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[Doc] add readme for js packages (#421)

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* add contributor

* add package readme

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* refine ocr readme
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[中文版](./README_cn.md)
# mobilenet
mobilenet model can classify img. It provides simple interfaces to use. You can use your own category model to classify img.
<img src="https://img.shields.io/npm/v/@paddle-js-models/mobilenet?color=success" alt="version"> <img src="https://img.shields.io/bundlephobia/min/@paddle-js-models/mobilenet" alt="size"> <img src="https://img.shields.io/npm/dm/@paddle-js-models/mobilenet?color=orange" alt="downloads"> <img src="https://img.shields.io/npm/dt/@paddle-js-models/mobilenet" alt="downloads">
# Usage
```js
import * as mobilenet from '@paddle-js-models/mobilenet';
// You need to specify your model path and the binary file count
// If your has mean and std params, you need to specify them.
// map is the results your model can classify.
await mobilenet.load({
path,
mean: [0.485, 0.456, 0.406],
std: [0.229, 0.224, 0.225]
}, map);
// get the result the mobilenet model classified.
const res = await mobilenet.classify(img);
```
# Online experience
mobileNet：https://paddlejs.baidu.com/mobilenet
wine：https://paddlejs.baidu.com/wine
# Performance
<img alt="image" src="https://user-images.githubusercontent.com/43414102/156393394-ab1c9e4d-2960-4fcd-ba22-2072fa9b0e9d.png">

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[English](./README.md)
# mobilenet
mobilenet 模型可以对图片进行分类，提供的接口简单，使用者传入自己的分类模型去分类。
<img src="https://img.shields.io/npm/v/@paddle-js-models/mobilenet?color=success" alt="version"> <img src="https://img.shields.io/bundlephobia/min/@paddle-js-models/mobilenet" alt="size"> <img src="https://img.shields.io/npm/dm/@paddle-js-models/mobilenet?color=orange" alt="downloads"> <img src="https://img.shields.io/npm/dt/@paddle-js-models/mobilenet" alt="downloads">
# 使用
```js
import * as mobilenet from '@paddle-js-models/mobilenet';
// 使用者需要提供分类模型的地址和二进制参数文件个数，且二进制参数文件，参考 chunk_1.dat、chunk_2.dat，...
// 模型参数支持 mean 和 std。如果没有，则不需要传
// 还需要传递分类映射文件
await mobilenet.load({
path,
mean: [0.485, 0.456, 0.406],
std: [0.229, 0.224, 0.225]
}, map);
// 获取图片分类结果
const res = await mobilenet.classify(img);
```
# 在线体验
1000物品识别：https://paddlejs.baidu.com/mobilenet
酒瓶识别：https://paddlejs.baidu.com/wine
# 效果
<img alt="image" src="https://user-images.githubusercontent.com/43414102/156393394-ab1c9e4d-2960-4fcd-ba22-2072fa9b0e9d.png">