Detected class

To represent an object detected on the picture, the model use an object of the class “Detected”, which is composed of:

• x_center

• y_center

Both double, they represent the coordinates of the center of the bounding box. x is the horizontal position between 0 and 160, and y the vertical position between 0 and 120. The origin is on the top left corner of the image.

• width

• height

Both double again, they represent the size of the bounding box. Combined with the center above, it allows to determine the position of the detected object on the picture

• Confidence

A double between 0 and 1, which represents the confidence of the model about this prediction, 1 being the best

• label

If the user is using the default trained weights, then the label will contain a string representing the block (Red Block, Green Block, Blue Block, Black Block, Black Ball, Epuck), or it will contains the class number if some custom weights are used.

The function get_detection() return a list of Detected Object, which contains between 0 and N items depending on the number of objects found on the picture, so the code usually looks like:

img = np.array(robot.get_camera())
detection = robot.get_detection(img)

for item in detection:

    #do something with each object found
    if item.label == "Blue Block":

        #do something with the blue block