Tag Archives: Raspberry Pi Camera

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()

Jetson Xavier NX

Jetson Xavier NX Lesson 8: Controlling Dual Pan/Tilt Raspberry Pi Cameras

July 8, 2020 admin

In this lesson we show how to independently control two Raspberry Pi Cameras using servo controlled pan/tilt brackets. This work will serve as the foundation for allowing us to create cameras that scan a room and locate objects of interest.

In this lesson, I am using two pan/tilt camera mounts. You can get the gear I am using on amazon HERE. I suggest purchasing two units.

Then, we also need two Version two raspberry pi cameras. I like the following ones, because they include a neat little acrylic case, and the long cable, which makes it work much better on the pan/tilt bracket. You can get the cameras HERE.

If you do not have a Jetson Xavier NX yet, you can pick up the gear I am using below:

First, you will need the Jetson Xavier NX, which you can get HERE:
You will want a quality, large SD card, I have very good luck with this one HERE:
You will need a camera. I have found that the Jetson Xavier NX works very well with most Logitech Webcams, but these cameras are a little hard to find right now. I suggest the best option if you do not have a logitech webcam is to get the Raspberry Pi Version 2 camera, which works very well. You can pick the camera up HERE.
It is optional, but I have found that it is nice to have an extra, longer cable for the Raspberry Pi camera, which is available HERE. Also, a small case/stand for the camera is nice and you can get the one I use HERE.
The Jetson Nano has a slot for a SSD drive. I really like having the SSD drive attached, and makes it much easier to keep your work backed up. The projects in these lessons will work fine with just the SD card, but if you like, the SSD drive makes life easier (note even with SSD drive, you will still need the SD card above). You can get the SSD drive I am using HERE.
You can use USB keyboard and mouse, but I like to preserve my USB slots for other things, so like using a wireless keyboard and mouse. This is optional, but I have found these work well on the Jetson Xavier NX, and you can get what I am using HERE.
You will need an HDMI cable and monitor, which you probably already have.

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

kit=ServoKit(channels=16)

tilt=90
pan=90
dTilt=10
dPan=1

kit.servo[0].angle=pan
kit.servo[1].angle=tilt
kit.servo[2].angle=pan
kit.servo[3].angle=tilt

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()
    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)
    print('fps: ',fps)
    #cv2.imshow('myCam1',frame1)
    #cv2.imshow('myCam2',frame2)
    cv2.imshow('comboCam',frame3)
    cv2.moveWindow('comboCam',0,450)
    kit.servo[0].angle=pan
    kit.servo[2].angle=pan
    pan=pan+dPan
    if pan>=179 or pan<=1:
        dPan=dPan*(-1)
        tilt=tilt+dTilt
        kit.servo[1].angle=tilt
        kit.servo[3].angle=tilt
        if tilt>=169 or tilt<=11:
            dTilt=dTilt*(-1)
    if cv2.waitKey(1)==ord('q'):
        break
cam.release()
cv2.destroyAllWindows()

import cv2

import numpy as np

import time

from adafruit_servokit import ServoKit

print(cv2.__version__)

timeMark=time.time()

dtFIL=0

kit=ServoKit(channels=16)

tilt=90

pan=90

dTilt=10

dPan=1

kit.servo[0].angle=pan

kit.servo[1].angle=tilt

kit.servo[2].angle=pan

kit.servo[3].angle=tilt

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()

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)

print('fps: ',fps)

#cv2.imshow('myCam1',frame1)

#cv2.imshow('myCam2',frame2)

cv2.imshow('comboCam',frame3)

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

kit.servo[0].angle=pan

kit.servo[2].angle=pan

pan=pan+dPan

if pan>=179 or pan<=1:

dPan=dPan*(-1)

tilt=tilt+dTilt

kit.servo[1].angle=tilt

kit.servo[3].angle=tilt

if tilt>=169 or tilt<=11:

dTilt=dTilt*(-1)

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

break

cam.release()

cv2.destroyAllWindows()

Jetson Xavier NX

Jetson Xavier NX Lesson 7: Connecting and Controlling Servos

July 1, 2020 admin

In this lesson we show you how to control a pan/tilt camera bracket with the NVIDIA Jetson Xavier NX. We go through the physical build of the bracket, how to connect the circuit, and then how to program the servos. We use the Adafruit circuitpython library, and show how to download and use the library. If you want to play along at home, you can pick the pan/tilt bracket and servos up HERE, and you can grab a couple of Raspberry Pi cameras HERE.

Below is the simple code for moving the servo using the Jetson Xavier NX:

import time
from adafruit_servokit import ServoKit
kit=ServoKit(channels=16)
tilt=125
pan=0
kit.servo[0].angle=pan
kit.servo[1].angle=tilt
for i in range(0,180):
    kit.servo[0].angle=i
    time.sleep(.05)
for i in range(180,0,-1):
    kit.servo[0].angle=i
    time.sleep(.05)
for i in range(45,180):
    kit.servo[1].angle=i
    time.sleep(.05)
for i in range(180,0,-1):
    kit.servo[1].angle=i
    time.sleep(.05)

import time

from adafruit_servokit import ServoKit

kit=ServoKit(channels=16)

tilt=125

pan=0

kit.servo[0].angle=pan

kit.servo[1].angle=tilt

for i in range(0,180):

kit.servo[0].angle=i

time.sleep(.05)

for i in range(180,0,-1):

kit.servo[0].angle=i

time.sleep(.05)

for i in range(45,180):

kit.servo[1].angle=i

time.sleep(.05)

for i in range(180,0,-1):

kit.servo[1].angle=i

time.sleep(.05)

NVIDIA Jetson Xavier NX

Jetson Xavier NX Lesson 5: Improving Raspberry Pi Camera Image Quality in Gstreamer

June 18, 2020 admin

In this video we show you the keys to radically improving the image quality from the Raspberry Pi Camera. We show how to set Gstreamer caps and props in OpenCV to get stunning image ‘pop’ from this inexpensive camera. If you follow this lesson you will be able to get better image quality from your Raspberry Pi cameras.

The code below has the improved camSet string we developed in this lesson. I have noticed that there can be variation between different Raspberry Pi cameras. Hence, you can adjust the parameters to get the best quality image from your particular camera. Also, results will depend on lighting conditions. You can adjust the wbmode to match your lighting situation, and you can tweak the contrast, brightness and saturation to dial in the perfect picture quality.

import cv2
print(cv2.__version__)
width=1280
height=720
flip=2
camSet='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 '
#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'
cam=cv2.VideoCapture(camSet)
while True:
    _, frame = cam.read()
    cv2.imshow('myCam',frame)
    cv2.moveWindow('myCam',0,0)
    if cv2.waitKey(1)==ord('q'):
        break
cam.release()
cv2.destroyAllWindows()

import cv2

print(cv2.__version__)

width=1280

height=720

flip=2

camSet='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 '

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

cam=cv2.VideoCapture(camSet)

while True:

_, frame = cam.read()

cv2.imshow('myCam',frame)

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

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

break

cam.release()

cv2.destroyAllWindows()

NVIDIA Jetson Xavier NX

Jetson Xavier NX Lesson 3: Using a WEB cam or Raspberry Pi camera in OpenCV with Gstreamer

June 3, 2020 admin

In this video lesson we learn how to launch the Raspberry Pi Camera or a simple WEB cam on the Jetson Xavier NX using openCV and a Gstreamer command. This simple code shows you how to set up the camera, and then how to grab a frame and show a frame to create live video from the cameras.

import cv2
print(cv2.__version__)
width=1280
height=720
flip=2
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=24/1 ! videoconvert ! appsink'
cam=cv2.VideoCapture(camSet)
while True:
    _, frame = cam.read()
    cv2.imshow('myCam',frame)
    cv2.moveWindow('myCam',0,0)
    if cv2.waitKey(1)==ord('q'):
        break
cam.release()
cv2.destroyAllWindows()

import cv2

print(cv2.__version__)

width=1280

height=720

flip=2

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=24/1 ! videoconvert ! appsink'

cam=cv2.VideoCapture(camSet)

while True:

_, frame = cam.read()

cv2.imshow('myCam',frame)

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

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

break

cam.release()

cv2.destroyAllWindows()

Technology Tutorials

Tag Archives: Raspberry Pi Camera

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

Jetson Xavier NX Lesson 8: Controlling Dual Pan/Tilt Raspberry Pi Cameras

Jetson Xavier NX Lesson 7: Connecting and Controlling Servos

Jetson Xavier NX Lesson 5: Improving Raspberry Pi Camera Image Quality in Gstreamer

Jetson Xavier NX Lesson 3: Using a WEB cam or Raspberry Pi camera in OpenCV with Gstreamer

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