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examples/cpp_libtorch/README.md
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examples/cpp_libtorch/README.md
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This is the source code for Silero-VAD V5 in C++, based on LibTorch.
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The primary implementation is the CPU version, and you should compare its results with the Python version.
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I only checked the 16kHz results.
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In addition, Batch and CUDA inference options are also available if you want to explore further.
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Note that when using batch inference, the speech probabilities might slightly differ from the standard version, likely due to differences in caching.
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Unlike processing individual inputs, batch inference may not be able to use the cache from previous chunks.
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Nevertheless, batch inference provides significantly faster processing.
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For optimal performance, carefully adjust the threshold when using batch inference.
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#Requirements:
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GCC 11.4.0 (GCC >= 5.1)
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LibTorch 1.13.0(Other versions are also acceptable)
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#Download Libtorch:
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*cpu
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$wget https://download.pytorch.org/libtorch/cpu/libtorch-shared-with-deps-1.13.0%2Bcpu.zip
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$unzip libtorch-shared-with-deps-1.13.0+cpu.zip
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*cuda
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$wget https://download.pytorch.org/libtorch/cu116/libtorch-shared-with-deps-1.13.0%2Bcu116.zip
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$unzip libtorch-shared-with-deps-1.13.0+cu116.zip
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#complie:
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*cpu
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$g++ main.cc silero_torch.cc -I ./libtorch/include/ -I ./libtorch/include/torch/csrc/api/include -L ./libtorch/lib/ -ltorch -ltorch_cpu -lc10 -Wl,-rpath,./libtorch/lib/ -o silero -std=c++14 -D_GLIBCXX_USE_CXX11_ABI=0
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*cuda
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$g++ main.cc silero_torch.cc -I ./libtorch/include/ -I ./libtorch/include/torch/csrc/api/include -L ./libtorch/lib/ -ltorch -ltorch_cuda -ltorch_cpu -lc10 -Wl,-rpath,./libtorch/lib/ -o silero -std=c++14 -D_GLIBCXX_USE_CXX11_ABI=0 -DUSE_GPU
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*option to add
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-DUSE_BATCH
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-DUSE_GPU
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# Run:
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./silero aepyx.wav 16000 0.5 #The sample file 'aepyx.wav' is part of the Voxconverse dataset.
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#aepyx.wav : 16kHz, 16-bit
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