update results documentation

Outputs.md

@@ -6,10 +6,12 @@ Result of `humand.detect()` is a single object that includes data for all enable
 
 ```js
 result = {
-  version:         // <string> version string of the human library
+  timestamp:       // timestamp in miliseconds when detection occured
+  canvas:          // optional processed canvas
   face:            // <array of detected objects>
   [
     {
+      id,          // <number> face id number
       confidence,  // <number> returns faceConfidence if exists, otherwise boxConfidence
       faceConfidence // <number> confidence in detection box after running mesh
       boxConfidence  // <number> confidence in detection box before running mesh
@@ -18,10 +20,18 @@ result = {
       mesh,        // <array of 3D points [x, y, z]> 468 base points & 10 iris points, normalized to input impact size
       meshRaw,     // <array of 3D points [x, y, z]> 468 base points & 10 iris points, normalized to range of 0..1
       annotations, // <list of object { landmark: array of points }> 32 base annotated landmarks & 2 iris annotations
-      iris,        // <number> relative distance of iris to camera, multiple by focal lenght to get actual distance
       age,         // <number> estimated age
       gender,      // <string> 'male', 'female'
-      embedding,   // <array>[float] vector of 192 values used for face similarity compare
+      genderConfidence  // <number> confidence in gender detection
+      embedding,   // <array>[float] vector of number values used for face similarity compare
+      iris,        // <number> relative distance of iris to camera, multiple by focal lenght to get actual distance
+      emotion:     // <array of emotions> returns multiple possible emotions for a given face, each with probability
+      [
+        {
+          score,       // <number> probabily of emotion
+          emotion,     // <string> 'angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'
+        }
+      ],
       rotation: {
         angle:     // 3d face rotation values in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees                 
           {
@@ -31,13 +41,6 @@ result = {
           }
         matrix: [] // flat array of [3,3] that can be directly used for GL matrix rotations such as in Three.js
       }
-      emotion:     // <array of emotions> returns multiple possible emotions for a given face, each with probability
-      [
-        {
-          score,       // <number> probabily of emotion
-          emotion,     // <string> 'angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'
-        }
-      ],
       tensor:      // if config.face.detector.return is set to true, detector will return
                    // a raw tensor containing cropped image of a face
                    // note that tensors must be explicitly disposed to free memory by calling tensor.dispose();
@@ -46,16 +49,20 @@ result = {
   body:            // <array of detected objects>
   [
     {
+      id,          // body id number
       score,       // <number>, overal detection score, only used for 'posenet', not used for 'blazepose'
       keypoints,   // for 'posenet': <array of 2D landmarks [ score, landmark, position [x, y] ]> 17 annotated landmarks
                    // for 'blazepose': <array of 2D landmarks [ score, landmark, position [x, y, z], presence ]>
                    //   39 annotated landmarks for full or 31 annotated landmarks for upper
                    //   presence denotes probability value in range 0..1 that the point is located within the frame
+      box,         // <array [x, y, width, height]>, clamped and normalized to input image size
+      boxRaw,      // <array [x, y, width, height]>, unclamped and normalized to range of 0..1     
     }
   ],
   hand:            // <array of detected objects>
   [
     {
+      id,          // hand id number
       confidence,  // <number>,
       box,         // <array [x, y, width, height]>, clamped and normalized to input image size
       boxRaw,      // <array [x, y, width, height]>, unclamped and normalized to range of 0..1
@@ -69,8 +76,6 @@ result = {
       score,       // <number>
       class,       // <number> class id based on coco labels
       label,       // <string> class label based on coco labels
-      center,      // <array [x, y]>, clamped and normalized to input image size
-      centerRaw,   // <array [x, y]>, unclamped and normalized to range of 0..1
       box,         // <array [x, y, width, height]>, clamped and normalized to input image size
       boxRaw,      // <array [x, y, width, height]>, unclamped and normalized to range of 0..1
     }
@@ -84,6 +89,8 @@ result = {
   ],
   performance = {  // performance data of last execution for each module measuredin miliseconds
                    // note that per-model performance data is not available in async execution mode
+    frames,        // total number of frames processed
+    cached,        // total number of frames where some cached values were used
     backend,       // time to initialize tf backend, keeps longest value measured
     load,          // time to load models, keeps longest value measured
     image,         // time for image processing
@@ -93,6 +100,7 @@ result = {
     face,          // model time
     agegender,     // model time
     emotion,       // model time
+    change,        // frame change detection time
     total,         // end to end time
   }
 }