人体分析

    人体关键点识别

    对于输入的一张图片(可正常解码,且长宽比适宜),检测图片中的所有人体,输出每个人体的21个主要关键点,包含头顶、五官、脖颈、四肢等部位,同时输出人体的坐标信息和数量

    支持多人检测、人体位置重叠、遮挡、背面、侧面、中低空俯拍、大动作等复杂场景。

    21个关键点的位置:头顶、左耳、右耳、左眼、右眼、鼻子、左嘴角、右嘴角、脖子、左肩、右肩、左手肘、右手肘、左手腕、右手腕、左髋部、右髋部、左膝、右膝、左脚踝、右脚踝。示意图如下,正在持续扩展更多关键点,敬请期待。

    单人场景:

    多人场景:

    public void BodyAnalysisDemo() {
    	var image = File.ReadAllBytes("图片文件路径");
    	// 调用人体关键点识别,可能会抛出网络等异常,请使用try/catch捕获
    	var result = client.BodyAnalysis(image);
    	Console.WriteLine(result);
    }

    人体关键点识别 请求参数详情

    参数名称 是否必选 类型 说明
    image byte[] 二进制图像数据

    人体关键点识别 返回数据参数详情

    接口除了返回人体框和每个关键点的坐标信息外,还会输出人体框和关键点的概率分数,实际应用中可以基于概率分数进行过滤,排除掉分数低的误识别“无效人体”推荐的过滤方案:当关键点得分大于0.2的个数大于3,且人体框的得分大于0.03时,才认为是有效人体

    实际应用中,可根据对误识别、漏识别的容忍程度,调整阈值过滤方案,灵活应用,比如对误识别容忍低的应用场景,人体框的得分阈值可以提到0.05甚至更高。

    字段 是否必选 类型 说明
    person_num uint32 人体数目
    person_info object[] 人体姿态信息
    +body_parts object 身体部位信息,包含21个关键点
    ++top_head object 头顶
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++left_eye object 左眼
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++right_eye object 右眼
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++nose object 鼻子
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++left_ear object 左耳
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++right_ear object 右耳
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++left_mouth_corner object 左嘴角
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++right_mouth_corner object 右嘴角
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++neck object 颈部
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++left_shoulder object 左肩
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++right_shoulder object 右肩
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++left_elbow object 左手肘
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++right_elbow object 右手肘
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++left_wrist object 左手腕
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++right_wrist object 右手腕
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++left_hip object 左髋部
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++right_hip object 右髋部
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++left_knee object 左膝
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++right_knee object 右膝
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++left_ankle object 左脚踝
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    ++right_ankle object 右脚踝
    +++x float x坐标
    +++y float y坐标
    +++score float 概率分数
    +location object 人体坐标信息
    ++height float 人体区域的高度
    ++left float 人体区域离左边界的距离
    ++top float 人体区域离上边界的距离
    ++width float 人体区域的宽度
    ++score float 人体框的概率分数
    log_id uint64 唯一的log id,用于问题定位

    说明:

    1、body_parts,一共21个part,每个part包含x,y两个坐标,如果part被截断,则x、y坐标为part被截断的图片边界位置,part顺序以实际返回顺序为准。

    2、接口返回人体坐标框和每个关键点的置信度分数,在应用时可综合置信度score分数,过滤掉置信度低的“无效人体”,建议过滤方法:当关键点得分大于0.2的个数大于3,且人体框的分数大于0.03时,才认为是有效人体。实际应用中,可根据对误识别、漏识别的容忍程度,调整阈值过滤方案,灵活应用。

    人体关键点识别 返回示例

    {
    	"person_num": 2,
    	"person_info": [
    		{
    			"body_parts": {
    				"left_hip": {
    					"y": 573,
    					"x": 686.09375,
    					"score": 0.78743487596512
    				},
    				"top_head": {
    					"y": 242.53125,
    					"x": 620,
    					"score": 0.87757384777069
    				},
    				"right_mouth_corner": {
    					"y": 308.625,
    					"x": 606.78125,
    					"score": 0.90121293067932
    				},
    				"neck": {
    					"y": 335.0625,
    					"x": 620,
    					"score": 0.84662038087845
    				},
    				"left_shoulder": {
    					"y": 361.5,
    					"x": 699.3125,
    					"score": 0.83550786972046
    				},
    				"left_knee": {
    					"y": 731.625,
    					"x": 699.3125,
    					"score": 0.83575332164764
    				},
    				"left_ankle": {
    					"y": 877.03125,
    					"x": 725.75,
    					"score": 0.85220056772232
    				},
    				"left_mouth_corner": {
    					"y": 308.625,
    					"x": 633.21875,
    					"score": 0.91475087404251
    				},
    				"right_elbow": {
    					"y": 348.28125,
    					"x": 461.375,
    					"score": 0.81766486167908
    				},
    				"right_ear": {
    					"y": 282.1875,
    					"x": 593.5625,
    					"score": 0.86551451683044
    				},
    				"nose": {
    					"y": 295.40625,
    					"x": 620,
    					"score": 0.90894532203674
    				},
    				"left_eye": {
    					"y": 282.1875,
    					"x": 633.21875,
    					"score": 0.89628517627716
    				},
    				"right_eye": {
    					"y": 282.1875,
    					"x": 606.78125,
    					"score": 0.89676940441132
    				},
    				"right_hip": {
    					"y": 586.21875,
    					"x": 593.5625,
    					"score": 0.79803824424744
    				},
    				"left_wrist": {
    					"y": 374.71875,
    					"x": 884.375,
    					"score": 0.89635348320007
    				},
    				"left_ear": {
    					"y": 295.40625,
    					"x": 659.65625,
    					"score": 0.86607384681702
    				},
    				"left_elbow": {
    					"y": 361.5,
    					"x": 791.84375,
    					"score": 0.83910942077637
    				},
    				"right_shoulder": {
    					"y": 348.28125,
    					"x": 553.90625,
    					"score": 0.85635334253311
    				},
    				"right_ankle": {
    					"y": 890.25,
    					"x": 580.34375,
    					"score": 0.85149073600769
    				},
    				"right_knee": {
    					"y": 744.84375,
    					"x": 580.34375,
    					"score": 0.83749794960022
    				},
    				"right_wrist": {
    					"y": 348.28125,
    					"x": 368.84375,
    					"score": 0.83893859386444
    				}
    			},
    			"location": {
    				"height": 703.20654296875,
    				"width": 652.61810302734,
    				"top": 221.92272949219,
    				"score": 0.99269664287567,
    				"left": 294.03039550781
    			}
    		},
    		{
    			"body_parts": {
    				"left_hip": {
    					"y": 576,
    					"x": 1239.5625,
    					"score": 0.84608125686646
    				},
    				"top_head": {
    					"y": 261.15625,
    					"x": 1176.59375,
    					"score": 0.871442258358
    				},
    				"right_mouth_corner": {
    					"y": 336.71875,
    					"x": 1164,
    					"score": 0.90951544046402
    				},
    				"neck": {
    					"y": 361.90625,
    					"x": 1176.59375,
    					"score": 0.85904294252396
    				},
    				"left_shoulder": {
    					"y": 361.90625,
    					"x": 1239.5625,
    					"score": 0.8512310385704
    				},
    				"left_knee": {
    					"y": 714.53125,
    					"x": 1277.34375,
    					"score": 0.82312393188477
    				},
    				"left_ankle": {
    					"y": 853.0625,
    					"x": 1315.125,
    					"score": 0.83786374330521
    				},
    				"left_mouth_corner": {
    					"y": 336.71875,
    					"x": 1189.1875,
    					"score": 0.90610301494598
    				},
    				"right_elbow": {
    					"y": 387.09375,
    					"x": 1025.46875,
    					"score": 0.88956367969513
    				},
    				"right_ear": {
    					"y": 311.53125,
    					"x": 1138.8125,
    					"score": 0.86518502235413
    				},
    				"nose": {
    					"y": 324.125,
    					"x": 1176.59375,
    					"score": 0.9168484210968
    				},
    				"left_eye": {
    					"y": 311.53125,
    					"x": 1189.1875,
    					"score": 0.91715461015701
    				},
    				"right_eye": {
    					"y": 311.53125,
    					"x": 1164,
    					"score": 0.90343600511551
    				},
    				"right_hip": {
    					"y": 576,
    					"x": 1164,
    					"score": 0.81976848840714
    				},
    				"left_wrist": {
    					"y": 298.9375,
    					"x": 1378.09375,
    					"score": 0.86095398664474
    				},
    				"left_ear": {
    					"y": 311.53125,
    					"x": 1201.78125,
    					"score": 0.86899447441101
    				},
    				"left_elbow": {
    					"y": 324.125,
    					"x": 1315.125,
    					"score": 0.89198768138885
    				},
    				"right_shoulder": {
    					"y": 387.09375,
    					"x": 1101.03125,
    					"score": 0.85161662101746
    				},
    				"right_ankle": {
    					"y": 878.25,
    					"x": 1151.40625,
    					"score": 0.83667933940887
    				},
    				"right_knee": {
    					"y": 727.125,
    					"x": 1151.40625,
    					"score": 0.85485708713531
    				},
    				"right_wrist": {
    					"y": 387.09375,
    					"x": 949.90625,
    					"score": 0.83042001724243
    				}
    			},
    			"location": {
    				"height": 670.80139160156,
    				"width": 524.25476074219,
    				"top": 241.42504882812,
    				"score": 0.98725789785385,
    				"left": 902.15216064453
    			}
    		}
    	],
    	"log_id": "6362401025381690607"
    }
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