[游戏开发]unity百度AI人体分析

前言

元旦的时候睡不着，也不想让自己闲下来颓废，就接一下百度AI玩玩，定位到百度智能云的人体识别。

实现步骤

一、百度智能云人体分析应用创建，得到自己的API Key和Secret Key

二、下载相应的SDK

文件下载解压之后得到这四个文件夹

文件夹后面的数字是指.net框架的版本，可以在Unity工程中去设置，我这里使用的是.net4，将net40文件夹中的dll文件导入unity工程中的Plugins文件夹中



三、创建UI界面，用于展示

四、查看API文档，编写代码，实现功能

因为此次所演示的主要是手势识别，所以主要查看手势识别的API参数，以上圈起来的是我此次所用到的。

using System.Collections;
using System.Collections.Generic;
using UnityEngine;
using Baidu.Aip.BodyAnalysis;
using System.IO;
using UnityEngine.UI;

public class BodyDetect : MonoBehaviour
{
    //自己的百度智能云api_key和secret_key
    //public string app_id;
    public string api_key;
    public string secret_key;

    Body client;
    private string deviceName;
    private WebCamTexture webCamTex;
    
    public Text result_message;//百度AI结果数据
    public Text detectedGesture_message;//展示手势名称
    private int Frame = 30;//摄像画面的帧数

    public int width;//画面大小
    public int height;
    
    public Camera cam;//截图摄像头
    public string imageName;

    RawImage panelRawimage;

    float timer = 0;
    float CupPictureTime = 1f;

    string imagepath = Application.streamingAssetsPath + "/image.jpg";
    // Use this for initialization
    void Start()
    {
        StartCoroutine(OpenCamera());
        client = new Body(api_key, secret_key);
        client.Timeout = 60000;  //超时时间
        panelRawimage = transform.GetComponent<RawImage>();
    }

    // Update is called once per frame
    void Update()
    {
        CupScreen();
    }

    /// <summary>
    /// 调用摄像机
    /// </summary>
    /// <returns></returns>
    IEnumerator OpenCamera()
    {
        yield return Application.RequestUserAuthorization(UserAuthorization.WebCam);
        if (Application.HasUserAuthorization(UserAuthorization.WebCam))
        {
            WebCamDevice[] devices = WebCamTexture.devices;
            deviceName = devices[0].name;
            webCamTex = new WebCamTexture(deviceName, width, height, Frame);//设置摄像机摄像的区域
            webCamTex.Play();//开始摄像    
            panelRawimage.texture = webCamTex;
        }
    }

    /// <summary>
    /// 截屏
    /// </summary>
    void CupScreen()
    {
        timer += Time.deltaTime;
        if (timer > CupPictureTime)
        {
            File.Delete(imagepath);
            Texture2D screenShot;
            RenderTexture rt = new RenderTexture(width, height, 1);
            cam.targetTexture = rt;
            cam.Render();
            RenderTexture.active = rt;
            screenShot = new Texture2D(width, height, TextureFormat.RGB24, false);
            screenShot.ReadPixels(new Rect(0, 0, width, height), 0, 0);
            screenShot.Apply();
            imageName = imagepath;
            SaveImage(screenShot, 0, 0, width, height);
            timer = 0;
        }
    }
 	/// <summary>
    /// 保存图片
    /// </summary>
    /// <param name="tex"></param>
    /// <param name="x"></param>
    /// <param name="y"></param>
    /// <param name="Width"></param>
    /// <param name="Height"></param>
    /// <returns></returns>
    byte[] SaveImage(Texture2D tex, int x, int y, float Width, float Height)
    {
        Color[] pixels = new Color[(int)(Width * Height)];
        Texture2D newTex = new Texture2D(Mathf.CeilToInt(Width), Mathf.CeilToInt(Height));
        pixels = tex.GetPixels(x, y, (int)Width, (int)Height);//批量获取点像素
        newTex.SetPixels(pixels);
        newTex.anisoLevel = 2;
        newTex.Apply();
        byte[] bytes = newTex.EncodeToJPG();
        System.IO.File.WriteAllBytes(imageName, bytes);//将截图后的新图片存在相应的路径中
        GetGestureFromBaiduAI(imageName);
        return bytes;
    }


    /// <summary>
    /// 上传图片，获取返回结果，并且解析显示
    /// </summary>
    /// <param name="filesPath"></param>
    public void GetGestureFromBaiduAI(string path)
    {
        var image = File.ReadAllBytes(path);
        try
        {
            var result = client.Gesture(image);
            result_message.text = result.ToString();
            string[] msgStr = result_message.text.Split(',');
            //解析返回的数据获取手势名称
            for (int i = 0; i < msgStr.Length; i++)
            {
                if (msgStr[i].Contains("classname"))
                {
                    string[] strArr = msgStr[i].Split(':');
                    detectedGesture_message.text = strArr[2];
                    break;
                }
            }
        }
        catch (System.Exception)
        {
            throw;
        }
    }
}

五、给脚本赋值，运行展示效果