对照测试

android/app/src/main/java/org/tensorflow/lite/examples/poseestimation/ml/PoseNet.kt

@@ -204,36 +204,14 @@ class PoseNet(private val interpreter: Interpreter, private var gpuDelegate: Gpu
             )
             totalScore += confidenceScores[idx]
         }
-
-        // 在此部分中添加角度数据和合格率数据
-        // 遍历 keyPoints
-        keypointList.forEach { keypoint ->
-            // 获取当前关键点的位置
-            val x = keypoint.coordinate.x
-            val y = keypoint.coordinate.y
-
-            // 假设我们计算胸部与左右肩膀之间的角度（这里只是示例，具体取决于你的模型）
-            if (keypoint.bodyPart == BodyPart.LEFT_SHOULDER || keypoint.bodyPart == BodyPart.RIGHT_SHOULDER) {
-                // 获取左肩和右肩的坐标
-                val leftShoulder = keypointList.first { it.bodyPart == BodyPart.LEFT_SHOULDER }
-                val rightShoulder = keypointList.first { it.bodyPart == BodyPart.RIGHT_SHOULDER }
-
-                // 计算肩膀角度
-                val angle = calculateAngle(
-                    leftShoulder.coordinate.x,
-                    leftShoulder.coordinate.y,
-                    rightShoulder.coordinate.x,
-                    rightShoulder.coordinate.y
-                )
-
-            }
-
-            // 添加合格率数据
-        }
+        //计算并得到关键点之间的角度关系
+        val keypoint = KeypointAngles()
+        keypoint.csAngles(keypointList.toList())
 
         // 返回一个包含关键点和总分数的Person对象
         return Person(keyPoints = keypointList.toList(), score = totalScore / numKeypoints)
     }
+
     class KeypointAngles {
         // 用来存储角度的列表
         val angles = mutableListOf<Float>()
@@ -322,9 +300,6 @@ class PoseNet(private val interpreter: Interpreter, private var gpuDelegate: Gpu
         }
     }
 
-
-
-
     // 返回上一次推理的时间
     override fun lastInferenceTimeNanos(): Long = lastInferenceTimeNanos