Confident Identification Object For Free
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How do you evaluate object detection?
Determining whether an object exists in the image (classification) Determining the location of the object (localization, a regression task).
How do you calculate map in object detection?
Precision & recall. Precision measures how accurate is your predictions. Recall measures how good you find all the positives. IOU (Intersection over union) Precision is the proportion of TP = 2/3 = 0.67. Recall is the proportion of TP out of the possible positives = 2/5 = 0.4.
What is map object detection?
The most common evaluation metric that is used in object recognition tasks is 'map', which stands for 'mean average precision'. It is a number from 0 to 100 and higher values are typically better, but its value is different from the accuracy metric in classification.
What is map metric?
In the mathematical theory of metric spaces, a metric map is a function between metric spaces that does not increase any distance (such functions are always continuous). They are also called Lipschitz functions with Lipschitz constant 1, nonexpansive maps, nonexpanding maps, weak contractions, or short maps.
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