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@@ -125,7 +125,7 @@ This table is subject to changes, as new metrics will be added in the future.
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| QUANTITY PER OBJECT TYPE | Number of identified objects for each type in the image. | PREDICTION | When Task Type is Object Detection or Semantic Segmentation | A one dimension integer array. | One metric for each output label |
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| TOTAL OBJECTS | Total number of identified objects independently from the object type. | PREDICTION | When Task Type is Object Detection or Semantic Segmentation | An integer value. ||
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| OBJECT TYPES COUNT | Number of different object types identified in the image. It differs from the other because it only counts the number of different labels and not the number of objects per labels or objects in total. | PREDICTION | When Task Type is Object Detection or Semantic Segmentation | An integer value. ||
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| TRACKING OBJECT POSITION |Array composed of distance, sine and cosine of the angle between the center of the image and the center of the polygon or bounding box| PREDICTION | When Task Type is Object Detection or Semantic Segmentation | An one dimensional array. ||
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| TRACKING OBJECT POSITION |Polars coordinates of the farthest polygon between the center of the image. It is an array with three elements: distance, cos-angle and sin-angle.| PREDICTION | When Task Type is Object Detection or Semantic Segmentation | An one dimensional array. ||
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| MODEL ENTROPY | Uncertainty of the model predicting objects in the images | PREDICTION PROBABILITY | When Task Type is Object Detection or Semantic Segmentation | A floating point value. ||
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