Denoiser
Phonexia denoiser is a tool for removing noises and other disturbing elements from audio recordings.
Versioning
We use Semantic Versioning.
Quick reference
- Maintained by Phonexia
- Contact us via e-mail, or open a ticket at the Phonexia Service Desk
- File an issue
- See list of licenses
- See the terms of use
How to use this image
Getting the image
You can easily obtain the docker image from docker hub. Just run:
docker pull phonexia/denoiser:latest
Running the image
The preferred way to deploy microservice to a production environment is to use Helm Chart. See the Helm chart deployment for more information.
Docker
You can start the microservice and list all the supported options by running:
docker run --rm -it phonexia/denoiser:latest --help
The output should look like this:
Usage: denoiser [OPTIONS]
Options:
-h,--help Print this help message and exit
-m,--model file REQUIRED (Env:PHX_MODEL_PATH)
Path to a model file.
-k,--license_key string REQUIRED (Env:PHX_LICENSE_KEY)
License key.
-a,--listening_address address [[::]] (Env:PHX_LISTENING_ADDRESS)
Address on which the server will be listening. Address '[::]' also accepts IPv4 connections.
-p,--port number [8080] (Env:PHX_PORT)
Port on which the server will be listening.
-l,--log_level level:{error,warning,info,debug,trace} [info] (Env:PHX_LOG_LEVEL)
Logging level. Possible values: error, warning, info, debug, trace.
--keepalive_time_s number:[0, max_int] [60] (Env:PHX_KEEPALIVE_TIME_S)
Time between 2 consecutive keep-alive messages, that are sent if there is no activity from the client. If set to 0, the default gRPC configuration (2hr) will be set (note, that this may get the microservice into unresponsive state).
--keepalive_timeout_s number:[1, max int] [20] (Env:PHX_KEEPALIVE_TIMEOUT_S)
Time to wait for keep alive acknowledgement until the connection is dropped by the server.
--num_instances_per_device NUM:UINT > 0 (Env:PHX_NUM_INSTANCES_PER_DEVICE)
Number of instances per device. Microservice can process requests concurrently if value is >1.
Note that the model and license_key options are required. To obtain the model and license, contact Phonexia.
You can specify the options either via command line arguments or via environmental variables.
Run the container with the mandatory parameters:
docker run --rm -it -v /opt/phx/models:/models -p 8080:8080 /phonexia/denoiser:latest --model /models/denoiser-generic-1.0.0.model --license_key ${license-key}
Replace the /opt/phx/models
, denoiser-generic-1.0.0.model
and license-key
with the corresponding values.
With this command, the container will start, and the microservice will be listening on port 8080 on localhost.
Docker compose
Create a docker-compose.yml
file:
version: '3'
services:
denoiser:
image: phonexia/denoiser:latest
environment:
- PHX_MODEL_PATH=/models/denoiser-generic-1.0.0.model
- PHX_LICENSE_KEY=<license-key>
ports:
- 8080:8080
volumes:
- ./models:/models/
Create a models
folder in the same directory as the docker-compose.yml
file and place a model file in it. Replace <license-key>
with your license key and denoiser-generic-1.0.0.model
with the actual name of a model.
Run a microservice:
$ docker compose up
Microservice communication
gRPC API
For communication, our microservices use gRPC, which is a high-performance, open-source Remote
Procedure Call (RPC
) framework that enables efficient communication between distributed systems using a variety of programming languages. We use an interface definition language to specify a common interface and contracts between components. This is primarily achieved by specifying methods with parameters and return types.
Take a look at our gRPC API documentation. The denoiser microservice defines a Denoiser
service with remote procedure called Denoise
. This procedure accepts an argument (also referred to as "message") called DenoiseRequest
, which contains the audio as an array of byte.
This DenoiseRequest
argument is streamed, meaning that it may be received in multiple requests, each containing a part of the audio. The Denoise
procedure returns a message called DenoiseResponse
which consists of the denoised audio. As well as DenoiseRequest
, DenoiseResponse
is also streamed.
Connecting to microservice
There are multiple ways how you can communicate with our microservices.
Using generated library
The most common way how to communicate with the microservices is via a programming language using a generated library.
Python library
If you use Python as your programming language, you can use our official gRPC Python library.
To install the package using pip
, run:
pip install phonexia-grpc
You can then import:
- Specific libraries for each microservice that provide the message wrappers.
- stubs for the
gRPC
clients.
from phonexia.grpc.common.core_pb2 import Audio, RawAudioConfig, TimeRange
from phonexia.grpc.technologies.denoiser.v1.denoiser_pb2 import DenoiseRequest, DenoiseResponse
from phonexia.grpc.technologies.denoiser.v1.denoiser_pb2_grpc import DenoiserStub
Generate library for programming language of your choice
For the definition of microservice interfaces, we use the standard way of protocol buffers. The services
, together with the procedures
and messages
that they expose, are defined in the so-called proto
files.
The proto
files can be used to generate client libraries in many programming languages. Take a look at protobuf tutorials for how to get started with generating the library in the languages of your choice using the protoc
tool.
You can find the proto
files developed by Phonexia in this repository.
Using existing clients
Phonexia Python client
The easiest way to get started with testing is to use our simple Python client. To get it, run:
pip install phonexia-denoiser-client
After the successful installation, run the following command to see the client options:
denoiser_client --help
grpcurl client
If you need a simple tool for testing the microservice on the command line, you can use grpcurl. This tool can serialize and send a request for you, if you provide the request body in JSON format and specify the endpoint.
The audio content in the body must be encoded in Base64
. The request also cannot exceed 4 MiB, therefore it's necessary to split bigger files to multiple chunks. You can use jq
tool to generate JSON input for grpcurl
.
Now you can make the request. The microservice supports reflection. That means that you don't need to know the API in advance to make a request. Replace ${path_to_audio_file}
with corresponding value.
base64 -w 4000000 ${path_to_audio_file} | jq -cnR '{"audio":{"content":inputs}}' | grpcurl -plaintext -use-reflection -d @ localhost:8080 phonexia.grpc.technologies.denoiser.v1.Denoiser/Denoise
The grpcurl
automatically serializes the response to this request into JSON. Note that the resulting audio will also be serialized to Base64.
GUI clients
If you'd prefer to use a GUI client like Postman or Warthog to test the microservice, take a look at the GUI Client page in our documentation. Note that you will still need to convert the audio into the Base64 format manually as those tools do not support it by default either.