.359 --> 00:00:00.419\n Passe-'),
|
||||
])
|
||||
def test_transcribe_whisper(self, tmp_path: pathlib.Path, word_level_timings: bool, output_format: OutputFormat, output_text: str):
|
||||
output_file_path = tmp_path / f'whisper.{output_format.value.lower()}'
|
||||
|
|
|
|||
Loading…
Reference in a new issue