add option to use Python or JS Tensorflow for ML predictions
This commit is contained in:
Alexandre Storelli
parent
3f2ead5701
commit
103966589e
20
README.md
20
README.md
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@ -23,15 +23,26 @@ In `post-processing.js`, results are gathered for each audio segment and cleaned
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A Readable interface, `Analyser`, is exposed to the end user. It streams objects containing the audio itself and all analysis results.
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On a regular laptop CPU, computations run at 5-10X for files and at 10-20% usage for live stream.
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On a regular laptop CPU and with the Python time-frequency analyser, computations run at 5-10X for files and at 10-20% usage for live stream.
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## Getting started
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### Installation
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As prerequisites, you need:
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As mandatory prerequisites, you need:
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- Node.js and NPM. This project requires a Node >= v10.12.x. Tested with NPM v6.4.1. If you need to manage several node versions on your platform, you might want to use [NVM](https://github.com/creationix/nvm).
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- FFmpeg (tested with v2.6.9). Installation instructions available [here](https://ffmpeg.org/download.html).
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- FFmpeg (tested with v2.6.9). [Installation instructions available here](https://ffmpeg.org/download.html).
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For best performance (~2x speedup) you should choose to do part of the computations with Python. Additional prerequisites are the following:
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- Python (tested with v2.7.9).
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- Keras (tested with v2.0.8). Keras installation instructions are available [here](https://keras.io/#installation).
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- Tensorflow (tested with `tensorflow` v1.4.0 and `tensorflow-gpu` v1.3.0). Installation instructions are [here](https://www.tensorflow.org/install/).
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```bash
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pip install keras tensorflow
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```
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should be enough. If you do not have pip [follow these instructions to install it](https://pip.pypa.io/en/stable/installing/).
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Then install this module:
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@ -52,7 +63,7 @@ npm test
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### Command-line demo
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At startup and periodically during runtime, filter configuration files are automatically updated from [adblockradio.com/models/](https://adblockradio.com/models/):
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- a compatible machine-learning model (`model.json` and `group1-shard1of1`), for the time-frequency analyser.
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- a compatible machine-learning model (`model.keras` or `model.json` + `group1-shard1of1`), for the time-frequency analyser.
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- a fingerprint database (`hotlist.sqlite`), for the fingerprint matcher.
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#### Live stream analysis
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@ -191,6 +202,7 @@ Property|Description|Default
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Property|Description|Periodicity|Default
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--------|-----------|-----------|-------
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`enablePredictorMl`|perform machine learning inference|`predInterval`|`true`
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`JSPredictorMl`|use tfjs instead of Python for ML inference (slower)|`false`
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`enablePredictorHotlist`|compute audio fingerprints and search them in a DB|`predInterval`|`true`
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`saveAudio*`|save stream audio data in segments on hard drive|`saveDuration`|`true`
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`saveMetadata`|save a JSON with predictions|`saveDuration`|`true`
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@ -557,6 +557,15 @@
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"resolved": "https://registry.npmjs.org/bit-twiddle/-/bit-twiddle-1.0.2.tgz",
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"bl": {
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"version": "1.2.2",
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"requires": {
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"readable-stream": "^2.3.5",
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"safe-buffer": "^5.1.1"
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}
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"block-stream": {
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"version": "0.0.9",
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"resolved": "https://registry.npmjs.org/block-stream/-/block-stream-0.0.9.tgz",
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@ -847,6 +856,11 @@
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"supports-color": "^5.3.0"
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@ -1181,6 +1195,14 @@
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"integrity": "sha1-6zkTMzRYd1y4TNGh+uBiEGu4dUU=",
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"version": "0.6.0",
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"resolved": "https://registry.npmjs.org/deep-extend/-/deep-extend-0.6.0.tgz",
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@ -1651,7 +1673,6 @@
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"version": "1.4.1",
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"resolved": "https://registry.npmjs.org/end-of-stream/-/end-of-stream-1.4.1.tgz",
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"dev": true,
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"requires": {
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"once": "^1.4.0"
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@ -1727,6 +1748,11 @@
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"integrity": "sha512-eGuFFw7Upda+g4p+QHvnW0RyTX/SVeJBDM/gCtMARO0cLuT2HcEKnTPvhjV6aGeqrCB/sbNop0Kszm0jsaWU4A==",
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"dev": true
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"version": "0.1.2",
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"resolved": "https://registry.npmjs.org/event-lite/-/event-lite-0.1.2.tgz",
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"version": "1.1.1",
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"resolved": "http://registry.npmjs.org/events/-/events-1.1.1.tgz",
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@ -1783,6 +1809,11 @@
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}
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"expand-template": {
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"version": "1.1.1",
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@ -2070,6 +2101,11 @@
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"map-cache": "^0.2.2"
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"fs-constants": {
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"version": "7.0.1",
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"resolved": "https://registry.npmjs.org/fs-extra/-/fs-extra-7.0.1.tgz",
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@ -2168,6 +2204,11 @@
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"assert-plus": "^1.0.0"
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"github-from-package": {
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"version": "0.0.0",
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"resolved": "https://registry.npmjs.org/glob/-/glob-7.1.3.tgz",
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@ -2387,8 +2428,7 @@
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"ieee754": {
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"version": "1.1.8",
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"resolved": "https://registry.npmjs.org/ieee754/-/ieee754-1.1.8.tgz",
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"dev": true
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"ignore-walk": {
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"version": "3.0.1",
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@ -2438,6 +2478,11 @@
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"resolved": "https://registry.npmjs.org/ini/-/ini-1.3.5.tgz",
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"resolved": "https://registry.npmjs.org/int64-buffer/-/int64-buffer-0.1.10.tgz",
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"integrity": "sha1-J3siiofZWtd30HwTgyAiQGpHNCM="
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"invert-kv": {
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"version": "2.0.0",
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"resolved": "https://registry.npmjs.org/invert-kv/-/invert-kv-2.0.0.tgz",
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@ -3082,6 +3127,11 @@
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"dev": true
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"resolved": "https://registry.npmjs.org/mimic-response/-/mimic-response-1.0.1.tgz",
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"resolved": "https://registry.npmjs.org/minimatch/-/minimatch-3.0.4.tgz",
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@ -3219,6 +3269,17 @@
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"version": "0.1.26",
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"integrity": "sha1-3TxQsm8FnyXn7e42REGDWOKprYk=",
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"requires": {
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"event-lite": "^0.1.1",
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"ieee754": "^1.1.8",
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"isarray": "^1.0.0"
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@ -3243,6 +3304,11 @@
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"to-regex": "^3.0.1"
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"napi-build-utils": {
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@ -3266,6 +3332,14 @@
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"dev": true
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@ -3352,6 +3426,11 @@
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"version": "3.0.6",
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"resolved": "https://registry.npmjs.org/nopt/-/nopt-3.0.6.tgz",
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@ -3862,6 +3941,36 @@
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"dev": true
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"github-from-package": "0.0.0",
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"mkdirp": "^0.5.1",
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"napi-build-utils": "^1.0.1",
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"node-abi": "^2.2.0",
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"noop-logger": "^0.1.1",
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"os-homedir": "^1.0.1",
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"rc": "^1.2.7",
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"simple-get": "^2.7.0",
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"which-pm-runs": "^1.0.0"
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"dependencies": {
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@ -3936,6 +4045,15 @@
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@ -4320,6 +4438,21 @@
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"requires": {
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"once": "^1.3.1",
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"single-line-log": {
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"resolved": "https://registry.npmjs.org/single-line-log/-/single-line-log-1.1.2.tgz",
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@ -4730,6 +4863,42 @@
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"requires": {
|
||||
"chownr": "^1.0.1",
|
||||
"mkdirp": "^0.5.1",
|
||||
"pump": "^1.0.0",
|
||||
"tar-stream": "^1.1.2"
|
||||
},
|
||||
"dependencies": {
|
||||
"pump": {
|
||||
"version": "1.0.3",
|
||||
"resolved": "https://registry.npmjs.org/pump/-/pump-1.0.3.tgz",
|
||||
"integrity": "sha512-8k0JupWme55+9tCVE+FS5ULT3K6AbgqrGa58lTT49RpyfwwcGedHqaC5LlQNdEAumn/wFsu6aPwkuPMioy8kqw==",
|
||||
"requires": {
|
||||
"end-of-stream": "^1.1.0",
|
||||
"once": "^1.3.1"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"tar-stream": {
|
||||
"version": "1.6.2",
|
||||
"resolved": "https://registry.npmjs.org/tar-stream/-/tar-stream-1.6.2.tgz",
|
||||
"integrity": "sha512-rzS0heiNf8Xn7/mpdSVVSMAWAoy9bfb1WOTYC78Z0UQKeKa/CWS8FOq0lKGNa8DWKAn9gxjCvMLYc5PGXYlK2A==",
|
||||
"requires": {
|
||||
"bl": "^1.0.0",
|
||||
"buffer-alloc": "^1.2.0",
|
||||
"end-of-stream": "^1.0.0",
|
||||
"fs-constants": "^1.0.0",
|
||||
"readable-stream": "^2.3.0",
|
||||
"to-buffer": "^1.1.1",
|
||||
"xtend": "^4.0.0"
|
||||
}
|
||||
},
|
||||
"temp-file": {
|
||||
"version": "3.3.2",
|
||||
"resolved": "https://registry.npmjs.org/temp-file/-/temp-file-3.3.2.tgz",
|
||||
|
|
@ -4812,6 +4981,11 @@
|
|||
"integrity": "sha1-8y6srFoXW+ol1/q1Zas+2HQe9W8=",
|
||||
"dev": true
|
||||
},
|
||||
"to-buffer": {
|
||||
"version": "1.1.1",
|
||||
"resolved": "https://registry.npmjs.org/to-buffer/-/to-buffer-1.1.1.tgz",
|
||||
"integrity": "sha512-lx9B5iv7msuFYE3dytT+KE5tap+rNYw+K4jVkb9R/asAb+pbBSM17jtunHplhBe6RRJdZx3Pn2Jph24O32mOVg=="
|
||||
},
|
||||
"to-object-path": {
|
||||
"version": "0.3.0",
|
||||
"resolved": "https://registry.npmjs.org/to-object-path/-/to-object-path-0.3.0.tgz",
|
||||
|
|
@ -4908,6 +5082,11 @@
|
|||
"integrity": "sha1-hnrHTjhkGHsdPUfZlqeOxciDB3c=",
|
||||
"dev": true
|
||||
},
|
||||
"underscore": {
|
||||
"version": "1.3.3",
|
||||
"resolved": "https://registry.npmjs.org/underscore/-/underscore-1.3.3.tgz",
|
||||
"integrity": "sha1-R6xTaD2vgyv6lS4XdEF9pHgXrkI="
|
||||
},
|
||||
"union-value": {
|
||||
"version": "1.0.0",
|
||||
"resolved": "https://registry.npmjs.org/union-value/-/union-value-1.0.0.tgz",
|
||||
|
|
@ -5187,6 +5366,11 @@
|
|||
"integrity": "sha1-2e8H3Od7mQK4o6j6SzHD4/fm6Ho=",
|
||||
"dev": true
|
||||
},
|
||||
"which-pm-runs": {
|
||||
"version": "1.0.0",
|
||||
"resolved": "https://registry.npmjs.org/which-pm-runs/-/which-pm-runs-1.0.0.tgz",
|
||||
"integrity": "sha1-Zws6+8VS4LVd9rd4DKdGFfI60cs="
|
||||
},
|
||||
"wide-align": {
|
||||
"version": "1.1.3",
|
||||
"resolved": "https://registry.npmjs.org/wide-align/-/wide-align-1.1.3.tgz",
|
||||
|
|
@ -5344,6 +5528,11 @@
|
|||
"integrity": "sha1-1QH5ezvbQDr4757MIFcxh6rawOk=",
|
||||
"dev": true
|
||||
},
|
||||
"xtend": {
|
||||
"version": "4.0.1",
|
||||
"resolved": "https://registry.npmjs.org/xtend/-/xtend-4.0.1.tgz",
|
||||
"integrity": "sha1-pcbVMr5lbiPbgg77lDofBJmNY68="
|
||||
},
|
||||
"y18n": {
|
||||
"version": "4.0.0",
|
||||
"resolved": "https://registry.npmjs.org/y18n/-/y18n-4.0.0.tgz",
|
||||
|
|
@ -5446,6 +5635,64 @@
|
|||
"requires": {
|
||||
"fd-slicer": "~1.0.1"
|
||||
}
|
||||
},
|
||||
"zeromq": {
|
||||
"version": "5.1.0",
|
||||
"resolved": "https://registry.npmjs.org/zeromq/-/zeromq-5.1.0.tgz",
|
||||
"integrity": "sha512-wBEwnWaC1BQgcVoC4ZcERuIf+F0LdW12rblcwFNQANUGjJqQB1Ty3D59+WhvBJU9EliQw9Qc6V914gYXMzO6jw==",
|
||||
"requires": {
|
||||
"nan": "^2.10.0",
|
||||
"prebuild-install": "5.2.1"
|
||||
}
|
||||
},
|
||||
"zerorpc": {
|
||||
"version": "0.9.8",
|
||||
"resolved": "https://registry.npmjs.org/zerorpc/-/zerorpc-0.9.8.tgz",
|
||||
"integrity": "sha512-F3J8mp196uveb0icLL85GszQDHNGuOJT1BoUNvKzo8hetACiLKdXWLw0i/wTB/skg79DZBPA9h0MdmOt772KRQ==",
|
||||
"requires": {
|
||||
"msgpack-lite": "^0.1.26",
|
||||
"underscore": "1.3.3",
|
||||
"uuid": "^3.0.0",
|
||||
"zeromq": "^4.6.0"
|
||||
},
|
||||
"dependencies": {
|
||||
"minimist": {
|
||||
"version": "1.2.0",
|
||||
"resolved": "https://registry.npmjs.org/minimist/-/minimist-1.2.0.tgz",
|
||||
"integrity": "sha1-o1AIsg9BOD7sH7kU9M1d95omQoQ="
|
||||
},
|
||||
"prebuild-install": {
|
||||
"version": "2.5.3",
|
||||
"resolved": "https://registry.npmjs.org/prebuild-install/-/prebuild-install-2.5.3.tgz",
|
||||
"integrity": "sha512-/rI36cN2g7vDQnKWN8Uzupi++KjyqS9iS+/fpwG4Ea8d0Pip0PQ5bshUNzVwt+/D2MRfhVAplYMMvWLqWrCF/g==",
|
||||
"requires": {
|
||||
"detect-libc": "^1.0.3",
|
||||
"expand-template": "^1.0.2",
|
||||
"github-from-package": "0.0.0",
|
||||
"minimist": "^1.2.0",
|
||||
"mkdirp": "^0.5.1",
|
||||
"node-abi": "^2.2.0",
|
||||
"noop-logger": "^0.1.1",
|
||||
"npmlog": "^4.0.1",
|
||||
"os-homedir": "^1.0.1",
|
||||
"pump": "^2.0.1",
|
||||
"rc": "^1.1.6",
|
||||
"simple-get": "^2.7.0",
|
||||
"tar-fs": "^1.13.0",
|
||||
"tunnel-agent": "^0.6.0",
|
||||
"which-pm-runs": "^1.0.0"
|
||||
}
|
||||
},
|
||||
"zeromq": {
|
||||
"version": "4.6.0",
|
||||
"resolved": "https://registry.npmjs.org/zeromq/-/zeromq-4.6.0.tgz",
|
||||
"integrity": "sha512-sU7pQqQj7f/C6orJZAXls+NEKaVMZZtnZqpMPTq5d5dP78CmdC0g15XIviFAN6poPuKl9qlGt74vipOUUuNeWg==",
|
||||
"requires": {
|
||||
"nan": "^2.6.2",
|
||||
"prebuild-install": "^2.2.2"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"description": "Distinguish ads, talk and music in radios",
|
||||
"main": "post-processing.js",
|
||||
"scripts": {
|
||||
"test": "mocha --delay test/file.js && mocha --delay test/online.js && mocha --delay test/offline.js"
|
||||
"test": "mocha --delay test/file.js && mocha --delay test/file.js --mljs && mocha --delay test/online.js && mocha --delay test/online.js --mljs && mocha --delay test/offline.js && mocha --delay test/offline.js --mljs"
|
||||
},
|
||||
"keywords": [
|
||||
"adblock",
|
||||
|
|
@ -25,7 +25,9 @@
|
|||
"sqlite3": "^4.0.6",
|
||||
"stream-audio-fingerprint": "^1.0.4",
|
||||
"stream-tireless-baler": "^1.0.15",
|
||||
"tar": "^4.4.8"
|
||||
"tar": "^4.4.8",
|
||||
"zeromq": "^5.1.0",
|
||||
"zerorpc": "^0.9.8"
|
||||
},
|
||||
"devDependencies": {
|
||||
"aws-sdk": "^2.420.0",
|
||||
|
|
|
|||
|
|
@ -341,7 +341,6 @@ class Analyser extends Readable {
|
|||
}
|
||||
|
||||
const defaultModelPath = process.cwd() + '/model';
|
||||
const defaultModelFile = this.country + '_' + this.name + '/model.json';
|
||||
const defaultHotlistFile = this.country + '_' + this.name + '/hotlist.sqlite';
|
||||
|
||||
// default module options
|
||||
|
|
@ -351,15 +350,18 @@ class Analyser extends Readable {
|
|||
file: null, // analyse a file instead of a HTTP stream. will not download stream
|
||||
records: null, // analyse a series of previous records (relative paths). will not download stream
|
||||
modelPath: defaultModelPath, // directory where ML models and hotlist DBs are stored
|
||||
modelFile: defaultModelFile, // path of the ML model relative to modelPath
|
||||
hotlistFile: defaultHotlistFile, // path of the hotlist DB relative to modelPath
|
||||
modelUpdates: true, // periodically fetch ML and hotlist models and refresh predictors
|
||||
modelUpdateInterval: 60 // update model files every N minutes
|
||||
modelUpdateInterval: 60, // update model files every N minutes
|
||||
JSPredictorMl: false, // whether to use JS (+ native lib) instead of Python for ML. JS is simpler but slower.
|
||||
}
|
||||
|
||||
// optional custom config
|
||||
Object.assign(this.config, options.config);
|
||||
|
||||
const defaultModelFile = this.country + '_' + this.name + '/model.' + (this.config.JSPredictorMl ? 'json' : 'keras');
|
||||
if (!this.config.modelFile) this.config.modelFile = defaultModelFile; // path of the ML model relative to modelPath
|
||||
|
||||
this.postProcessor = new PostProcessor({
|
||||
country: this.country,
|
||||
name: this.name,
|
||||
|
|
@ -419,14 +421,19 @@ class Analyser extends Readable {
|
|||
// download and/or update models at startup
|
||||
// TODO only download model/hotlist if ML/hotlist is enabled
|
||||
if (self.config.modelUpdates) {
|
||||
await checkModelUpdates({
|
||||
localPath: self.config.modelPath,
|
||||
files: [
|
||||
const files = self.config.JSPredictorMl ?
|
||||
[
|
||||
{ file: self.config.modelFile, tar: false },
|
||||
{ file: self.config.modelFile.replace('model.json', 'group1-shard1of1'), tar: false },
|
||||
{ file: self.config.hotlistFile, tar: true },
|
||||
]
|
||||
});
|
||||
:
|
||||
[
|
||||
{ file: self.config.modelFile, tar: true },
|
||||
{ file: self.config.hotlistFile, tar: true },
|
||||
]
|
||||
;
|
||||
await checkModelUpdates({ localPath: self.config.modelPath, files });
|
||||
} else {
|
||||
log.info(self.country + '_' + self.name + ' model updates are disabled');
|
||||
}
|
||||
|
|
@ -484,14 +491,19 @@ class Analyser extends Readable {
|
|||
|
||||
self.modelUpdatesInterval = setInterval(function() {
|
||||
if (self.config.modelUpdates) {
|
||||
checkModelUpdates({
|
||||
localPath: self.config.modelPath,
|
||||
files: [
|
||||
const files = self.config.JSPredictorMl ?
|
||||
[
|
||||
{ file: self.config.modelFile, tar: false, callback: self.predictor.refreshPredictorMl },
|
||||
{ file: self.config.modelFile.replace('model.json', 'group1-shard1of1'), tar: false, callback: self.predictor.refreshPredictorMl },
|
||||
{ file: self.config.hotlistFile, tar: true, callback: self.predictor.refreshPredictorHotlist },
|
||||
]
|
||||
});
|
||||
:
|
||||
[
|
||||
{ file: self.config.modelFile, tar: true, callback: self.predictor.refreshPredictorMl },
|
||||
{ file: self.config.hotlistFile, tar: true, callback: self.predictor.refreshPredictorHotlist },
|
||||
]
|
||||
;
|
||||
checkModelUpdates({ localPath: self.config.modelPath, files });
|
||||
}
|
||||
checkMetadataUpdates(self.predictor.refreshMetadata);
|
||||
}, self.config.modelUpdateInterval * 60000);
|
||||
|
|
|
|||
|
|
@ -150,16 +150,14 @@ class PredictorFile {
|
|||
});
|
||||
|
||||
// start analysis as soon as both ML and hotlist are ready
|
||||
let hotlistReady = false;
|
||||
if (this.config.enablePredictorHotlist) this.startPredictorHotlist(function() {
|
||||
hotlistReady = true;
|
||||
if ((self.config.enablePredictorMl && mlReady) || !self.config.enablePredictorMl) self.input.resume();
|
||||
});
|
||||
|
||||
let mlReady = false;
|
||||
if (this.config.enablePredictorMl) this.startPredictorMl(function() {
|
||||
mlReady = true;
|
||||
if ((self.config.enablePredictorHotlist && hotlistReady) || !self.config.enablePredictorHotlist) self.input.resume();
|
||||
Promise.all([
|
||||
this.config.enablePredictorHotlist && this.startPredictorHotlist(),
|
||||
this.config.enablePredictorMl && this.startPredictorMl()
|
||||
]).then(function() {
|
||||
log.info("hotlist and/or ml loaded");
|
||||
self.input.resume();
|
||||
}).catch(function(err) {
|
||||
log.error(self.country + "_" + self.name + " predictor err=" + err);
|
||||
});
|
||||
}
|
||||
|
||||
|
|
@ -214,31 +212,40 @@ class PredictorFile {
|
|||
});
|
||||
}
|
||||
|
||||
startPredictorHotlist(callback) {
|
||||
async startPredictorHotlist() {
|
||||
if (this.config.enablePredictorHotlist) {
|
||||
this.hotlist = new Hotlist({
|
||||
country: this.country,
|
||||
name: this.name,
|
||||
fileDB: this.hotlistFile,
|
||||
callback: callback,
|
||||
const self = this;
|
||||
return new Promise(function(resolve, reject) {
|
||||
self.hotlist = new Hotlist({
|
||||
country: self.country,
|
||||
name: self.name,
|
||||
fileDB: self.hotlistFile,
|
||||
callback: resolve,
|
||||
});
|
||||
});
|
||||
} else {
|
||||
this.hotlist = null;
|
||||
}
|
||||
}
|
||||
|
||||
startPredictorMl(callback) {
|
||||
async startPredictorMl() {
|
||||
if (this.config.enablePredictorMl) {
|
||||
this.mlPredictor = new MlPredictor({
|
||||
country: this.country,
|
||||
name: this.name,
|
||||
modelFile: this.modelFile,
|
||||
});
|
||||
const self = this;
|
||||
return new Promise(function(resolve, reject) {
|
||||
self.mlPredictor = new MlPredictor({
|
||||
country: self.country,
|
||||
name: self.name,
|
||||
modelFile: self.modelFile,
|
||||
JSPredictorMl: self.config.JSPredictorMl,
|
||||
callback: resolve,
|
||||
});
|
||||
});
|
||||
|
||||
/*const self = this;
|
||||
(async function() {
|
||||
await self.mlPredictor.load(self.modelFile);
|
||||
callback();
|
||||
})();
|
||||
})();*/
|
||||
} else {
|
||||
this.mlPredictor = null;
|
||||
}
|
||||
|
|
@ -246,8 +253,8 @@ class PredictorFile {
|
|||
|
||||
stopPredictors() {
|
||||
log.info("close predictor");
|
||||
if (this.hotlist) this.hotlist.end();
|
||||
if (this.mlPredictor) this.mlPredictor.end();
|
||||
if (this.hotlist) this.hotlist.destroy();
|
||||
if (this.mlPredictor) this.mlPredictor.destroy();
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -10,6 +10,8 @@ const { log } = require("abr-log")("pred-ml");
|
|||
const cp = require("child_process");
|
||||
const assert = require("assert");
|
||||
|
||||
const fs = require("fs-extra");
|
||||
|
||||
function parse(msg) {
|
||||
try {
|
||||
return JSON.parse(msg);
|
||||
|
|
@ -25,64 +27,245 @@ class MlPredictor extends Writable {
|
|||
this.canonical = options.country + "_" + options.name;
|
||||
this.verbose = options.verbose || false;
|
||||
this.ready = false; // becomes true when ML model is loaded
|
||||
this.modelFile = options.modelFile;
|
||||
//this.ready2 = false; // becomes true when audio data is piped to this module. managed externally
|
||||
//this.finalCallback = null;
|
||||
this.modelFile = options.modelFile;
|
||||
//this.readyToCallFinal = false;
|
||||
this.dataWrittenSinceLastSeg = false;
|
||||
this.JSPredictorMl = !!options.JSPredictorMl;
|
||||
|
||||
this.load = this.load.bind(this);
|
||||
this.predict = this.predict.bind(this);
|
||||
|
||||
const self = this;
|
||||
(async function() {
|
||||
await self.load();
|
||||
if (options.callback) options.callback();
|
||||
})();
|
||||
}
|
||||
|
||||
async load() {
|
||||
const self = this;
|
||||
return new Promise(function(resolve, reject) {
|
||||
self.child = cp.fork(__dirname + '/ml-worker.js', {
|
||||
env: {
|
||||
canonical: self.canonical,
|
||||
modelFile: self.modelFile,
|
||||
if (this.JSPredictorMl) { // Javascript MFCC & Tensorflow: tfjs (pure JS) or node-tfjs (native lib and Node bindings)
|
||||
|
||||
log.info(this.canonical + " JS predictor");
|
||||
await new Promise(function(resolve, reject) {
|
||||
self.child = cp.fork(__dirname + '/ml-worker.js', {
|
||||
env: {
|
||||
canonical: self.canonical,
|
||||
modelFile: self.modelFile,
|
||||
}
|
||||
});
|
||||
|
||||
self.child.once('message', function(msg) {
|
||||
msg = parse(msg);
|
||||
assert.equal(msg.type, 'loading');
|
||||
if (msg.err) {
|
||||
log.warn(self.canonical + ' could not load model: ' + JSON.stringify(msg));
|
||||
return reject();
|
||||
}
|
||||
self.ready = msg.loaded;
|
||||
log.info(self.canonical + ' loaded=' + self.ready);
|
||||
resolve();
|
||||
});
|
||||
});
|
||||
|
||||
} else { // Python MFCC & Tensorflow
|
||||
|
||||
const isPKG = __dirname.indexOf("/snapshot/") === 0 || __dirname.indexOf("C:\\snapshot\\") === 0; // in a PKG environment (https://github.com/zeit/pkg)
|
||||
const isElectron = !!(process && process.versions['electron']); // in a Electron environment (https://github.com/electron/electron/issues/2288)
|
||||
|
||||
log.info(this.canonical + " Python predictor. __dirname=" + __dirname + " env: PKG=" + isPKG + " Electron=" + isElectron);
|
||||
|
||||
if (isPKG) {
|
||||
this.predictChild = cp.spawn(process.cwd() + "/dist/mlpredict/mlpredict",
|
||||
[ this.canonical ], { stdio: ['pipe', 'pipe', 'pipe']});
|
||||
} else if (isElectron) {
|
||||
const paths = [
|
||||
"",
|
||||
"/Adblock Radio Buffer-linux-x64/resources/app"
|
||||
];
|
||||
|
||||
for (let i=0; i<paths.length; i++) {
|
||||
const path = process.cwd() + paths[i] + "/node_modules/adblockradio/predictor-ml/dist/mlpredict/mlpredict"
|
||||
try {
|
||||
await fs.access(path);
|
||||
log.info("mlpredict found at " + path);
|
||||
this.predictChild = cp.spawn(path, [ this.canonical ], { stdio: ['pipe', 'pipe', 'pipe']});
|
||||
break;
|
||||
} catch (e) {
|
||||
// pass
|
||||
}
|
||||
if (i === paths.length - 1) {
|
||||
const msg = "Could not locate mlpredict. cwd=" + process.cwd() + " paths=" + JSON.stringify(paths);
|
||||
log.error(msg);
|
||||
throw new Error(msg);
|
||||
}
|
||||
}
|
||||
|
||||
} else {
|
||||
this.predictChild = cp.spawn('python', [
|
||||
'-u',
|
||||
__dirname + '/mlpredict.py',
|
||||
this.canonical,
|
||||
], { stdio: ['pipe', 'pipe', 'pipe'] });
|
||||
}
|
||||
|
||||
const zerorpc = require("zerorpc");
|
||||
// increase default timeouts, otherwise this would fail at model loading on some CPU-bound devices.
|
||||
// https://github.com/0rpc/zerorpc-node#clients
|
||||
this.client = new zerorpc.Client({ timeout: 120, heartbeatInterval: 60000 });
|
||||
this.client.connect("ipc:///tmp/" + this.canonical);
|
||||
|
||||
this.client.on("error", function(error) {
|
||||
log.error(self.canonical + " RPC client error:" + error);
|
||||
});
|
||||
|
||||
this.predictChild.stdout.on('data', function(msg) { // received messages from python worker
|
||||
const msgS = msg.toString().split("\n");
|
||||
|
||||
// sometimes, several lines arrive at once. separate them.
|
||||
for (let i=0; i<msgS.length; i++) {
|
||||
if (msgS[i].length > 0) log.debug(msgS[i]);
|
||||
}
|
||||
});
|
||||
|
||||
self.child.once('message', function(msg) {
|
||||
msg = parse(msg);
|
||||
assert.equal(msg.type, 'loading');
|
||||
if (msg.err) {
|
||||
log.warn(self.canonical + ' could not load model: ' + JSON.stringify(msg));
|
||||
return reject();
|
||||
}
|
||||
self.ready = msg.loaded;
|
||||
log.info(self.canonical + ' loaded=' + self.ready);
|
||||
resolve();
|
||||
this.predictChild.stderr.on("data", function(msg) {
|
||||
if (msg.includes("Using TensorFlow backend.")) return;
|
||||
log.error(self.canonical + " mlpredict child stderr data: " + msg);
|
||||
});
|
||||
});
|
||||
this.predictChild.stdin.on("error", function(err) {
|
||||
log.warn(self.canonical + " mlpredict child stdin error: " + err);
|
||||
});
|
||||
this.predictChild.stdout.on("error", function(err) {
|
||||
log.warn(self.canonical + " mlpredict child stdout error: " + err);
|
||||
});
|
||||
this.predictChild.stderr.on("error", function(err) {
|
||||
log.warn(self.canonical + " mlpredict child stderr error: " + err);
|
||||
});
|
||||
this.predictChild.stdout.on("end", function() {
|
||||
//log.debug("cp stdout end");
|
||||
//self.readyToCallFinal = true;
|
||||
//if (self.finalCallback) self.finalCallback();
|
||||
});
|
||||
|
||||
await new Promise(function(resolve, reject) {
|
||||
self.client.invoke("load", self.modelFile, function(error, res, more) {
|
||||
if (error) {
|
||||
if (error === "model not found") {
|
||||
log.error(self.canonical + " Keras ML file " + self.modelFile + " not found. Cannot tag audio");
|
||||
} else {
|
||||
log.error(error);
|
||||
|
||||
// TODO has occasionally thrown:
|
||||
// "Initializer for variable lstm_1_2/kernel/ is from inside a control-flow construct,
|
||||
// such as a loop or conditional. When creating a variable inside a loop or conditional,
|
||||
// use a lambda as the initializer."
|
||||
//
|
||||
// but cannot reproduce :/
|
||||
}
|
||||
return reject();
|
||||
}
|
||||
|
||||
log.info(self.canonical + " predictor process is ready to crunch audio");
|
||||
self.ready = true;
|
||||
return resolve();
|
||||
});
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
_write(buf, enc, next) {
|
||||
if (this.child && this.ready) {
|
||||
if (this.JSPredictorMl && this.child && this.ready) {
|
||||
this.child.send(JSON.stringify({
|
||||
type: 'write',
|
||||
buf: buf,
|
||||
}));
|
||||
|
||||
} else if (!this.JSPredictorMl && this.client && this.predictChild && this.ready) {
|
||||
this.dataWrittenSinceLastSeg = true;
|
||||
const self = this;
|
||||
this.client.invoke("write", buf, function(err, res, more) {
|
||||
if (err) {
|
||||
log.error(self.canonical + " _write client returned error=" + err);
|
||||
}
|
||||
});
|
||||
}
|
||||
next();
|
||||
}
|
||||
|
||||
predict(callback) {
|
||||
if (this.child && this.ready) {
|
||||
const self = this;
|
||||
|
||||
if (this.JSPredictorMl && this.child && this.ready) {
|
||||
this.child.send(JSON.stringify({
|
||||
type: 'predict',
|
||||
}));
|
||||
const self = this;
|
||||
this.child.once('message', function(msg) {
|
||||
msg = parse(msg);
|
||||
assert.equal(msg.type, 'predict');
|
||||
if (msg.err) log.warn(self.canonical + ' skipped prediction: ' + JSON.stringify(msg));
|
||||
callback(null, msg.outData);
|
||||
});
|
||||
|
||||
} else if (!this.JSPredictorMl && this.client && this.predictChild && this.ready) {
|
||||
if (!this.dataWrittenSinceLastSeg) {
|
||||
//if (this.ready2) log.warn(this.canonical + " skip predict as no data is available for analysis");
|
||||
return callback();
|
||||
}
|
||||
this.dataWrittenSinceLastSeg = false;
|
||||
this.client.invoke("predict", function(err, res, more) {
|
||||
if (err) {
|
||||
log.error(self.canonical + " predict() returned error=" + err);
|
||||
return callback(err);
|
||||
}
|
||||
try {
|
||||
var results = JSON.parse(res);
|
||||
//log.debug("results=" + JSON.stringify(results))
|
||||
//log.debug("perf: nwin=" + results.nwin + " pre=" + results.timings.pre + " tf=" + results.timings.tf + " post=" + results.timings.post + " total=" + results.timings.total);
|
||||
} catch(e) {
|
||||
log.error(self.canonical + " could not parse json results: " + e + " original data=|" + res + "|");
|
||||
return callback(err);
|
||||
}
|
||||
|
||||
let outData = {
|
||||
type: results.type,
|
||||
confidence: results.confidence,
|
||||
softmaxraw: results.softmax.concat([0]), // the last class is about jingles. ML does not detect them.
|
||||
//date: new Date(stream.lastData.getTime() + Math.round(stream.tBuffer*1000)),
|
||||
gain: results.rms,
|
||||
lenPcm: results.lenpcm
|
||||
}
|
||||
|
||||
callback(null, outData);
|
||||
});
|
||||
} else {
|
||||
callback(null);
|
||||
}
|
||||
}
|
||||
|
||||
_final() {
|
||||
if (this.child) {
|
||||
this.child.kill();
|
||||
log.info(this.canonical + " killed child process.");
|
||||
if (this.JSPredictorMl) {
|
||||
if (this.child) {
|
||||
this.child.kill();
|
||||
log.info(this.canonical + " killed child process.");
|
||||
}
|
||||
} else {
|
||||
const self = this;
|
||||
this.client.invoke("exit", function(err, res, more) {
|
||||
if (err) {
|
||||
log.error(self.canonical + "_final: exit() returned error=" + err);
|
||||
}
|
||||
});
|
||||
|
||||
this.client.close();
|
||||
|
||||
// if not enough, kill it directly!
|
||||
this.predictChild.stdin.end();
|
||||
this.predictChild.kill();
|
||||
|
||||
//if (this.readyToCallFinal) return next();
|
||||
//this.readyToCallFinal = next;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
|||
17
predictor.js
17
predictor.js
|
|
@ -302,17 +302,24 @@ class Predictor {
|
|||
}
|
||||
|
||||
async refreshPredictorMl() {
|
||||
log.info(this.canonical + " refresh ML predictor");
|
||||
log.info(this.canonical + " refresh ML predictor (" + (this.config.JSPredictorMl ? "JS" : "Python") + " child process)");
|
||||
if (this.mlPredictor) {
|
||||
this.decoder.stdout.unpipe(this.mlPredictor);
|
||||
this.mlPredictor.destroy();
|
||||
}
|
||||
if (this.config.enablePredictorMl && !this.mlPredictor) {
|
||||
this.mlPredictor = new MlPredictor({
|
||||
country: this.country,
|
||||
name: this.name,
|
||||
modelFile: this.modelFile,
|
||||
JSPredictorMl: this.config.JSPredictorMl,
|
||||
});
|
||||
this.decoder.stdout.pipe(this.mlPredictor);
|
||||
} else {
|
||||
this.mlPredictor = null;
|
||||
}
|
||||
if (this.config.enablePredictorMl) {
|
||||
await this.mlPredictor.load();
|
||||
//if (this.config.enablePredictorMl) {
|
||||
// await this.mlPredictor.load();
|
||||
// we pipe decoder into mlPredictor later, once mlPredictor is ready to process data. the flag for this is mlPredictor.ready2
|
||||
/*const self = this;
|
||||
this.mlPredictor.ready2 = false;
|
||||
|
|
@ -335,13 +342,13 @@ class Predictor {
|
|||
}
|
||||
}, self.config.waitAfterMlModelLoad); // to not overwhelm the CPU in CPU-bound systems
|
||||
*/
|
||||
} else {
|
||||
/*} else {
|
||||
if (this.mlPredictor) {
|
||||
if (this.mlPredictor.ready2) this.decoder.stdout.unpipe(this.mlPredictor);
|
||||
this.mlPredictor.destroy();
|
||||
this.mlPredictor = null;
|
||||
}
|
||||
}
|
||||
}*/
|
||||
}
|
||||
|
||||
refreshMetadata() {
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ const TEST_ML = true;
|
|||
const TEST_HOTLIST = true;
|
||||
const PRED_INTERVAL = 1; // in seconds
|
||||
|
||||
const MLJS = process.argv.includes('--mljs');
|
||||
|
||||
if (cluster.isMaster) {
|
||||
|
||||
const TIMEOUT = 30000; // this must be at least the length of the audio tested
|
||||
|
|
@ -77,7 +79,7 @@ if (cluster.isMaster) {
|
|||
run();
|
||||
});*/
|
||||
|
||||
describe('File analysis', function() {
|
||||
describe('File analysis (' + (MLJS ? 'JS' : 'Python') + ' child process)', function() {
|
||||
|
||||
it("should have emitted data", function() {
|
||||
assert(gotData);
|
||||
|
|
@ -175,6 +177,7 @@ if (cluster.isMaster) {
|
|||
enablePredictorMl: TEST_ML,
|
||||
saveMetadata: true,
|
||||
verbose: false,
|
||||
JSPredictorMl: MLJS
|
||||
}
|
||||
});
|
||||
|
||||
|
|
|
|||
|
|
@ -10,6 +10,8 @@ const PRED_INTERVAL = 1; // in seconds
|
|||
const COUNTRY = "France";
|
||||
const NAME = "RTL";
|
||||
|
||||
const MLJS = process.argv.includes('--mljs');
|
||||
|
||||
if (cluster.isMaster) {
|
||||
|
||||
// first, download some chunks of audio
|
||||
|
|
@ -205,8 +207,8 @@ if (cluster.isMaster) {
|
|||
}
|
||||
}
|
||||
|
||||
const test = function(origNPredictions) {
|
||||
describe('Offline analysis', function() {
|
||||
const test = function() {
|
||||
describe('Offline analysis (' + (MLJS ? 'JS' : 'Python') + ' child process)', function() {
|
||||
|
||||
it("should have emitted an end event", function() {
|
||||
assert(oaFinished);
|
||||
|
|
@ -284,6 +286,7 @@ if (cluster.isMaster) {
|
|||
saveMetadata: true,
|
||||
fetchMetadata: true,
|
||||
verbose: true,
|
||||
JSPredictorMl: MLJS,
|
||||
}
|
||||
});
|
||||
|
||||
|
|
@ -321,6 +324,7 @@ if (cluster.isMaster) {
|
|||
enablePredictorHotlist: true,
|
||||
enablePredictorMl: true,
|
||||
modelUpdates: false,
|
||||
JSPredictorMl: MLJS,
|
||||
}
|
||||
});
|
||||
|
||||
|
|
|
|||
|
|
@ -10,6 +10,8 @@ const TEST_ML = true;
|
|||
const TEST_HOTLIST = true;
|
||||
const PRED_INTERVAL = 1; // in seconds
|
||||
|
||||
const MLJS = process.argv.includes('--mljs');
|
||||
|
||||
if (cluster.isMaster) {
|
||||
|
||||
const CLOSE_DELAY = 15000;
|
||||
|
|
@ -89,7 +91,7 @@ if (cluster.isMaster) {
|
|||
})();
|
||||
});
|
||||
|
||||
describe('Live stream analysis', function() {
|
||||
describe('Live stream analysis (' + (MLJS ? 'JS' : 'Python') + ' child process)', function() {
|
||||
|
||||
it("should have emitted data", function() {
|
||||
assert(gotData);
|
||||
|
|
@ -192,6 +194,7 @@ if (cluster.isMaster) {
|
|||
saveMetadata: true,
|
||||
fetchMetadata: true,
|
||||
verbose: false,
|
||||
JSPredictorMl: MLJS,
|
||||
}
|
||||
});
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue