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https://github.com/ModelDepot/tfjs-yolo-tiny

In-Browser Object Detection using Tiny YOLO on Tensorflow.js
https://github.com/ModelDepot/tfjs-yolo-tiny

browser computer-vision deep-learning detection machine-learning npm-package object-detection tensorflow tensorflow-js tfjs yolo yolo-models

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

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README 

        
  



# ⚡️ Fast In-Browser Object Detection 👀



Detect objects in images right in your browser using [Tensorflow.js](https://js.tensorflow.org/)! Currently takes ~800ms

to analyze each frame on Chrome MBP 13" mid-2014.



Supports [`Tiny YOLO`](https://pjreddie.com/darknet/yolo/), as of right now,

 [`tfjs`](https://github.com/tensorflow/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](https://modeldepot.github.io/tfjs-yolo-tiny-demo/)



(You can only get so far with 1 FPS)



![yolo person detection](https://github.com/ModelDepot/tfjs-yolo-tiny/raw/master/assets/demo.gif)



## Install



### Yarn

    yarn add tfjs-yolo-tiny

### Or NPM

    npm install tfjs-yolo-tiny



## Usage Example

```javascript

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](https://js.tensorflow.org/api/0.8.0/#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/[email protected]`

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](https://github.com/ModelDepot/tfjs-yolo-tiny-demo)

to test out changes.



```

yarn watch

```