Tag Archives: Python

In this lesson we create an Analog Clock Model with proper hand motion. The code developed in the lesson is shown below:

from vpython import *
import numpy as np
import time
clockR=1
clockT=clockR/10
majorTickL=clockR/7
majorTickT=2*np.pi*clockR/400
majorTickW=clockT*1.2

minorTickL=clockR/12
minorTickT=2*np.pi*clockR/600
minorTickW=clockT*1.2

minuteHandL=clockR-majorTickL
minuteHandT=minuteHandL/25
minuteHandOffset=clockT/2+minuteHandT

hourHandL=.75*minuteHandL
hourHandT=minuteHandT*1.25
hourHandOffset=clockT+hourHandT

secondHandL=clockR-majorTickL/2
secondHandT=minuteHandL/50
secondHandOffset=clockT*1.5+minuteHandT

hubRadius=clockT/2

hourAngle=np.pi/2
minuteAngle=np.pi/2
minInc=.0001
hourInc=minInc/12
secondAngle=np.pi/2
secondInc=minInc*60

for theta in np.linspace(0,2*np.pi,13):
    majorTick=box(axis=vector(clockR*np.cos(theta),clockR*np.sin(theta),0), color=color.black, length=majorTickL, width=majorTickW, height=majorTickT, pos=vector((clockR-majorTickL/2)*np.cos(theta),(clockR-majorTickL/2)*np.sin(theta),0))
for theta in np.linspace(0,2*np.pi,61):
    minorTick=box(axis=vector(clockR*np.cos(theta),clockR*np.sin(theta),0), color=color.black, length=minorTickL, width=minorTickW, height=minorTickT, pos=vector((clockR-minorTickL/2)*np.cos(theta),(clockR-minorTickL/2)*np.sin(theta),0))

clockFace=cylinder(axis=vector(0,0,1),color=vector(0,1,.8),length=clockT, radius=clockR,pos=vector(0,0,-clockT/2))
minuteHand=arrow(axis=vector(0,1,0),color=color.red,shaftwidth=minuteHandT,length=minuteHandL, pos=vector(0,0,minuteHandOffset))
hourHand=arrow(axis=vector(0,1,0),color=color.red,shaftwidth=hourHandT,length=hourHandL, pos=vector(0,0,hourHandOffset))
secondHand=arrow(axis=vector(0,1,0),color=color.red,shaftwidth=secondHandT,length=secondHandL, pos=vector(0,0,secondHandOffset))
hub=cylinder(axis=vector(0,0,1),color=color.red, radius=hubRadius, length= 2*clockT)
while True:
    rate(5000)
    hour=time.localtime(time.time())[3]
    if hour>12:
        hour=hour-12
    minute=time.localtime(time.time())[4]
    second=time.localtime(time.time())[5]
    hourAngle=-((hour+minute/60)/12)*2*np.pi+np.pi/2
    minuteAngle=-((minute+second/60)/60)*2*np.pi+np.pi/2
    secondAngle=-(second/60)*2*np.pi+np.pi/2
    print(second)
    hourHand.axis=vector(hourHandL*np.cos(hourAngle),hourHandL*np.sin(hourAngle),0)
    minuteHand.axis=vector(minuteHandL*np.cos(minuteAngle),minuteHandL*np.sin(minuteAngle),0)
    secondHand.axis=vector(secondHandL*np.cos(secondAngle),secondHandL*np.sin(secondAngle),0)

from vpython import *

import numpy as np

import time

clockR=1

clockT=clockR/10

majorTickL=clockR/7

majorTickT=2*np.pi*clockR/400

majorTickW=clockT*1.2

minorTickL=clockR/12

minorTickT=2*np.pi*clockR/600

minorTickW=clockT*1.2

minuteHandL=clockR-majorTickL

minuteHandT=minuteHandL/25

minuteHandOffset=clockT/2+minuteHandT

hourHandL=.75*minuteHandL

hourHandT=minuteHandT*1.25

hourHandOffset=clockT+hourHandT

secondHandL=clockR-majorTickL/2

secondHandT=minuteHandL/50

secondHandOffset=clockT*1.5+minuteHandT

hubRadius=clockT/2

hourAngle=np.pi/2

minuteAngle=np.pi/2

minInc=.0001

hourInc=minInc/12

secondAngle=np.pi/2

secondInc=minInc*60

for theta in np.linspace(0,2*np.pi,13):

majorTick=box(axis=vector(clockR*np.cos(theta),clockR*np.sin(theta),0), color=color.black, length=majorTickL, width=majorTickW, height=majorTickT, pos=vector((clockR-majorTickL/2)*np.cos(theta),(clockR-majorTickL/2)*np.sin(theta),0))

for theta in np.linspace(0,2*np.pi,61):

minorTick=box(axis=vector(clockR*np.cos(theta),clockR*np.sin(theta),0), color=color.black, length=minorTickL, width=minorTickW, height=minorTickT, pos=vector((clockR-minorTickL/2)*np.cos(theta),(clockR-minorTickL/2)*np.sin(theta),0))

clockFace=cylinder(axis=vector(0,0,1),color=vector(0,1,.8),length=clockT, radius=clockR,pos=vector(0,0,-clockT/2))

minuteHand=arrow(axis=vector(0,1,0),color=color.red,shaftwidth=minuteHandT,length=minuteHandL, pos=vector(0,0,minuteHandOffset))

hourHand=arrow(axis=vector(0,1,0),color=color.red,shaftwidth=hourHandT,length=hourHandL, pos=vector(0,0,hourHandOffset))

secondHand=arrow(axis=vector(0,1,0),color=color.red,shaftwidth=secondHandT,length=secondHandL, pos=vector(0,0,secondHandOffset))

hub=cylinder(axis=vector(0,0,1),color=color.red, radius=hubRadius, length= 2*clockT)

while True:

rate(5000)

hour=time.localtime(time.time())[3]

if hour>12:

hour=hour-12

minute=time.localtime(time.time())[4]

second=time.localtime(time.time())[5]

hourAngle=-((hour+minute/60)/12)*2*np.pi+np.pi/2

minuteAngle=-((minute+second/60)/60)*2*np.pi+np.pi/2

secondAngle=-(second/60)*2*np.pi+np.pi/2

print(second)

hourHand.axis=vector(hourHandL*np.cos(hourAngle),hourHandL*np.sin(hourAngle),0)

minuteHand.axis=vector(minuteHandL*np.cos(minuteAngle),minuteHandL*np.sin(minuteAngle),0)

secondHand.axis=vector(secondHandL*np.cos(secondAngle),secondHandL*np.sin(secondAngle),0)

OpenCV, Python

AI for Everyone LESSON 16: Face Recognition with OpenCV

October 19, 2021 admin

Guys in this lesson we learn how to not only detect faces in an image, but also recognize who the person is. We start by training our model with known faces, and then find and identify those faces in other pictures. For your convenience, I include the code developed in this lesson below.

import cv2
import face_recognition as FR
font=cv2.FONT_HERSHEY_SIMPLEX

donFace=FR.load_image_file('C:/Users/Valued Customer/Documents/Python/demoImages/known/Donald Trump.jpg')
faceLoc=FR.face_locations(donFace)[0]
donFaceEncode=FR.face_encodings(donFace)[0]


nancyFace=FR.load_image_file('C:/Users/Valued Customer/Documents/Python/demoImages/known/Nancy Pelosi.jpg')
faceLoc=FR.face_locations(nancyFace)[0]
nancyFaceEncode=FR.face_encodings(nancyFace)[0]

penceFace=FR.load_image_file('C:/Users/Valued Customer/Documents/Python/demoImages/known/Mike Pence.jpg')
faceLoc=FR.face_locations(penceFace)[0]
penceFaceEncode=FR.face_encodings(penceFace)[0]

knownEncodings=[donFaceEncode,nancyFaceEncode,penceFaceEncode]
names=['Donald Trump','Nancy Pelosi','Mike Pence']

unknownFace=FR.load_image_file('C:/Users/Valued Customer/Documents/Python/demoImages/unknown/u1.jpg')
unknownFaceBGR=cv2.cvtColor(unknownFace,cv2.COLOR_RGB2BGR)
faceLocations=FR.face_locations(unknownFace)
unknownEncodings=FR.face_encodings(unknownFace,faceLocations)

for faceLocation,unknownEncoding in zip(faceLocations,unknownEncodings):
    top,right,bottom,left=faceLocation
    print(faceLocation)
    cv2.rectangle(unknownFaceBGR,(left,top),(right,bottom),(255,0,0),3)
    name='Unknown Person'
    matches=FR.compare_faces(knownEncodings,unknownEncoding)
    print(matches)
    if True in matches:
        matchIndex=matches.index(True)
        print(matchIndex)
        print(names[matchIndex])
        name=names[matchIndex]
    cv2.putText(unknownFaceBGR,name,(left,top),font,.75,(0,0,255),2)

cv2.imshow('My Faces',unknownFaceBGR)

cv2.waitKey(10000)

import cv2

import face_recognition as FR

font=cv2.FONT_HERSHEY_SIMPLEX

donFace=FR.load_image_file('C:/Users/Valued Customer/Documents/Python/demoImages/known/Donald Trump.jpg')

faceLoc=FR.face_locations(donFace)[0]

donFaceEncode=FR.face_encodings(donFace)[0]

nancyFace=FR.load_image_file('C:/Users/Valued Customer/Documents/Python/demoImages/known/Nancy Pelosi.jpg')

faceLoc=FR.face_locations(nancyFace)[0]

nancyFaceEncode=FR.face_encodings(nancyFace)[0]

penceFace=FR.load_image_file('C:/Users/Valued Customer/Documents/Python/demoImages/known/Mike Pence.jpg')

faceLoc=FR.face_locations(penceFace)[0]

penceFaceEncode=FR.face_encodings(penceFace)[0]

knownEncodings=[donFaceEncode,nancyFaceEncode,penceFaceEncode]

names=['Donald Trump','Nancy Pelosi','Mike Pence']

unknownFace=FR.load_image_file('C:/Users/Valued Customer/Documents/Python/demoImages/unknown/u1.jpg')

unknownFaceBGR=cv2.cvtColor(unknownFace,cv2.COLOR_RGB2BGR)

faceLocations=FR.face_locations(unknownFace)

unknownEncodings=FR.face_encodings(unknownFace,faceLocations)

for faceLocation,unknownEncoding in zip(faceLocations,unknownEncodings):

top,right,bottom,left=faceLocation

print(faceLocation)

cv2.rectangle(unknownFaceBGR,(left,top),(right,bottom),(255,0,0),3)

name='Unknown Person'

matches=FR.compare_faces(knownEncodings,unknownEncoding)

print(matches)

if True in matches:

matchIndex=matches.index(True)

print(matchIndex)

print(names[matchIndex])

name=names[matchIndex]

cv2.putText(unknownFaceBGR,name,(left,top),font,.75,(0,0,255),2)

cv2.imshow('My Faces',unknownFaceBGR)

cv2.waitKey(10000)

OpenCV, Python

AI for Everyone LESSON 15: Face Detection using OpenCV

October 12, 2021 admin

In this video lesson we show a simple method to detect faces in a WEB cam frame using openCV and Haar Cascades. We use pretrained models to find, box and track faces in a frame. Enjoy!

import cv2
print(cv2.__version__)
width=640
height=360
cam=cv2.VideoCapture(0,cv2.CAP_DSHOW)
cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)
cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)
cam.set(cv2.CAP_PROP_FPS, 30)
cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))

faceCascade=cv2.CascadeClassifier('C:\Users\Valued Customer\Documents\Python\haar\haarcascade_frontalface_default.xml')

while True:
    ignore,  frame = cam.read()
    frameGray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
    faces=faceCascade.detectMultiScale(frameGray,1.3,5)
    for face in faces:
        x,y,w,h=face
        cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),3)
    cv2.imshow('my WEBcam', frame)
    cv2.moveWindow('my WEBcam',0,0)
    if cv2.waitKey(1) & 0xff ==ord('q'):
        break
cam.release()

import cv2

print(cv2.__version__)

width=640

height=360

cam=cv2.VideoCapture(0,cv2.CAP_DSHOW)

cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)

cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)

cam.set(cv2.CAP_PROP_FPS, 30)

cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))

faceCascade=cv2.CascadeClassifier('C:\Users\Valued Customer\Documents\Python\haar\haarcascade_frontalface_default.xml')

while True:

ignore, frame = cam.read()

frameGray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)

faces=faceCascade.detectMultiScale(frameGray,1.3,5)

for face in faces:

x,y,w,h=face

cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),3)

cv2.imshow('my WEBcam', frame)

cv2.moveWindow('my WEBcam',0,0)

if cv2.waitKey(1) & 0xff ==ord('q'):

break

cam.release()

Python

Tracking an Object Based on Color in OpenCV

September 28, 2021 admin

In this lesson I describe how to track an object in OpenCV based on color. We use the HSV color space to make it simpler to train the model. Below, for your convenience, we include the code we develop in this lesson.

import numpy as np
import cv2
print(cv2.__version__)

def onTrack1(val):
    global hueLow
    hueLow=val
    print('Hue Low',hueLow)
def onTrack2(val):
    global hueHigh
    hueHigh=val
    print('Hue High',hueHigh)
def onTrack3(val):
    global satLow
    satLow=val
    print('Sat Low',satLow)
def onTrack4(val):
    global satHigh
    satHigh=val
    print('Sat High',satHigh)
def onTrack5(val):
    global valLow
    valLow=val
    print('Val Low',valLow)
def onTrack6(val):
    global valHigh
    valHigh=val
    print('Val High',valHigh)

width=640
height=360
cam=cv2.VideoCapture(0,cv2.CAP_DSHOW)
cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)
cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)
cam.set(cv2.CAP_PROP_FPS, 30)
cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))

cv2.namedWindow('myTracker')
cv2.moveWindow('myTracker',width,0)

hueLow=10
hueHigh=20
satLow=10
satHigh=250
valLow=10
valHigh=250

cv2.createTrackbar('Hue Low','myTracker',10,179,onTrack1)
cv2.createTrackbar('Hue High','myTracker',20,179,onTrack2)
cv2.createTrackbar('Sat Low','myTracker',10,255,onTrack3)
cv2.createTrackbar('Sat High','myTracker',250,255,onTrack4)
cv2.createTrackbar('Val Low','myTracker',10,255,onTrack5)
cv2.createTrackbar('Val High','myTracker',250,255,onTrack6)

while True:
    ignore,  frame = cam.read()
    frameHSV=cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)
    lowerBound=np.array([hueLow,satLow,valLow])
    upperBound=np.array([hueHigh,satHigh,valHigh])
    myMask=cv2.inRange(frameHSV,lowerBound,upperBound)
    #myMask=cv2.bitwise_not(myMask)
    myObject=cv2.bitwise_and(frame,frame,mask=myMask)
    myObjectSmall=cv2.resize(myObject,(int(width/2),int(height/2)))
    cv2.imshow('My Object',myObjectSmall)
    cv2.moveWindow('My Object',int(width/2),int(height))
    myMaskSmall=cv2.resize(myMask,(int(width/2),int(height/2)))
    cv2.imshow('My Mask',myMaskSmall)
    cv2.moveWindow('My Mask',0,height)
    cv2.imshow('my WEBcam', frame)
    cv2.moveWindow('my WEBcam',0,0)
    if cv2.waitKey(1) & 0xff ==ord('q'):
        break
cam.release()

import numpy as np

import cv2

print(cv2.__version__)

def onTrack1(val):

global hueLow

hueLow=val

print('Hue Low',hueLow)

def onTrack2(val):

global hueHigh

hueHigh=val

print('Hue High',hueHigh)

def onTrack3(val):

global satLow

satLow=val

print('Sat Low',satLow)

def onTrack4(val):

global satHigh

satHigh=val

print('Sat High',satHigh)

def onTrack5(val):

global valLow

valLow=val

print('Val Low',valLow)

def onTrack6(val):

global valHigh

valHigh=val

print('Val High',valHigh)

width=640

height=360

cam=cv2.VideoCapture(0,cv2.CAP_DSHOW)

cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)

cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)

cam.set(cv2.CAP_PROP_FPS, 30)

cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))

cv2.namedWindow('myTracker')

cv2.moveWindow('myTracker',width,0)

hueLow=10

hueHigh=20

satLow=10

satHigh=250

valLow=10

valHigh=250

cv2.createTrackbar('Hue Low','myTracker',10,179,onTrack1)

cv2.createTrackbar('Hue High','myTracker',20,179,onTrack2)

cv2.createTrackbar('Sat Low','myTracker',10,255,onTrack3)

cv2.createTrackbar('Sat High','myTracker',250,255,onTrack4)

cv2.createTrackbar('Val Low','myTracker',10,255,onTrack5)

cv2.createTrackbar('Val High','myTracker',250,255,onTrack6)

while True:

ignore, frame = cam.read()

frameHSV=cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)

lowerBound=np.array([hueLow,satLow,valLow])

upperBound=np.array([hueHigh,satHigh,valHigh])

myMask=cv2.inRange(frameHSV,lowerBound,upperBound)

#myMask=cv2.bitwise_not(myMask)

myObject=cv2.bitwise_and(frame,frame,mask=myMask)

myObjectSmall=cv2.resize(myObject,(int(width/2),int(height/2)))

cv2.imshow('My Object',myObjectSmall)

cv2.moveWindow('My Object',int(width/2),int(height))

myMaskSmall=cv2.resize(myMask,(int(width/2),int(height/2)))

cv2.imshow('My Mask',myMaskSmall)

cv2.moveWindow('My Mask',0,height)

cv2.imshow('my WEBcam', frame)

cv2.moveWindow('my WEBcam',0,0)

if cv2.waitKey(1) & 0xff ==ord('q'):

break

cam.release()

OpenCV, Python, Tutorial

Putting Text, Rectangles and Circles on Images in OpenCV for Windows

August 24, 2021 admin

In the video lesson above we show how to add text, rectangles and circles to video frames using OpenCV. Below we include the code with we developed in this lesson. Enjoy!

import cv2
print(cv2.__version__)
width=640
height=360
myRadius=30
myColor=(0,0,0)
myThick=2
fontH=2
fontT=2
myText='Paul is Boss'
myFont=cv2.FONT_HERSHEY_DUPLEX
upperLeft=(250,140)
lowerRight=(390,220)
lineW=4
cam=cv2.VideoCapture(1,cv2.CAP_DSHOW)
cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)
cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)
cam.set(cv2.CAP_PROP_FPS, 30)
cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))
while True:
    ignore,  frame = cam.read()
    frame[140:220,250:390]=(255,0,0)
    cv2.rectangle(frame,upperLeft,lowerRight,(0,255,0),lineW)
    cv2.circle(frame,(int(width/2),int(height/2)),myRadius,myColor,myThick)
    cv2.putText(frame,myText,(120,60),myFont,fontH,(0,0,255),fontT)
    cv2.imshow('my WEBcam', frame)
    cv2.moveWindow('my WEBcam',0,0)
    if cv2.waitKey(1) & 0xff ==ord('q'):
        break
cam.release()

import cv2

print(cv2.__version__)

width=640

height=360

myRadius=30

myColor=(0,0,0)

myThick=2

fontH=2

fontT=2

myText='Paul is Boss'

myFont=cv2.FONT_HERSHEY_DUPLEX

upperLeft=(250,140)

lowerRight=(390,220)

lineW=4

cam=cv2.VideoCapture(1,cv2.CAP_DSHOW)

cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)

cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)

cam.set(cv2.CAP_PROP_FPS, 30)

cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))

while True:

ignore, frame = cam.read()

frame[140:220,250:390]=(255,0,0)

cv2.rectangle(frame,upperLeft,lowerRight,(0,255,0),lineW)

cv2.circle(frame,(int(width/2),int(height/2)),myRadius,myColor,myThick)

cv2.putText(frame,myText,(120,60),myFont,fontH,(0,0,255),fontT)

cv2.imshow('my WEBcam', frame)

cv2.moveWindow('my WEBcam',0,0)

if cv2.waitKey(1) & 0xff ==ord('q'):

break

cam.release()

Technology Tutorials

Tag Archives: Python

Python 3D Graphics Tutorial 18: 3D Clock Model with Proper Hand Motion

AI for Everyone LESSON 16: Face Recognition with OpenCV

AI for Everyone LESSON 15: Face Detection using OpenCV

Tracking an Object Based on Color in OpenCV

Putting Text, Rectangles and Circles on Images in OpenCV for Windows

Making The World a Better Place One High Tech Project at a Time. Enjoy!