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tfjs-yolo-tiny

In-Browser Object Detection using Tiny YOLO on Tensorflow.js.

ApplicationsObject detectionJavaScript
Open on GitHub
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534
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88
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Created 2018-04-07 · Updated 2026-09-12 · #17534 today
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MikeShi42moklick

ModelDepot/tfjs-yolo-tiny is ranked 17,534 with 534 stars.

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ModelDepot/tfjs-yolo-tiny is ranked 17,534 among these 8 peers; S-Trespassing/claw-in-chrome is ranked 17,535.

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Key parameters and specifications
Key parameters and specifications
ParameterValue
LanguageJavaScript
CategoryApplications
SubcategoryObject detection
KeywordsComputer vision, JavaScript
Stars534
Forks88
Contributors2
Created date2018-04-07
Updated date2026-09-12
Stars in 1 day0
Stars in 7 days0
Rank17,534
Previous rank17,318
Rank change-216
7-day stars rank16,157
Previous 7-day stars rank16,163
7-day stars rank change6
Total stars rank18,379
Previous total stars rank18,354
Total stars rank change-25
README summary

⚡️ Fast In-Browser Object Detection 👀 Detect objects in images right in your browser using Tensorflow. Currently takes ~800ms to analyze each frame on Chrome MBP 13" mid-2014. Supports , as of right now, does not have support to run any full YOLO models (and your user's computers probably can't handle it either). Tensor | - | Expected shape (1, 416, 416, 3) Tensor representing input image (RGB 416x416) model | tf. Model [options] | Object | See Below | Optional, Additional Configs If you're using a custom

Tiny YOLO model or want to adjust the default filtering cutoffs, you may do so by passing an additional options object. classProbThreshold] | | | Filter out classes below a certain threshold | | [options. iouThreshold] | | | Filter out boxes that have an IoU greater than this threadhold (refer to tf. filterBoxesThreshold] | | | Threshold to filter out box confidence * class confidence | | [options. maxBoxes] | | | Number of max boxes to return, refer to tf. Note: The model itself can only return so many boxes. yoloAnchors] | | | (Advanced) Yolo Anchor Boxes

, only needed if retraining on a new dataset | | [options. width] | | | (Advanced) If your model's input width is not 416, only if you're using a custom model | | [options. height] | | | (Advanced) If your model's input height is not 416, only if you're using a custom model | | [options. numClasses] | | | (Advanced) If your model has a different number of classes, only if you're using a custom model | | [options. classNames] | | | (Advanced) If your model has non-MSCOCO class names, only if you're using a custom

model | Returns Returns an array of objects. right | Number | Pixels from left of image where box ends. classProb | Number | Probability of the class in the bounding box. className | String | Human name of the class. loadModel Returns Returns a that can resolve to a . Contributing PR's are more than welcome! Perf improvement or better test coverage are probably the two biggest areas of immediate need. If you have thoughts on extensibility as well, feel free to open an issue! Install Dependencies

Run Tests If you're running tests, make sure to so that you you don't get tfjs package not found errors. If you're developing, make sure to remove tfjs as a dependency, as it'll start using the local version of intead of the peer version. Note: Test coverage is poor, definitely don't rely on them to catch your errors. Build Or during development, use watch mode, you can use the demo app to test out changes.

Frequently asked questions

How many stars and forks are recorded?

ModelDepot/tfjs-yolo-tiny has 534 stars and 88 forks.

What is the repository rank?

ModelDepot/tfjs-yolo-tiny is ranked 17,534.

What language and category are recorded?

ModelDepot/tfjs-yolo-tiny has 534 stars, uses JavaScript and belongs to Applications.

Which repository is closest in rank?

ModelDepot/tfjs-yolo-tiny is compared with S-Trespassing/claw-in-chrome, ranked 17,535 with 534 stars.

README

⚡️ Fast In-Browser Object Detection 👀

Detect objects in images right in your browser using Tensorflow.js! Currently takes ~800ms to analyze each frame on Chrome MBP 13" mid-2014.

Supports Tiny YOLO, as of right now, tfjs does not have support to run any full YOLO models (and your user's computers probably can't handle it either).

Demo

Check out the Live Demo

(You can only get so far with 1 FPS)

Install

Yarn

yarn add tfjs-yolo-tiny

Or NPM

npm install tfjs-yolo-tiny

Usage Example

import yolo, { downloadModel } from 'tfjs-yolo-tiny';

const model = await downloadModel();
const inputImage = webcam.capture();

const boxes = await yolo(inputImage, model);

// Display detected boxes
boxes.forEach(box => {
  const {
    top, left, bottom, right, classProb, className,
  } = box;

  drawRect(left, top, right-left, bottom-top, `${className} ${classProb}`)
});

API Docs

yolo(input, model, options)

Args

Param Type Default Description
input tf.Tensor - Expected shape (1, 416, 416, 3) Tensor representing input image (RGB 416x416)
model tf.Model - Tiny YOLO tf.Model
[options] Object See Below Optional, Additional Configs

If you're using a custom Tiny YOLO model or want to adjust the default filtering cutoffs, you may do so by passing an additional options object.

Example: yolo(inputImage, model, { classProbThreshold: 0.8 });

Option Type Default Description
[options.classProbThreshold] Number 0.4 Filter out classes below a certain threshold
[options.iouThreshold] Number 0.4 Filter out boxes that have an IoU greater than this threadhold (refer to tf.image.nonMaxSuppression)
[options.filterBoxesThreshold] Number 0.01 Threshold to filter out box confidence * class confidence
[options.maxBoxes] Number 2048 Number of max boxes to return, refer to tf.image.nonMaxSuppression. Note: The model itself can only return so many boxes.
[options.yoloAnchors] tf.Tensor See src/postprocessing.js (Advanced) Yolo Anchor Boxes, only needed if retraining on a new dataset
[options.width] Number 416 (Advanced) If your model's input width is not 416, only if you're using a custom model
[options.height] Number 416 (Advanced) If your model's input height is not 416, only if you're using a custom model
[options.numClasses] Number 80 (Advanced) If your model has a different number of classes, only if you're using a custom model
[options.classNames] Array.<String> See src/coco_classes.js (Advanced) If your model has non-MSCOCO class names, only if you're using a custom model

Returns

Returns an array of objects.

Property Type Description
top Number Pixels from top of image where bounding box starts
left Number Pixels from left of image where bounding box starts
bottom Number Pixels from top of image where box ends.
right Number Pixels from left of image where box ends.
classProb Number Probability of the class in the bounding box.
className String Human name of the class.

downloadModel(url)

Args

Param Type Default Description
url string See DEFAULT_MODEL_LOCATION Tiny YOLO Model config path. See tf.loadModel

Returns

Returns a Promise that can resolve to a tf.Model.

Contributing

PR's are more than welcome! Perf improvement or better test coverage are probably the two biggest areas of immediate need. If you have thoughts on extensibility as well, feel free to open an issue!

Install Dependencies

yarn install

Run Tests

If you're running tests, make sure to yarn add @tensorflow/tfjs@0.7.0 so that you you don't get tfjs package not found errors. If you're developing, make sure to remove tfjs as a dependency, as it'll start using the local version of tfjs intead of the peer version.

Note: Test coverage is poor, definitely don't rely on them to catch your errors.

yarn test

Build

yarn build

Or during development, use watch mode, you can use the demo app to test out changes.

yarn watch
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