JS method to obtain the top N color values ​​​​of an image

This time I will bring you the top N color value method of JS to get the top N color value of the picture. What are the precautions for getting the top N color value of the picture with JS. The following is a practical case, let's take a look.

Question Requirements

Find out the tag that appears most frequently on a page! ! !

Personal solution:

var eles = document.getElementsByTagName('*');
var rs = [];
for(var i=0; i<eles.length; i++) {
  var tag_name = eles[i].tagName.toLowerCase();
  if(undefined != tag_name) {
    if(inJsonArray(rs, tag_name)) {
      addWeight(rs, tag_name);
    }else {
      rs.push({
        tag : tag_name,
        weight : 1
      })
    }        
  }      
}
SortByWeight(rs);

Idea:

Get all the tags--cluster according to the tag name---sort according to the weight.

If there is a better way, please share it.

Let’s look at today’s question:

Obtaining the top N main color values ​​​​of a picture is very similar to the problem with the most labels above. There is a difference in data size, but everything else is the same.

The idea of ​​​​this problem is very clear. The first step is to get the image data; the second step is to cluster according to the color value; the third step is to sort the clustering results. So this time we will implement it based on this idea.

1. Data acquisition

Image data acquisition uses the getImageData() method of canvas to obtain the rgba of each pixel of the image. data.

var imgdatas=context.getImageData(0,0,150,150);//获取当前canvas数据
var imgdata = imgdatas.data;//获取rgba数据
var i = 0, len = imgdata.length;
var arr = [];
//将图片rgba数据push到新数组中
for(i ; i<len ; i+=4 ) {
  arr.push(imgdata[i]+','+imgdata[i+1]+','+imgdata[i+2]+','+imgdata[i+3]);  
}

In this way, you can get all the data of the picture, and the rest is a mathematical problem.

2. Data clustering

Remove duplication, merge the same color values, and record the number (weight) of the color value weight

Clustering There are many methods, including direct mathematical statistics, or k-means, decision trees, naive Bayes, support vector machines, etc. You can use whichever you like, but you still need to consider the applicability and efficiency of different methods. Something.
We will get such an array [{rgba: '21,12,45,0', weight: 12}, {...}] to record the color value and the number of occurrences,

3. Sorting of clustering results

Sort the json array obtained in the previous step. Sort from large to small or small to large according to the value of the attribute weight. Needless to say, the sorting algorithm.

4. Result preview

5. to Do

similar color values Merge

Is it necessary to merge similar rgba(234,234,234,1) and rgba(234,235,235,1) into one value? This will also involve issues such as similarity calculation.

Optimize clustering algorithm

Increase complexity, improve performance, and improve execution speed

Combined with some visualization things

6. Summary

For processing with large amounts of data, it is more appropriate to place it on the backend. After all, multi-end computing such as distributed frameworks can be used.

The browser’s ability to process data is still limited.

I believe you have mastered the method after reading the case in this article. For more exciting information, please pay attention to other related articles on the php Chinese website!

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