I got this behavior after use the object classification, the Huskylens still show Object:ID1 on screen.geab wrote:I have uploaded 0.4.9Class firmware from the Github and tried to train 3 different objects using a white paper as background.
When I finish the training Huskylens can recognize the 3 objects and differentiate them - Nice!
But whenever I point Huskylens at an area (eg wodden table or the white paper) with none of the 3 objects it will still display eg Object:ID1 or 2 on the screen.
Could you share how you did the training of the gestures in a tutorial?
Cheers, Gernot
from huskylib import HuskyLensLibrary
hl= HuskyLensLibrary("I2C","",address=0x32)
print(hl.knock())
#Description: Get the number of frame HUSKYLENS have processed.
print("frameNumber:", hl.frameNumber())
#Description: Get the number of learned and unlearned objects on the screen.
print("count:", hl.count())
#Description: Get the total number of learned objects for the current running algorithm, objects do not need to be present on screen.
print("learnedObjCount:", hl.learnedObjCount())
hl.algorthim("ALGORITHM_OBJECT_CLASSIFICATION")