The function enables the automatic display of the landmark on pose/hand detected on the stage.
Syntax: enablebox()
[PictoBloxExtension]
Quarky Ultimate Robots
Extension Description
Controls the various configurations of the Quarky robots.
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Available in: Block Coding, Python Coding
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Mode: Stage Mode, Upload Mode
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WiFi Required: No
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Compatible Hardware in Block Coding: Quarky
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Compatible Hardware in Python: Quarky
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Object Declaration in Python: Not Applicable
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Extension Catergory: Quarky
Introduction
Python Functions
The function disables the automatic display of the landmark on pose/hand detected on the stage.
Syntax: disablebox()
This function is used to analyze the image received as input from the stage, for human pose detection.
Syntax: analysestage()
This function returns the x position of the pose landmark detected. The position is mapped with the stage coordinates.
Syntax: x(landmark_number = 1, pose_number = 1)
This function returns the y position of the pose landmark detected. The position is mapped with the stage coordinates.
Syntax: y(landmark_number = 1, pose_number = 1)
The function tells whether the human pose is detected or not.
Syntax: isdetected(landmark_number = 1, pose_number = 1)
This function is used to analyze the image received as input from the camera, for human hand detection.
Syntax: analysehand()
The function tells whether the human hand is detected or not.
Syntax: ishanddetected()
This function returns the specified parameter of the hand landmark detected.
Syntax: gethandposition(parameter = 1, landmark_number = 4)
This function returns the x position of the hand detected. The position is mapped with the stage coordinates.
Syntax: handx()
This function returns the y position of the hand detected. The position is mapped with the stage coordinates.
Syntax: handy()
The function adds the specified text data to the specified class.
Syntax: pushdata(text_data = “your text”, class_label = “class”)
The function trains the NLP model with the data added with pushdata() function.
Syntax: train()
The function resets and clears the NLP model.
Syntax: reset()
The function analyses the specified test and provides the class name under which it has been classified by the NLP model.
Syntax: analyse(text = “your text”)
The function is used to control the state of the camera.
Syntax: video(video_state = “on”, transparency = 1)
The function enables the automatic display of the box on object detection on the stage.
Syntax: enablebox()
The function disables the automatic display of the box on object detection on the stage.
Syntax: disablebox()
This function is used to set the threshold for the confidence (accuracy) of object detection, 0 being low confidence and 1 being high confidence.
Syntax: setthreshold(threshold = 0.5)
This function is used to analyze the image received as input from the camera, for objects.
Syntax: analysecamera()
This function is used to analyze the image received as input from the stage, for objects.
Syntax: analysestage()
This function returns the total number of objects detected in the camera feed or the stage.
Syntax: count()
This function is used to get the class name of the analyzed object.
Syntax: classname(object = 1)
This function returns the x position of the object detected. You can specify the object for which the value is needed. The position is mapped with the stage coordinates.
Syntax: x(object = 1)
This function returns the y position of the object detected. You can specify the object for which the value is needed. The position is mapped with the stage coordinates.
Syntax: y(object = 1)
This function returns the width of the object detected. You can specify the object for which the value is needed. The position is mapped with the stage coordinates.
Syntax: width(object = 1)
This function returns the height of the object detected. You can specify the object for which the value is needed. The position is mapped with the stage coordinates.
Syntax: height(object = 1)
This function is used to get the confidence (accuracy) of object detection, 0 being low confidence and 1 being high confidence.
Syntax: confidence(object = 1)
The function returns whether the specified signal is detected in the analysis or not.
Syntax: issignaldetected(signal_name = “Go”)
The function returns the specified parameter for the specified signal detected.
Syntax: getsignaldetail(signal_name = “Go”, parameter_value = 1)
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