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merged 2 commits into from
Mar 9, 2019
Merged

Update docs for body-pix and toxicity. #169

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6803966
update documentation
annxingyuan Mar 7, 2019
9063104
update readme
annxingyuan Mar 8, 2019
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12 changes: 6 additions & 6 deletions body-pix/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -17,8 +17,8 @@ To keep track of issues we use the [tensorflow/tfjs](https://github.com/tensorfl
You can use this as standalone es5 bundle like this:

```html
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs"></script>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/body-pix"></script>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@1.0.0"></script>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/body-pix@1.0.0"></script>
```

Or you can install it via npm for use in a TypeScript / ES6 project.
Expand Down Expand Up @@ -81,9 +81,9 @@ An object containing a width, height, and a binary array with 1 for the pixels t
<html>
<head>
<!-- Load TensorFlow.js -->
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.13.3"></script>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@1.0.0"></script>
<!-- Load BodyPix -->
<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/body-pix@0.0.4"></script>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/body-pix@1.0.0"></script>
</head>

<body>
Expand Down Expand Up @@ -201,9 +201,9 @@ An object containing a width, height, and an array with a part id from 0-24 for
<html>
<head>
<!-- Load TensorFlow.js -->
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.13.3"></script>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@1.0.0"></script>
<!-- Load BodyPix -->
<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/body-pix@0.0.4"></script>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/body-pix@1.0.0"></script>
</head>

<body>
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3 changes: 2 additions & 1 deletion toxicity/README.md
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Expand Up @@ -47,7 +47,8 @@ toxicity.load(threshold).then(model => {
model.classify(sentences).then(predictions => {
// `predictions` is an array of objects, one for each prediction head,
// that contains the raw probabilities for each input along with the
// final prediction boolean given the threshold.
// final prediction in `match` (either `true` or `false`).
// If neither prediction exceeds the threshold, `match` is `null`.

console.log(predictions);
/*
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