Unity实现菜品识别的示例代码

using System;
 
/// <summary>
/// 菜品识别
/// </summary>
[Serializable]
public class DishRecognition 
{
    /// <summary>
    /// 唯一的log id，用于问题定位
    /// </summary>
    public float log_id;
    /// <summary>
    /// 返回结果数目，及result数组中的元素个数
    /// </summary>
    public int result_num;
    /// <summary>
    /// 菜品识别结果数组
    /// </summary>
    public DishRecognitionResult[] result;
}
 
/// <summary>
/// 菜品识别结果
/// </summary>
[Serializable]
public class DishRecognitionResult
{
    /// <summary>
    /// 菜名
    /// </summary>
    public string name;
    /// <summary>
    /// 卡路里，每100g的卡路里含量
    /// </summary>
    public float calorie;
    /// <summary>
    /// 识别结果中每一行的置信度值，0-1
    /// </summary>
    public float probability;
    /// <summary>
    /// 百科词条
    /// </summary>
    public BaikeInfo baike_info;
}
 
[Serializable]
public class BaikeInfo
{
    /// <summary>
    /// 对应识别结果百度百科页面链接
    /// </summary>
    public string baike_url;
    /// <summary>
    /// 对应识别结果百科图片链接
    /// </summary>
    public string image_url;
    /// <summary>
    /// 对应识别结果百科内容描述
    /// </summary>
    public string description;
}

using System;
using System.Collections.Generic;
using UnityEngine;
 
/// <summary>
/// 图像识别
/// </summary>
public class ImageRecognition 
{
    //以下信息于百度开发者中心控制台创建应用获取
    private const string appID = "";
    private const string apiKey = "";
    private const string secretKey = "";
 
    /// <summary>
    /// 菜品识别
    /// </summary>
    /// <param name="bytes">图片字节数据</param>
    /// <param name="topNum">返回预测得分top结果数，默认为5</param>
    /// <param name="filterThreshold">默认0.95，可以通过该参数调节识别效果，降低非菜识别率.</param>
    /// <param name="baikeNum">    返回百科信息的结果数，默认不返回</param>
    /// <returns></returns>
    public static DishRecognition Dish(byte[] bytes, int topNum = 5, float filterThreshold = 0.95f, int baikeNum = 0)
    {
        var client = new Baidu.Aip.ImageClassify.ImageClassify(apiKey, secretKey);
        try
        {
            var options = new Dictionary<string, object>
            {
                { "top_num", topNum },
                { "filter_threshold", Mathf.Clamp01(filterThreshold)},
                { "baike_num", baikeNum}
            };
            var response = client.DishDetect(bytes, options);
            DishRecognition dishRecognition = JsonConvert.DeserializeObject<DishRecognition>(response.ToString());
            return dishRecognition;
        }
        catch (Exception error)
        {
            Debug.LogError(error);
        }
        return null;
    }
}

using System.IO;
using UnityEngine;
 
public class Example : MonoBehaviour
{
    private void Start()
    {
        ImageRecognition.Dish(File.ReadAllBytes(Application.dataPath + "/Picture.jpg"));
    }
}