MIR AI Camera, Начало работы

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4. Comissioning
MiR AI Camera Getting started (en) 09/2019 - v.1.0 ©Copyright 2019: Mobile Industrial Robots A/S. 27
CAUTION
This is one of the most important stages when setting up your MiR AI
Camera. It is vital that you follow the guide accurately to make sure your MiR
AI Camera performs as expected. The following section describes how to label
your MiR AI Camera the images correctly. It is highly recommended to read
this description before continuing to the step by step instructions following the
description.
Labeling
During the Pre-processing phase, MiR AI Training Tool detects candidate target objects,
frames them in the images where they appear, and attempts to cluster images with the
same target objects. In the Validation phase, there are two actions that must be performed:
• Create new label
The target objects must be given an appropriate label to categorize them under an object
type. The first time you select an image with a new target object, you must create a new
label. Only one target object is found per image, thus only one label must be applied per
image. As a general rule, if the appearance of target objects are the same, they should be
grouped under the same label. If two target objects similar in appearance are given two
separate labels, it is not guaranteed that MiR AI Camera can distinguish the difference.
For this reason, when creating a new label, it is important to choose a label name that cor-
rectly encapsulates the target object type that you are categorizing.
Table 4.1 provides an
overview of the correct and incorrect usage of labels for some example target objects.
You can train your camera to detect other target objects than those listed in the table.
Example tar-
get objects
Correct labeling Incorrect labeling
People All people go under one collective
label.
Example: person
Creating individual labels for
certain people.
Example: Sarah , John , workers ,
intruders , guests