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tfjs-yolo-tiny

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

ApplicationsObject detectionJavaScript
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创建于 2018-04-07 · 更新于 2026-09-12 · 今日第 17534 名
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ModelDepot/tfjs-yolo-tiny 排名第 17,534，有 534 个星标。

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关键参数与规格
关键参数与规格
参数值
语言JavaScript
类别Applications
子类别Object detection
关键词Computer vision, JavaScript
星标数534
分叉数88
贡献者2
创建日期2018-04-07
更新日期2026-09-12
1 天星标数0
7 天星标数0
排名17,534
上次排名17,318
排名变化-216
7 天星标排名16,157
上次 7 天星标排名16,163
7 天星标排名变化6
总星标排名18,379
上次总星标排名18,354
总星标排名变化-25
README 摘录

⚡️ 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.

常见问题

记录了多少星标和分叉？

ModelDepot/tfjs-yolo-tiny 有 534 个星标和 88 个分叉。

仓库排名是多少？

ModelDepot/tfjs-yolo-tiny 排名第 17,534。

记录的语言和类别是什么？

ModelDepot/tfjs-yolo-tiny 有 534 个星标，语言为 JavaScript，类别为 Applications。

哪个仓库排名最接近？

ModelDepot/tfjs-yolo-tiny 与 S-Trespassing/claw-in-chrome 比较，后者排名第 17,535，有 534 个星标。

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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