Piper Tts Docker Image
Jetson平台上的文本转语音(TTS) Docker镜像,基于Piper TTS引擎,支持CUDA/GPU加速,依赖CUDA、cuDNN、TensorRT等组件,适用于嵌入式设备的高效语音合成应用。
piper-tts
CONTAINERSIMAGESRUNBUILD
CONTAINERS
piper-tts | |
|---|---|
| Requires | L4T ['>=32.6'] |
| Dependencies | https://github.com/dusty-nv/jetson-containers/tree/master/packages/build/build-essential https://github.com/dusty-nv/jetson-containers/tree/master/packages/cuda/cuda https://github.com/dusty-nv/jetson-containers/tree/master/packages/cuda/cudnn https://github.com/dusty-nv/jetson-containers/tree/master/packages/build/python https://github.com/dusty-nv/jetson-containers/tree/master/packages/tensorrt https://github.com/dusty-nv/jetson-containers/tree/master/packages/build/cmake/cmake_pip https://github.com/dusty-nv/jetson-containers/tree/master/packages/numpy https://github.com/dusty-nv/jetson-containers/tree/master/packages/onnx https://github.com/dusty-nv/jetson-containers/tree/master/packages/onnxruntime |
| Dependants | https://github.com/dusty-nv/jetson-containers/tree/master/packages/smart-home/wyoming/piper |
| Dockerfile | https://github.com/dusty-nv/jetson-containers/tree/master/packages/audio/piper-tts/Dockerfile |
| Images | https://hub.docker.com/r/dustynv/piper-tts/tags (2024-04-07, 5.5GB)https://hub.docker.com/r/dustynv/piper-tts/tags (2024-04-07, 6.7GB) |
CONTAINER IMAGES
| Repository/Tag | Date | Arch | Size |
|---|---|---|---|
| https://hub.docker.com/r/dustynv/piper-tts/tags | 2024-04-07 | arm64 | 5.5GB |
| https://hub.docker.com/r/dustynv/piper-tts/tags | 2024-04-07 | arm64 | 6.7GB |
Container images are compatible with other minor versions of JetPack/L4T:
• L4T R32.7 containers can run on other versions of L4T R32.7 (JetPack 4.6+)
• L4T R35.x containers can run on other versions of L4T R35.x (JetPack 5.1+)
RUN CONTAINER
To start the container, you can use https://github.com/dusty-nv/jetson-containers/tree/master/docs/run.md and https://github.com/dusty-nv/jetson-containers/tree/master/docs/run.md#autotag, or manually put together a https://docs.docker.com/engine/reference/commandline/run/ command:
bash# automatically pull or build a compatible container image jetson-containers run $(autotag piper-tts) # or explicitly specify one of the container images above jetson-containers run dustynv/piper-tts:r36.2.0 # or if using 'docker run' (specify image and mounts/ect) sudo docker run --runtime nvidia -it --rm --network=host dustynv/piper-tts:r36.2.0
https://github.com/dusty-nv/jetson-containers/tree/master/docs/run.md forwards arguments to https://docs.docker.com/engine/reference/commandline/run/ with some defaults added (like
--runtime nvidia, mounts a/datacache, and detects devices)
https://github.com/dusty-nv/jetson-containers/tree/master/docs/run.md#autotag finds a container image that's compatible with your version of JetPack/L4T - either locally, pulled from a registry, or by building it.
To mount your own directories into the container, use the https://docs.docker.com/engine/reference/commandline/run/#volume or https://docs.docker.com/engine/reference/commandline/run/#volume flags:
bashjetson-containers run -v /path/on/host:/path/in/container $(autotag piper-tts)
To launch the container running a command, as opposed to an interactive shell:
bashjetson-containers run $(autotag piper-tts) my_app --abc xyz
You can pass any options to it that you would to https://docs.docker.com/engine/reference/commandline/run/, and it'll print out the full command that it constructs before executing it.
BUILD CONTAINER
If you use https://github.com/dusty-nv/jetson-containers/tree/master/docs/run.md#autotag as shown above, it'll ask to build the container for you if needed. To manually build it, first do the https://github.com/dusty-nv/jetson-containers/tree/master/docs/setup.md, then run:
bashjetson-containers build piper-tts
The dependencies from above will be built into the container, and it'll be tested during. Run it with https://github.com/dusty-nv/jetson-containers/tree/master/jetson_containers/build.py for build options.
dustynv 命名空间的其他可用镜像:
dustynv/vllm
dustynv/ollama
dustynv/ros
dustynv/jetson-inference
dustynv/l4t-pytorch
dustynv/transformers
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