All posts by admin

In this video lesson we show how two Raspberry Pi cameras can independently track to different objects of interest. As a demonstration, we track on two different colors, with pan/tilt servo systems adjusting to keep the object of interest in the center of the field of view.

In this project we are using the Jetson Xavier NX, which you can pick up HERE. You will also need to of the bracket/servo kits, which you can get HERE, and then two Raspberry Pi Version two cameras, available HERE.

import cv2
import numpy as np
import time
from adafruit_servokit import ServoKit
print(cv2.__version__)
timeMark=time.time()
dtFIL=0

def nothing(x):
    pass

cv2.namedWindow('TrackBars')
cv2.moveWindow('TrackBars',1320,0)
cv2.createTrackbar('hueLower', 'TrackBars',100,179,nothing)
cv2.createTrackbar('hueUpper', 'TrackBars',116,179,nothing)
cv2.createTrackbar('satLow', 'TrackBars',160,255,nothing)
cv2.createTrackbar('satHigh', 'TrackBars',255,255,nothing)
cv2.createTrackbar('valLow', 'TrackBars',150,255,nothing)
cv2.createTrackbar('valHigh', 'TrackBars',255,255,nothing)

cv2.namedWindow('TrackBars2')
cv2.moveWindow('TrackBars2',1100,0)
cv2.createTrackbar('hueLower2', 'TrackBars2',150,179,nothing)
cv2.createTrackbar('hueUpper2', 'TrackBars2',170,179,nothing)
cv2.createTrackbar('satLow2', 'TrackBars2',160,255,nothing)
cv2.createTrackbar('satHigh2', 'TrackBars2',255,255,nothing)
cv2.createTrackbar('valLow2', 'TrackBars2',150,255,nothing)
cv2.createTrackbar('valHigh2', 'TrackBars2',255,255,nothing)


kit=ServoKit(channels=16)

tilt1=90
pan1=90
tilt2=90
pan2=90

kit.servo[0].angle=pan1
kit.servo[1].angle=tilt1
kit.servo[2].angle=pan2
kit.servo[3].angle=tilt2

width=720
height=480
flip=2
font=cv2.FONT_HERSHEY_SIMPLEX
camSet1='nvarguscamerasrc sensor-id=0 ee-mode=1 ee-strength=0 tnr-mode=2 tnr-strength=1 wbmode=3 ! video/x-raw(memory:NVMM), width=3264, height=2464, framerate=21/1,format=NV12 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(width)+', height='+str(height)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! videobalance contrast=1.3 brightness=-.2 saturation=1.2 ! appsink drop=True'
camSet2='nvarguscamerasrc sensor-id=1 ee-mode=1 ee-strength=0 tnr-mode=2 tnr-strength=1 wbmode=3 ! video/x-raw(memory:NVMM), width=3264, height=2464, framerate=21/1,format=NV12 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(width)+', height='+str(height)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! videobalance contrast=1.3 brightness=-.2 saturation=1.2 ! appsink drop=True'

#camSet='nvarguscamerasrc sensor-id=0 ! video/x-raw(memory:NVMM), width=3264, height=2464, framerate=21/1,format=NV12 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(width)+', height='+str(height)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! appsink'
#camSet ='v4l2src device=/dev/video1 ! video/x-raw,width='+str(width)+',height='+str(height)+',framerate=20/1 ! videoconvert ! appsink'
cam1=cv2.VideoCapture(camSet1)
cam2=cv2.VideoCapture(camSet2)
while True:
    _, frame1 = cam1.read()
    _, frame2 = cam2.read()

    hsv1=cv2.cvtColor(frame1,cv2.COLOR_BGR2HSV)
    hsv2=cv2.cvtColor(frame2,cv2.COLOR_BGR2HSV)

    hueLow=cv2.getTrackbarPos('hueLower', 'TrackBars')
    hueUp=cv2.getTrackbarPos('hueUpper', 'TrackBars')

    Ls=cv2.getTrackbarPos('satLow', 'TrackBars')
    Us=cv2.getTrackbarPos('satHigh', 'TrackBars')

    Lv=cv2.getTrackbarPos('valLow', 'TrackBars')
    Uv=cv2.getTrackbarPos('valHigh', 'TrackBars')

    l_b=np.array([hueLow,Ls,Lv])
    u_b=np.array([hueUp,Us,Uv])


    hueLow2=cv2.getTrackbarPos('hueLower2', 'TrackBars2')
    hueUp2=cv2.getTrackbarPos('hueUpper2', 'TrackBars2')

    Ls2=cv2.getTrackbarPos('satLow2', 'TrackBars2')
    Us2=cv2.getTrackbarPos('satHigh2', 'TrackBars2')

    Lv2=cv2.getTrackbarPos('valLow2', 'TrackBars2')
    Uv2=cv2.getTrackbarPos('valHigh2', 'TrackBars2')

    l_b2=np.array([hueLow2,Ls2,Lv2])
    u_b2=np.array([hueUp2,Us2,Uv2])

    FGmask1=cv2.inRange(hsv1,l_b,u_b)
    FGmask2=cv2.inRange(hsv2,l_b2,u_b2)

    cv2.imshow('FGmask1',FGmask1)
    cv2.moveWindow('FGmask1',0,0)

    cv2.imshow('FGmask2',FGmask2)
    cv2.moveWindow('FGmask2',350,0)

    contours1,_ = cv2.findContours(FGmask1,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
    contours1=sorted(contours1,key=lambda x:cv2.contourArea(x),reverse=True)
    for cnt in contours1:
        area=cv2.contourArea(cnt)
        (x,y,w,h)=cv2.boundingRect(cnt)
        if area>=100:
            cv2.rectangle(frame1,(x,y),(x+w,y+h),(0,255,255),3)
            objX=x+w/2
            objY=y+h/2
            errorPan1=objX-width/2
            errorTilt1=objY-height/2
            if abs(errorPan1)>15:
                pan1=pan1+errorPan1/40
            if abs(errorTilt1)>15:
                tilt1=tilt1-errorTilt1/40
            if pan1>180:
                pan1=180
                print('Pan Out of Range')
            if pan1<0:
                pan1=0
                print('Pan Out of Range')
            if tilt1>180:
                tilt1=180
                print('Tilt Out of Range')
            if tilt1<0:
                tilt1=0
            kit.servo[2].angle=pan1
            kit.servo[3].angle=tilt1
            break
    
    contours2,_ = cv2.findContours(FGmask2,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
    contours2=sorted(contours2,key=lambda x:cv2.contourArea(x),reverse=True)
    for cnt in contours2:
        area=cv2.contourArea(cnt)
        (x,y,w,h)=cv2.boundingRect(cnt)
        if area>=100:
            cv2.rectangle(frame2,(x,y),(x+w,y+h),(0,255,255),3)
            objX=x+w/2
            objY=y+h/2
            errorPan2=objX-width/2
            errorTilt2=objY-height/2
            if abs(errorPan2)>15:
                pan2=pan2+errorPan2/40
            if abs(errorTilt2)>15:
                tilt2=tilt2-errorTilt2/40
            if pan2>180:
                pan2=180
                print('Pan Out of Range')
            if pan2<0:
                pan2=0
                print('Pan Out of Range')
            if tilt2>180:
                tilt2=180
                print('Tilt Out of Range')
            if tilt2<0:
                tilt2=0
            kit.servo[0].angle=pan2
            kit.servo[1].angle=tilt2            
            break

    frame3=np.hstack((frame1,frame2))
    dt=time.time()-timeMark
    timeMark=time.time()
    dtFIL=.9*dtFIL + .1*dt
    fps=1/dtFIL
    cv2.rectangle(frame3,(0,0),(150,40),(0,0,255),-1)
    cv2.putText(frame3,'fps: '+str(round(fps,1)),(0,30),font,1,(0,255,255),2)

    #cv2.imshow('myCam1',frame1)
    #cv2.imshow('myCam2',frame2)
    cv2.imshow('comboCam',frame3)
    cv2.moveWindow('comboCam',0,450)

    if cv2.waitKey(1)==ord('q'):
        break
cam1.release()
cam2.release()
cv2.destroyAllWindows()

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import cv2

import numpy as np

import time

from adafruit_servokit import ServoKit

print(cv2.__version__)

timeMark=time.time()

dtFIL=0

def nothing(x):

pass

cv2.namedWindow('TrackBars')

cv2.moveWindow('TrackBars',1320,0)

cv2.createTrackbar('hueLower', 'TrackBars',100,179,nothing)

cv2.createTrackbar('hueUpper', 'TrackBars',116,179,nothing)

cv2.createTrackbar('satLow', 'TrackBars',160,255,nothing)

cv2.createTrackbar('satHigh', 'TrackBars',255,255,nothing)

cv2.createTrackbar('valLow', 'TrackBars',150,255,nothing)

cv2.createTrackbar('valHigh', 'TrackBars',255,255,nothing)

cv2.namedWindow('TrackBars2')

cv2.moveWindow('TrackBars2',1100,0)

cv2.createTrackbar('hueLower2', 'TrackBars2',150,179,nothing)

cv2.createTrackbar('hueUpper2', 'TrackBars2',170,179,nothing)

cv2.createTrackbar('satLow2', 'TrackBars2',160,255,nothing)

cv2.createTrackbar('satHigh2', 'TrackBars2',255,255,nothing)

cv2.createTrackbar('valLow2', 'TrackBars2',150,255,nothing)

cv2.createTrackbar('valHigh2', 'TrackBars2',255,255,nothing)

kit=ServoKit(channels=16)

tilt1=90

pan1=90

tilt2=90

pan2=90

kit.servo[0].angle=pan1

kit.servo[1].angle=tilt1

kit.servo[2].angle=pan2

kit.servo[3].angle=tilt2

width=720

height=480

flip=2

font=cv2.FONT_HERSHEY_SIMPLEX

camSet1='nvarguscamerasrc sensor-id=0 ee-mode=1 ee-strength=0 tnr-mode=2 tnr-strength=1 wbmode=3 ! video/x-raw(memory:NVMM), width=3264, height=2464, framerate=21/1,format=NV12 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(width)+', height='+str(height)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! videobalance contrast=1.3 brightness=-.2 saturation=1.2 ! appsink drop=True'

camSet2='nvarguscamerasrc sensor-id=1 ee-mode=1 ee-strength=0 tnr-mode=2 tnr-strength=1 wbmode=3 ! video/x-raw(memory:NVMM), width=3264, height=2464, framerate=21/1,format=NV12 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(width)+', height='+str(height)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! videobalance contrast=1.3 brightness=-.2 saturation=1.2 ! appsink drop=True'

#camSet='nvarguscamerasrc sensor-id=0 ! video/x-raw(memory:NVMM), width=3264, height=2464, framerate=21/1,format=NV12 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(width)+', height='+str(height)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! appsink'

#camSet ='v4l2src device=/dev/video1 ! video/x-raw,width='+str(width)+',height='+str(height)+',framerate=20/1 ! videoconvert ! appsink'

cam1=cv2.VideoCapture(camSet1)

cam2=cv2.VideoCapture(camSet2)

while True:

_, frame1 = cam1.read()

_, frame2 = cam2.read()

hsv1=cv2.cvtColor(frame1,cv2.COLOR_BGR2HSV)

hsv2=cv2.cvtColor(frame2,cv2.COLOR_BGR2HSV)

hueLow=cv2.getTrackbarPos('hueLower', 'TrackBars')

hueUp=cv2.getTrackbarPos('hueUpper', 'TrackBars')

Ls=cv2.getTrackbarPos('satLow', 'TrackBars')

Us=cv2.getTrackbarPos('satHigh', 'TrackBars')

Lv=cv2.getTrackbarPos('valLow', 'TrackBars')

Uv=cv2.getTrackbarPos('valHigh', 'TrackBars')

l_b=np.array([hueLow,Ls,Lv])

u_b=np.array([hueUp,Us,Uv])

hueLow2=cv2.getTrackbarPos('hueLower2', 'TrackBars2')

hueUp2=cv2.getTrackbarPos('hueUpper2', 'TrackBars2')

Ls2=cv2.getTrackbarPos('satLow2', 'TrackBars2')

Us2=cv2.getTrackbarPos('satHigh2', 'TrackBars2')

Lv2=cv2.getTrackbarPos('valLow2', 'TrackBars2')

Uv2=cv2.getTrackbarPos('valHigh2', 'TrackBars2')

l_b2=np.array([hueLow2,Ls2,Lv2])

u_b2=np.array([hueUp2,Us2,Uv2])

FGmask1=cv2.inRange(hsv1,l_b,u_b)

FGmask2=cv2.inRange(hsv2,l_b2,u_b2)

cv2.imshow('FGmask1',FGmask1)

cv2.moveWindow('FGmask1',0,0)

cv2.imshow('FGmask2',FGmask2)

cv2.moveWindow('FGmask2',350,0)

contours1,_ = cv2.findContours(FGmask1,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)

contours1=sorted(contours1,key=lambda x:cv2.contourArea(x),reverse=True)

for cnt in contours1:

area=cv2.contourArea(cnt)

(x,y,w,h)=cv2.boundingRect(cnt)

if area>=100:

cv2.rectangle(frame1,(x,y),(x+w,y+h),(0,255,255),3)

objX=x+w/2

objY=y+h/2

errorPan1=objX-width/2

errorTilt1=objY-height/2

if abs(errorPan1)>15:

pan1=pan1+errorPan1/40

if abs(errorTilt1)>15:

tilt1=tilt1-errorTilt1/40

if pan1>180:

pan1=180

print('Pan Out of Range')

if pan1<0:

pan1=0

print('Pan Out of Range')

if tilt1>180:

tilt1=180

print('Tilt Out of Range')

if tilt1<0:

tilt1=0

kit.servo[2].angle=pan1

kit.servo[3].angle=tilt1

break

contours2,_ = cv2.findContours(FGmask2,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)

contours2=sorted(contours2,key=lambda x:cv2.contourArea(x),reverse=True)

for cnt in contours2:

area=cv2.contourArea(cnt)

(x,y,w,h)=cv2.boundingRect(cnt)

if area>=100:

cv2.rectangle(frame2,(x,y),(x+w,y+h),(0,255,255),3)

objX=x+w/2

objY=y+h/2

errorPan2=objX-width/2

errorTilt2=objY-height/2

if abs(errorPan2)>15:

pan2=pan2+errorPan2/40

if abs(errorTilt2)>15:

tilt2=tilt2-errorTilt2/40

if pan2>180:

pan2=180

print('Pan Out of Range')

if pan2<0:

pan2=0

print('Pan Out of Range')

if tilt2>180:

tilt2=180

print('Tilt Out of Range')

if tilt2<0:

tilt2=0

kit.servo[0].angle=pan2

kit.servo[1].angle=tilt2

break

frame3=np.hstack((frame1,frame2))

dt=time.time()-timeMark

timeMark=time.time()

dtFIL=.9*dtFIL + .1*dt

fps=1/dtFIL

cv2.rectangle(frame3,(0,0),(150,40),(0,0,255),-1)

cv2.putText(frame3,'fps: '+str(round(fps,1)),(0,30),font,1,(0,255,255),2)

#cv2.imshow('myCam1',frame1)

#cv2.imshow('myCam2',frame2)

cv2.imshow('comboCam',frame3)

cv2.moveWindow('comboCam',0,450)

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

break

cam1.release()

cam2.release()

cv2.destroyAllWindows()

Live Streaming Studio

Low Cost High Quality Studio for Online and Distance Learning or Electronic School Using OBS

July 28, 2020 admin

In this video lesson we show you how to create a high quality, easy to use, low cost studio for streaming from a classroom. We show how to install a powerful, free piece of software that will do everything you need. We show how to set up the software and how to use it for a number of different simple shots.

The minimum you will need is a simple WEB cam. The one we recommend is the Logitech High Definition, available HERE.

Next up, you will need some form of greenscreen. You can paint a wall behind you green, you can put green butcher paper behind you, or just about anything that will put a solid green background behind you. A convenient method if the budget allows is an actual green screen, available HERE.

Now, to take your production quality to the next level, the best thing you can do is get a quality microphone. I really like the Yeti, and that is what I use. You can get yours HERE.

This gear will give you what you need to do really nice live streams. If the budget allows the final thing that is really nice is a good set of studio lights, which you can gere HERE.

Jetson Nano

AI on the Jetson Nano LESSON 52: Improving Picture Quality of the Raspberry Pi Camera with Gstreamer

July 25, 2020 admin

In this lesson we want to pause and work on improving the image quality of the video stream coming from the Raspberry Pi camera. Right now, we are using a boilerplate Gstreamer string to launch the Raspberry Pi camera. In the video above we show how image quality can be drastically improved by tweaking the Gstreamer launch string.

Based on the Video above, we develop a greatly improved image quality by adjusting the Gstreamer launch string. Below, for you enjoyment is the code that will optimize picture quality.

First, this is the key line that results in excellent video quality:

# Gstreamer code for improvded Raspberry Pi Camera Quality
camSet='nvarguscamerasrc wbmode=3 tnr-mode=2 tnr-strength=1 ee-mode=2 ee-strength=1 ! video/x-raw(memory:NVMM), width=3264, height=2464, format=NV12, framerate=21/1 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(dispW)+', height='+str(dispH)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! videobalance contrast=1.5 brightness=-.2 saturation=1.2 ! appsink'

# Gstreamer code for improvded Raspberry Pi Camera Quality

camSet='nvarguscamerasrc wbmode=3 tnr-mode=2 tnr-strength=1 ee-mode=2 ee-strength=1 ! video/x-raw(memory:NVMM), width=3264, height=2464, format=NV12, framerate=21/1 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(dispW)+', height='+str(dispH)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! videobalance contrast=1.5 brightness=-.2 saturation=1.2 ! appsink'

And here is the overall code for running and displaying from the camera with the enhanced quality:

import cv2
print(cv2.__version__)
dispW=1280
dispH=720
flip=2
#Uncomment These next Two Line for Pi Camera
camSet='nvarguscamerasrc wbmode=3 tnr-mode=2 tnr-strength=1 ee-mode=2 ee-strength=1 !  video/x-raw(memory:NVMM), width=3264, height=2464, format=NV12, framerate=21/1 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(dispW)+', height='+str(dispH)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! videobalance contrast=1.5 brightness=-.2 saturation=1.2 !  appsink'
cam= cv2.VideoCapture(camSet)

#Or, if you have a WEB cam, uncomment the next line
#cam=cv2.VideoCapture('/dev/video1')
while True:
    ret, frame = cam.read()
    cv2.imshow('nanoCam',frame)
    cv2.moveWindow('nanoCam',0,0)
    if cv2.waitKey(1)==ord('q'):
        break
cam.release()
cv2.destroyAllWindows()

import cv2

print(cv2.__version__)

dispW=1280

dispH=720

flip=2

#Uncomment These next Two Line for Pi Camera

cam= cv2.VideoCapture(camSet)

#Or, if you have a WEB cam, uncomment the next line

#cam=cv2.VideoCapture('/dev/video1')

while True:

ret, frame = cam.read()

cv2.imshow('nanoCam',frame)

cv2.moveWindow('nanoCam',0,0)

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

break

cam.release()

cv2.destroyAllWindows()

Now, once we have optimized the Gstreamer launch stream, we need to consider what path to move forward. In lesson #50 we saw that we could either control the camera using the NVIDIA Jetson Utilities, or we could control the camera normally from OpenCV. The advantage of our old OpenCV method is that it gives us more control of the camera. The advantage of the Jetson Utility method is that it appears to run faster, and for the rPi camera, have less latency. Below are two code examples for the two methods above. In the video lesson above, we will figure out the best strategy by tweaking the parameters in these two programas.

OPTION #1: Launch the cameras using OpenCV

import jetson.inference
import jetson.utils
import cv2
import numpy as np
import time
width=1280
height=720
dispW=width
dispH=height
flip=2
camSet='nvarguscamerasrc !  video/x-raw(memory:NVMM), width=3264, height=2464, format=NV12, framerate=21/1 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(dispW)+', height='+str(dispH)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! videobalance  contrast=1.5 brightness=-.3 saturation=1.2 ! appsink  '
cam1=cv2.VideoCapture(camSet)
#cam1=cv2.VideoCapture('/dev/video1')
#cam1.set(cv2.CAP_PROP_FRAME_WIDTH,dispW)
#cam1.set(cv2.CAP_PROP_FRAME_HEIGHT,dispH)
net=jetson.inference.imageNet('alexnet')
font=cv2.FONT_HERSHEY_SIMPLEX
timeMark=time.time()
fpsFilter=0
while True:
    _,frame=cam1.read()
    img=cv2.cvtColor(frame,cv2.COLOR_BGR2RGBA).astype(np.float32)
    img=jetson.utils.cudaFromNumpy(img)
    classID, confidence =net.Classify(img, width, height)
    item=''
    item =net.GetClassDesc(classID)
    dt=time.time()-timeMark
    fps=1/dt
    fpsFilter=.95*fpsFilter +.05*fps
    timeMark=time.time()
    cv2.putText(frame,str(round(fpsFilter,1))+' fps '+item,(0,30),font,1,(0,0,255),2)
    cv2.imshow('recCam',frame)
    cv2.moveWindow('recCam',0,0)
    if cv2.waitKey(1)==ord('q'):
        break
cam.releast()
cv2.destroyAllWindows()

import jetson.inference

import jetson.utils

import cv2

import numpy as np

import time

width=1280

height=720

dispW=width

dispH=height

flip=2

camSet='nvarguscamerasrc ! video/x-raw(memory:NVMM), width=3264, height=2464, format=NV12, framerate=21/1 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(dispW)+', height='+str(dispH)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! videobalance contrast=1.5 brightness=-.3 saturation=1.2 ! appsink '

cam1=cv2.VideoCapture(camSet)

#cam1=cv2.VideoCapture('/dev/video1')

#cam1.set(cv2.CAP_PROP_FRAME_WIDTH,dispW)

#cam1.set(cv2.CAP_PROP_FRAME_HEIGHT,dispH)

net=jetson.inference.imageNet('alexnet')

font=cv2.FONT_HERSHEY_SIMPLEX

timeMark=time.time()

fpsFilter=0

while True:

_,frame=cam1.read()

img=cv2.cvtColor(frame,cv2.COLOR_BGR2RGBA).astype(np.float32)

img=jetson.utils.cudaFromNumpy(img)

classID, confidence =net.Classify(img, width, height)

item=''

item =net.GetClassDesc(classID)

dt=time.time()-timeMark

fps=1/dt

fpsFilter=.95*fpsFilter +.05*fps

timeMark=time.time()

cv2.putText(frame,str(round(fpsFilter,1))+' fps '+item,(0,30),font,1,(0,0,255),2)

cv2.imshow('recCam',frame)

cv2.moveWindow('recCam',0,0)

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

break

cam.releast()

cv2.destroyAllWindows()

OPTION # 2: Control Camera with NVIDIA Jetson Utilities Library

import jetson.inference
import jetson.utils
import time
import cv2
import numpy as np
width=1280
height=720
#cam=jetson.utils.gstCamera(width,height,'/dev/video1')
cam=jetson.utils.gstCamera(width,height,'0')
net=jetson.inference.imageNet('googlenet')
timeMark=time.time()
fpsFilter=0
timeMark=time.time()
font=cv2.FONT_HERSHEY_SIMPLEX
while True:
    frame, width, height = cam.CaptureRGBA(zeroCopy=1)
    classID, confidence = net.Classify(frame, width, height)
    item = net.GetClassDesc(classID)
    dt=time.time()-timeMark
    fps=1/dt
    fpsFilter=.95*fpsFilter+.05*fps
    timeMark=time.time()
    frame=jetson.utils.cudaToNumpy(frame,width,height,4)
    frame=cv2.cvtColor(frame, cv2.COLOR_RGBA2BGR).astype(np.uint8)
    cv2.putText(frame,str(round(fpsFilter,1))+'      '+item,(0,30),font,1,(0,0,255),2)
    cv2.imshow('webCam',frame)
    cv2.moveWindow('webCam',0,0)
    if cv2.waitKey(1)==ord('q'):
        break
cam.release()
cv2.destroyAllWindows()

import jetson.inference

import jetson.utils

import time

import cv2

import numpy as np

width=1280

height=720

#cam=jetson.utils.gstCamera(width,height,'/dev/video1')

cam=jetson.utils.gstCamera(width,height,'0')

net=jetson.inference.imageNet('googlenet')

timeMark=time.time()

fpsFilter=0

timeMark=time.time()

font=cv2.FONT_HERSHEY_SIMPLEX

while True:

frame, width, height = cam.CaptureRGBA(zeroCopy=1)

classID, confidence = net.Classify(frame, width, height)

item = net.GetClassDesc(classID)

dt=time.time()-timeMark

fps=1/dt

fpsFilter=.95*fpsFilter+.05*fps

timeMark=time.time()

frame=jetson.utils.cudaToNumpy(frame,width,height,4)

frame=cv2.cvtColor(frame, cv2.COLOR_RGBA2BGR).astype(np.uint8)

cv2.putText(frame,str(round(fpsFilter,1))+' '+item,(0,30),font,1,(0,0,255),2)

cv2.imshow('webCam',frame)

cv2.moveWindow('webCam',0,0)

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

break

cam.release()

cv2.destroyAllWindows()

Elegoo Smart Car Tutorial

Robotics Training LESSON 7: Calibrating the Smart Car for Distance and Speed

July 23, 2020 admin

In this lesson we show how to program the Elegoo Smart car to operate with user defined speed and distance. This allows programming by simply stacking simple pre-defined functions. If you want to play along at home, you can get the hardware I am using in this series HERE.

int ENA=5;
int ENB=6;
int IN1=7;
int IN2=8;
int IN3=9;
int IN4=11;
float d;
int degRot;
int left;
int right;
int wv;
void setup() {
  // put your setup code here, to run once:
Serial.begin(9600);
pinMode(ENA,OUTPUT);
pinMode(ENB,OUTPUT);
pinMode(IN1,OUTPUT);
pinMode(IN2,OUTPUT);
pinMode(IN3,OUTPUT);
pinMode(IN4,OUTPUT);
digitalWrite(ENA,HIGH);
digitalWrite(ENB,HIGH);
}

void loop() {
wv=255;
left=wv;
right=wv;
setSpeed(left,right);
forward(4,wv);
  while(1==1){

  }
}
void setSpeed(int leftVal,int rightVal){
  analogWrite(ENA,leftVal);
  analogWrite(ENB,rightVal);
}
void forward(float d, float wv){
float t;
float v;
digitalWrite(IN1,HIGH);
digitalWrite(IN2,LOW);
digitalWrite(IN3,LOW);
digitalWrite(IN4,HIGH);
v=.0075*wv+.35;
t=d/v*1000;
delay(t);
stopCar();
}
void backward(float d, float wv){
float t;
float v;
digitalWrite(IN1,LOW);
digitalWrite(IN2,HIGH);
digitalWrite(IN3,HIGH);
digitalWrite(IN4,LOW);
v=.0075*wv+.35;
t=d/v*1000;
delay(t);
stopCar();
}
void turnRight(int deg){
  float t;
digitalWrite(IN1,HIGH);
digitalWrite(IN2,LOW);
digitalWrite(IN3,HIGH);
digitalWrite(IN4,LOW);
t=deg/345.*1000.;
Serial.println(deg);
delay(t);
stopCar();
}
void turnLeft(float deg){
  float t;
digitalWrite(IN1,LOW);
digitalWrite(IN2,HIGH);
digitalWrite(IN3,LOW);
digitalWrite(IN4,HIGH);
t=deg/345.*1000.;
Serial.println(deg);
delay(t);
stopCar();
}
void stopCar(){
digitalWrite(IN1,LOW);
digitalWrite(IN2,LOW);
digitalWrite(IN3,LOW);
digitalWrite(IN4,LOW);
}

void calF(){
digitalWrite(IN1,HIGH);
digitalWrite(IN2,LOW);
digitalWrite(IN3,LOW);
digitalWrite(IN4,HIGH);
delay(5000);
stopCar();
}
void calB(){
digitalWrite(IN1,LOW);
digitalWrite(IN2,HIGH);
digitalWrite(IN3,HIGH);
digitalWrite(IN4,LOW);
delay(5000);
stopCar();
}
void calR(){
digitalWrite(IN1,HIGH);
digitalWrite(IN2,LOW);
digitalWrite(IN3,HIGH);
digitalWrite(IN4,LOW);
delay(5000);
stopCar();
}
void calL(){
digitalWrite(IN1,LOW);
digitalWrite(IN2,HIGH);
digitalWrite(IN3,LOW);
digitalWrite(IN4,HIGH);
delay(5000);
stopCar();
}

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int ENA=5;

int ENB=6;

int IN1=7;

int IN2=8;

int IN3=9;

int IN4=11;

float d;

int degRot;

int left;

int right;

int wv;

void setup() {

// put your setup code here, to run once:

Serial.begin(9600);

pinMode(ENA,OUTPUT);

pinMode(ENB,OUTPUT);

pinMode(IN1,OUTPUT);

pinMode(IN2,OUTPUT);

pinMode(IN3,OUTPUT);

pinMode(IN4,OUTPUT);

digitalWrite(ENA,HIGH);

digitalWrite(ENB,HIGH);

}

void loop() {

wv=255;

left=wv;

right=wv;

setSpeed(left,right);

forward(4,wv);

while(1==1){

}

void setSpeed(int leftVal,int rightVal){

analogWrite(ENA,leftVal);

analogWrite(ENB,rightVal);

}

void forward(float d, float wv){

float t;

float v;

digitalWrite(IN1,HIGH);

digitalWrite(IN2,LOW);

digitalWrite(IN3,LOW);

digitalWrite(IN4,HIGH);

v=.0075*wv+.35;

t=d/v*1000;

delay(t);

stopCar();

}

void backward(float d, float wv){

float t;

float v;

digitalWrite(IN1,LOW);

digitalWrite(IN2,HIGH);

digitalWrite(IN3,HIGH);

digitalWrite(IN4,LOW);

v=.0075*wv+.35;

t=d/v*1000;

delay(t);

stopCar();

}

void turnRight(int deg){

float t;

digitalWrite(IN1,HIGH);

digitalWrite(IN2,LOW);

digitalWrite(IN3,HIGH);

digitalWrite(IN4,LOW);

t=deg/345.*1000.;

Serial.println(deg);

delay(t);

stopCar();

}

void turnLeft(float deg){

float t;

digitalWrite(IN1,LOW);

digitalWrite(IN2,HIGH);

digitalWrite(IN3,LOW);

digitalWrite(IN4,HIGH);

t=deg/345.*1000.;

Serial.println(deg);

delay(t);

stopCar();

}

void stopCar(){

digitalWrite(IN1,LOW);

digitalWrite(IN2,LOW);

digitalWrite(IN3,LOW);

digitalWrite(IN4,LOW);

}

void calF(){

digitalWrite(IN1,HIGH);

digitalWrite(IN2,LOW);

digitalWrite(IN3,LOW);

digitalWrite(IN4,HIGH);

delay(5000);

stopCar();

}

void calB(){

digitalWrite(IN1,LOW);

digitalWrite(IN2,HIGH);

digitalWrite(IN3,HIGH);

digitalWrite(IN4,LOW);

delay(5000);

stopCar();

}

void calR(){

digitalWrite(IN1,HIGH);

digitalWrite(IN2,LOW);

digitalWrite(IN3,HIGH);

digitalWrite(IN4,LOW);

delay(5000);

stopCar();

}

void calL(){

digitalWrite(IN1,LOW);

digitalWrite(IN2,HIGH);

digitalWrite(IN3,LOW);

digitalWrite(IN4,HIGH);

delay(5000);

stopCar();

}

Jetson Xavier NX

Jetson Xavier NX Lesson 10: Tracking Multiple Objects of Interest with Servos in OpenCV

July 22, 2020 admin

<span data-mce-type="bookmark" style="display: inline-block; width: 0px; overflow: hidden; line-height: 0;" class="mce_SELRES_start"></span>
In this lesson we learn how to use OpenCV on the Jetson Xavier NX to track an object of interest in with two cameras on two Pan/Tilt servo brackets. The system tracks based on HSV color space, but the same basic setup could be used with other object detection algorithms. In this project we are using the Jetson Xavier NX, which you can pick up HERE. You will also need to of the bracket/servo kits, which you can get HERE, and then two Raspberry Pi Version two cameras, available HERE.

import cv2
import numpy as np
import time
from adafruit_servokit import ServoKit
print(cv2.__version__)
timeMark=time.time()
dtFIL=0

def nothing(x):
    pass

cv2.namedWindow('TrackBars')
cv2.moveWindow('TrackBars',1320,0)
cv2.createTrackbar('hueLower', 'TrackBars',100,179,nothing)
cv2.createTrackbar('hueUpper', 'TrackBars',116,179,nothing)
cv2.createTrackbar('satLow', 'TrackBars',160,255,nothing)
cv2.createTrackbar('satHigh', 'TrackBars',255,255,nothing)
cv2.createTrackbar('valLow', 'TrackBars',150,255,nothing)
cv2.createTrackbar('valHigh', 'TrackBars',255,255,nothing)
kit=ServoKit(channels=16)

tilt1=90
pan1=90
tilt2=90
pan2=90

kit.servo[0].angle=pan1
kit.servo[1].angle=tilt1
kit.servo[2].angle=pan2
kit.servo[3].angle=tilt2

width=720
height=480
flip=2
font=cv2.FONT_HERSHEY_SIMPLEX
camSet1='nvarguscamerasrc sensor-id=0 ee-mode=1 ee-strength=0 tnr-mode=2 tnr-strength=1 wbmode=3 ! video/x-raw(memory:NVMM), width=3264, height=2464, framerate=21/1,format=NV12 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(width)+', height='+str(height)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! videobalance contrast=1.3 brightness=-.2 saturation=1.2 ! appsink drop=True'
camSet2='nvarguscamerasrc sensor-id=1 ee-mode=1 ee-strength=0 tnr-mode=2 tnr-strength=1 wbmode=3 ! video/x-raw(memory:NVMM), width=3264, height=2464, framerate=21/1,format=NV12 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(width)+', height='+str(height)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! videobalance contrast=1.3 brightness=-.2 saturation=1.2 ! appsink drop=True'

#camSet='nvarguscamerasrc sensor-id=0 ! video/x-raw(memory:NVMM), width=3264, height=2464, framerate=21/1,format=NV12 ! nvvidconv flip-method='+str(flip)+' ! video/x-raw, width='+str(width)+', height='+str(height)+', format=BGRx ! videoconvert ! video/x-raw, format=BGR ! appsink'
#camSet ='v4l2src device=/dev/video1 ! video/x-raw,width='+str(width)+',height='+str(height)+',framerate=20/1 ! videoconvert ! appsink'
cam1=cv2.VideoCapture(camSet1)
cam2=cv2.VideoCapture(camSet2)
while True:
    _, frame1 = cam1.read()
    _, frame2 = cam2.read()

    hsv1=cv2.cvtColor(frame1,cv2.COLOR_BGR2HSV)
    hsv2=cv2.cvtColor(frame2,cv2.COLOR_BGR2HSV)

    hueLow=cv2.getTrackbarPos('hueLower', 'TrackBars')
    hueUp=cv2.getTrackbarPos('hueUpper', 'TrackBars')

    Ls=cv2.getTrackbarPos('satLow', 'TrackBars')
    Us=cv2.getTrackbarPos('satHigh', 'TrackBars')

    Lv=cv2.getTrackbarPos('valLow', 'TrackBars')
    Uv=cv2.getTrackbarPos('valHigh', 'TrackBars')

    l_b=np.array([hueLow,Ls,Lv])
    u_b=np.array([hueUp,Us,Uv])

    FGmask1=cv2.inRange(hsv1,l_b,u_b)
    FGmask2=cv2.inRange(hsv2,l_b,u_b)

    cv2.imshow('FGmask1',FGmask1)
    cv2.moveWindow('FGmask1',0,0)

    contours1,_ = cv2.findContours(FGmask1,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
    contours1=sorted(contours1,key=lambda x:cv2.contourArea(x),reverse=True)
    for cnt in contours1:
        area=cv2.contourArea(cnt)
        (x,y,w,h)=cv2.boundingRect(cnt)
        if area>=100:
            cv2.rectangle(frame1,(x,y),(x+w,y+h),(0,255,255),3)
            objX=x+w/2
            objY=y+h/2
            errorPan1=objX-width/2
            errorTilt1=objY-height/2
            if abs(errorPan1)>15:
                pan1=pan1+errorPan1/40
            if abs(errorTilt1)>15:
                tilt1=tilt1-errorTilt1/40
            if pan1>180:
                pan1=180
                print('Pan Out of Range')
            if pan1<0:
                pan1=0
                print('Pan Out of Range')
            if tilt1>180:
                tilt1=180
                print('Tilt Out of Range')
            if tilt1<0:
                tilt1=0
            kit.servo[2].angle=pan1
            kit.servo[3].angle=tilt1
            break
    
    contours2,_ = cv2.findContours(FGmask2,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
    contours2=sorted(contours2,key=lambda x:cv2.contourArea(x),reverse=True)
    for cnt in contours2:
        area=cv2.contourArea(cnt)
        (x,y,w,h)=cv2.boundingRect(cnt)
        if area>=100:
            cv2.rectangle(frame2,(x,y),(x+w,y+h),(0,255,255),3)
            objX=x+w/2
            objY=y+h/2
            errorPan2=objX-width/2
            errorTilt2=objY-height/2
            if abs(errorPan2)>15:
                pan2=pan2+errorPan2/40
            if abs(errorTilt2)>15:
                tilt2=tilt2-errorTilt2/40
            if pan2>180:
                pan2=180
                print('Pan Out of Range')
            if pan2<0:
                pan2=0
                print('Pan Out of Range')
            if tilt2>180:
                tilt2=180
                print('Tilt Out of Range')
            if tilt2<0:
                tilt2=0
            kit.servo[0].angle=pan2
            kit.servo[1].angle=tilt2            
            break

    frame3=np.hstack((frame1,frame2))
    dt=time.time()-timeMark
    timeMark=time.time()
    dtFIL=.9*dtFIL + .1*dt
    fps=1/dtFIL
    cv2.rectangle(frame3,(0,0),(150,40),(0,0,255),-1)
    cv2.putText(frame3,'fps: '+str(round(fps,1)),(0,30),font,1,(0,255,255),2)

    #cv2.imshow('myCam1',frame1)
    #cv2.imshow('myCam2',frame2)
    cv2.imshow('comboCam',frame3)
    cv2.moveWindow('comboCam',0,450)

    if cv2.waitKey(1)==ord('q'):
        break
cam1.release()
cam2.release()
cv2.destroyAllWindows()

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import cv2

import numpy as np

import time

from adafruit_servokit import ServoKit

print(cv2.__version__)

timeMark=time.time()

dtFIL=0

def nothing(x):

pass

cv2.namedWindow('TrackBars')

cv2.moveWindow('TrackBars',1320,0)

cv2.createTrackbar('hueLower', 'TrackBars',100,179,nothing)

cv2.createTrackbar('hueUpper', 'TrackBars',116,179,nothing)

cv2.createTrackbar('satLow', 'TrackBars',160,255,nothing)

cv2.createTrackbar('satHigh', 'TrackBars',255,255,nothing)

cv2.createTrackbar('valLow', 'TrackBars',150,255,nothing)

cv2.createTrackbar('valHigh', 'TrackBars',255,255,nothing)

kit=ServoKit(channels=16)

tilt1=90

pan1=90

tilt2=90

pan2=90

kit.servo[0].angle=pan1

kit.servo[1].angle=tilt1

kit.servo[2].angle=pan2

kit.servo[3].angle=tilt2

width=720

height=480

flip=2

font=cv2.FONT_HERSHEY_SIMPLEX

#camSet ='v4l2src device=/dev/video1 ! video/x-raw,width='+str(width)+',height='+str(height)+',framerate=20/1 ! videoconvert ! appsink'

cam1=cv2.VideoCapture(camSet1)

cam2=cv2.VideoCapture(camSet2)

while True:

_, frame1 = cam1.read()

_, frame2 = cam2.read()

hsv1=cv2.cvtColor(frame1,cv2.COLOR_BGR2HSV)

hsv2=cv2.cvtColor(frame2,cv2.COLOR_BGR2HSV)

hueLow=cv2.getTrackbarPos('hueLower', 'TrackBars')

hueUp=cv2.getTrackbarPos('hueUpper', 'TrackBars')

Ls=cv2.getTrackbarPos('satLow', 'TrackBars')

Us=cv2.getTrackbarPos('satHigh', 'TrackBars')

Lv=cv2.getTrackbarPos('valLow', 'TrackBars')

Uv=cv2.getTrackbarPos('valHigh', 'TrackBars')

l_b=np.array([hueLow,Ls,Lv])

u_b=np.array([hueUp,Us,Uv])

FGmask1=cv2.inRange(hsv1,l_b,u_b)

FGmask2=cv2.inRange(hsv2,l_b,u_b)

cv2.imshow('FGmask1',FGmask1)

cv2.moveWindow('FGmask1',0,0)

contours1,_ = cv2.findContours(FGmask1,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)

contours1=sorted(contours1,key=lambda x:cv2.contourArea(x),reverse=True)

for cnt in contours1:

area=cv2.contourArea(cnt)

(x,y,w,h)=cv2.boundingRect(cnt)

if area>=100:

cv2.rectangle(frame1,(x,y),(x+w,y+h),(0,255,255),3)

objX=x+w/2

objY=y+h/2

errorPan1=objX-width/2

errorTilt1=objY-height/2

if abs(errorPan1)>15:

pan1=pan1+errorPan1/40

if abs(errorTilt1)>15:

tilt1=tilt1-errorTilt1/40

if pan1>180:

pan1=180

print('Pan Out of Range')

if pan1<0:

pan1=0

print('Pan Out of Range')

if tilt1>180:

tilt1=180

print('Tilt Out of Range')

if tilt1<0:

tilt1=0

kit.servo[2].angle=pan1

kit.servo[3].angle=tilt1

break

contours2,_ = cv2.findContours(FGmask2,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)

contours2=sorted(contours2,key=lambda x:cv2.contourArea(x),reverse=True)

for cnt in contours2:

area=cv2.contourArea(cnt)

(x,y,w,h)=cv2.boundingRect(cnt)

if area>=100:

cv2.rectangle(frame2,(x,y),(x+w,y+h),(0,255,255),3)

objX=x+w/2

objY=y+h/2

errorPan2=objX-width/2

errorTilt2=objY-height/2

if abs(errorPan2)>15:

pan2=pan2+errorPan2/40

if abs(errorTilt2)>15:

tilt2=tilt2-errorTilt2/40

if pan2>180:

pan2=180

print('Pan Out of Range')

if pan2<0:

pan2=0

print('Pan Out of Range')

if tilt2>180:

tilt2=180

print('Tilt Out of Range')

if tilt2<0:

tilt2=0

kit.servo[0].angle=pan2

kit.servo[1].angle=tilt2

break

frame3=np.hstack((frame1,frame2))

dt=time.time()-timeMark

timeMark=time.time()

dtFIL=.9*dtFIL + .1*dt

fps=1/dtFIL

cv2.rectangle(frame3,(0,0),(150,40),(0,0,255),-1)

cv2.putText(frame3,'fps: '+str(round(fps,1)),(0,30),font,1,(0,255,255),2)

#cv2.imshow('myCam1',frame1)

#cv2.imshow('myCam2',frame2)

cv2.imshow('comboCam',frame3)

cv2.moveWindow('comboCam',0,450)

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

break

cam1.release()

cam2.release()

cv2.destroyAllWindows()

Technology Tutorials

All posts by admin

Jetson Xavier NX Lesson 11: Independently Tracking Different Objects in Different Cameras

Low Cost High Quality Studio for Online and Distance Learning or Electronic School Using OBS

AI on the Jetson Nano LESSON 52: Improving Picture Quality of the Raspberry Pi Camera with Gstreamer

Robotics Training LESSON 7: Calibrating the Smart Car for Distance and Speed

Jetson Xavier NX Lesson 10: Tracking Multiple Objects of Interest with Servos in OpenCV

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