robot-arm-opencv/robotArm.py at master · joemac875/robot-arm-opencv

OpenCV: OpenCV modules

To better understand hand tracking with OpenCV, and to develop a hand tracking model from the ground up, this page will be responsible for documenting the functionality of this code.

Style Guide

1. Define Type and Label Parameters
2. Go over Mathematical Framework (use Online LaTeX Equation Editor for fancy symbols, then write in using “/Block Equation”)
3. Summarize Functionality

Key Terms

• HSV
• Colorspace
• Masks
• Contour
• Convexity & Convexity Defects
• Reference Point

Global Data Members

global avgHSV1 
global avgHSV2
global avgHSV3
global hsv

avgContainer : list = [] # container for HSV values 

refPt : list = [0, 0, 0, 0] # holds x1, y1, x2, y2 coordinate values of {???}

screenHeight : int = 720 # height of window
screenWidth : int = 1280 # width of window

font : cv2.HersheyFonts = cv2.FONT_HERSHEY_SIMPLEX # font initialized

cap : cv2.VideoCapture = cv2.VideoCapture(0)

cv2.namedWindow('setup')
cv2.setMouseCallback('setup', setRectPoints)

averages = avgHSVs(1, refPt) 
calibrationPointsLRTB, calibrationPointsFB = calibration(averages, refPt)

DistLtoR = calibrationPointsLRTB[0] - calibrationPointsLRTB[1]
DistTtoB = calibrationPointsLRTB[3] - calibrationPointsLRTB[2]
DistFtoB = calibrationPointsFB[0] - calibrationPointsFB[1]