https://github.com/seanchas116/node-tflite

TensorFlow Lite bindings for Node.js
https://github.com/seanchas116/node-tflite

deep-learning electron javascript machine-learning nodejs tensorflow tensorflow-lite typescript

Last synced: 4 days ago
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TensorFlow Lite bindings for Node.js

• Host: GitHub
• URL: https://github.com/seanchas116/node-tflite
• Owner: seanchas116
• License: mit
• Created: 2020-05-05T02:40:53.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2023-01-06T06:21:48.000Z (almost 2 years ago)
• Last Synced: 2024-10-30T08:52:03.298Z (13 days ago)
• Topics: deep-learning, electron, javascript, machine-learning, nodejs, tensorflow, tensorflow-lite, typescript
• Language: C
• Homepage: https://www.npmjs.com/package/node-tflite
• Size: 17.5 MB
• Stars: 14
• Watchers: 5
• Forks: 6
• Open Issues: 18
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# node-tflite

node-tflite is an unofficial TensorFlow Lite 2.2 bindings for Node.js.

It can run TensorFlow Lite models (`.tflite`) in Node.js environment (including Electron).

## Differences to TensorFlow.js

- node-tflite can run TensorFlow Lite models (`.tflite`) while TensorFlow.js cannot (you'll need a different way of model conversion in TensorFlow.js)

- node-tflite may or may not be faster than TensorFlow.js

  - I didn't run any benchmarks yet, but the example below runs faster than TF.js

- node-tflite only supports model inference, not training

- node-tflite doesn't support Web environments

- node-tflite doesn't support GPU execution (now) while TensorFlow.js supports through WebGL or tfjs-node-gpu

## Supported Platforms

- [x] macOS

- [x] Windows

- [x] Linux

## Install

```

npm install node-tflite

```

## Use

```js

import { Interpreter } from "node-tflite";

const modelData = fs.readFileSync("/path/to/model.tflite");

const interpreter = new Interpreter(modelData);

interpreter.allocateTensors();

interpreter.inputs[0].copyFrom(inputData);

interpreter.invoke();

interpreter.outputs[0].copyTo(outputData);

```

## Examples

- [BlazeFace face detection in Electron](https://github.com/seanchas116/node-tflite/tree/master/examples/electron-mediapipe-face)

  - Uses the BlazeFace model from [MediaPipe](https://github.com/google/mediapipe)

  - It runs in 60 FPS in MacBook Pro 16'' 2019, which is faster than [BlazeFace TF.js demo](https://storage.googleapis.com/tfjs-models/demos/blazeface/index.html) (around 40 FPS in both wasm and WebGL)

## Benchmark

TODO

## Develop

### Setup

```

npm install

```

### Test

```

npm test

```

### Build .js and .d.ts

```

npm run dist

```

### How to build tensorflowlite_c library

- [Configure tensorflow](https://www.tensorflow.org/install/source)

- `bazel build //tensorflow/lite/c:tensorflowlite_c`