Category Archives: NVIDIA Jetson Xavier NX

In this video lesson we should you a simple method to train our face recognizer on larger data sets. We use the python os.walk command to step through, and train automatically on all the training images in our folder. We then show how to store our training set to our SD card using the pickle utility. This allows us to train once, and use the trained model over and over.

For your convenience, the code below is what we developed to allow training our face recognition model.

import face_recognition
import cv2
import os
import pickle
print(cv2.__version__)

Encodings=[]
Names=[]
j=0

image_dir='/home/pjm/Desktop/pyPro/demoimages/known'
for root, dirs, files in os.walk(image_dir):
    print(files)
    for file in files:
        fullPath=os.path.join(root,file)
        print(fullPath)
        name=os.path.splitext(file)[0]
        print(name)
        person=face_recognition.load_image_file(fullPath)
        encoding=face_recognition.face_encodings(person)[0]
        Encodings.append(encoding)
        Names.append(name)
print(Names)
with open('train.pkl','wb') as f:
        pickle.dump(Names,f)
        pickle.dump(Encodings,f)

import face_recognition

import cv2

import os

import pickle

print(cv2.__version__)

Encodings=[]

Names=[]

j=0

image_dir='/home/pjm/Desktop/pyPro/demoimages/known'

for root, dirs, files in os.walk(image_dir):

print(files)

for file in files:

fullPath=os.path.join(root,file)

print(fullPath)

name=os.path.splitext(file)[0]

print(name)

person=face_recognition.load_image_file(fullPath)

encoding=face_recognition.face_encodings(person)[0]

Encodings.append(encoding)

Names.append(name)

print(Names)

with open('train.pkl','wb') as f:

pickle.dump(Names,f)

pickle.dump(Encodings,f)

Then this is a simple program that loads the trained model, and uses it to recognize people in unknown images.

import cv2
print(cv2.__version__)
import face_recognition
import pickle

with open('train.pkl','rb') as f:
    Names=pickle.load(f)
    Encodings=pickle.load(f)

font=cv2.FONT_HERSHEY_SIMPLEX
testImage=face_recognition.load_image_file('/home/pjm/Desktop/pyPro/demoimages/unkno$

facePositions=face_recognition.face_locations(testImage)
allEncodings=face_recognition.face_encodings(testImage,facePositions)

testImage=cv2.cvtColor(testImage,cv2.COLOR_RGB2BGR)
for (top,right,bottom,left), face_encoding in zip(facePositions, allEncodings):
    name='Unknown Life Form'
    matches=face_recognition.compare_faces(Encodings,face_encoding)
    if True in matches:
        first_match_index=matches.index(True)
        name=Names[first_match_index]
    cv2.rectangle(testImage,(left,top),(right,bottom),(255,0,0),2)
    cv2.rectangle(testImage, (left,top),(left+200, top+30),(0,255,255),-1)
    cv2.putText(testImage,name,(left,top+20),font,.75,(255,0,0),2)
cv2.imshow('mywindow',testImage)
cv2.moveWindow('mywindow',0,0)
if cv2.waitKey(0)==ord('q'):
    cv2.destroyAllWindows()

import cv2

print(cv2.__version__)

import face_recognition

import pickle

with open('train.pkl','rb') as f:

Names=pickle.load(f)

Encodings=pickle.load(f)

font=cv2.FONT_HERSHEY_SIMPLEX

testImage=face_recognition.load_image_file('/home/pjm/Desktop/pyPro/demoimages/unkno$

facePositions=face_recognition.face_locations(testImage)

allEncodings=face_recognition.face_encodings(testImage,facePositions)

testImage=cv2.cvtColor(testImage,cv2.COLOR_RGB2BGR)

for (top,right,bottom,left), face_encoding in zip(facePositions, allEncodings):

name='Unknown Life Form'

matches=face_recognition.compare_faces(Encodings,face_encoding)

if True in matches:

first_match_index=matches.index(True)

name=Names[first_match_index]

cv2.rectangle(testImage,(left,top),(right,bottom),(255,0,0),2)

cv2.rectangle(testImage, (left,top),(left+200, top+30),(0,255,255),-1)

cv2.putText(testImage,name,(left,top+20),font,.75,(255,0,0),2)

cv2.imshow('mywindow',testImage)

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

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

cv2.destroyAllWindows()

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='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()

NVIDIA Jetson Xavier NX

Jetson Xavier NX Lesson 2: Installing Visual Studio Code on NVIDIA Jetpack 4.4

June 18, 2020 admin

In this video lesson, we show you how to install Visual Studio Code (code-oss) on the NVIDIA Jetson Xavier NX. We take you through the process step by step. If you want to play along at home, you can get the gear you need HERE.

NVIDIA Jetson Xavier NX

Jetson Xavier NX Lesson 4: Understanding and Using Gstreamer for Absolute Beginners

June 10, 2020 admin

In this lesson we show you how to understand the great mystery known as Gstreamer. Most folks using the NVIDIA Jetson Nano or the NVIDIA Jetson Exavier NX just copy and past the launch string they found on the internet, but do not have a clue how Gstreamer actually works. In this video we will take you through it step-by-step, and show you how to actually understand what you are doing, and how to design your own pipes for maximum performance and image quality. Below are all the commands we used in the video lesson

gst-launch-1.0 audiotestsrc ! alsasink

gst-inspect-1.0 audiotestsrc

gst-launch-1.0 audiotestsrc freq=500 ! alsasink

gst-launch-1.0 audiotestsrc freq=500 ! alsasink

gst-inspect-1.0 audiotestsrc

gst-launch-1.0 audiotestsrc freq=500 ! audio/x-raw, format=U8 ! alsasink

gst-launch-1.0 audiotestsrc freq=500 ! audio/x-raw, format=U18LE ! alsasink

gst-launch-1.0 audiotestsrc freq=500 ! audio/x-raw, format=U18LE ! audioconvert ! audio/x-raw, format=U8 ! alsasink

gst-launch-1.0 videotestsrc ! ximagesink

gst-inspect-1.0 videotestsrc

gst-launch-1.0 videotestsrc pattern=11 ! ximagesink

gst-launch-1.0 videotestsrc pattern=0 ! video/x-raw, format=BGR ! ximagesink

gst-inspect-1.0 autovideoconvert

gst-launch-1.0 videotestsrc pattern=0 ! video/x-raw, format=BGR ! autovideoconvert ! ximagesink

gst-launch-1.0 videotestsrc pattern=0 ! video/x-raw, format=BGR ! autovideoconvert ! videoconvert ! video/x-raw, width=1280, height=960 !  ximagesink 

gst-launch-1.0 videotestsrc pattern=0 ! video/x-raw, format=BGR ! autovideoconvert ! videoconvert ! video/x-raw, width=1280, height=960, framerate=30/1 !  ximagesink

gst-launch-1.0 videotestsrc pattern=0 ! video/x-raw, format=BGR ! autovideoconvert ! videoconvert ! video/x-raw, width=1280, height=960, framerate=1/1 !  ximagesink

gst-launch-1.0 nvarguscamerasrc ! autovideo

gst-launch-1.0 nvarguscamerasrc !  nvvidconv flip-method=2 ! video/x-raw,width=1280,height=840 ! autovideoconvert  !  ximagesink

gst-launch-1.0 nvarguscamerasrc ! "video/x-raw(memory:NVMM),width=3264,height=2464,format=NV12,framerate=21/1" !  nvvidconv flip-method=2 ! video/x-raw,width=640,height=480 ! autovideoconvert  !  ximagesink

gst-launch-1.0 nvarguscamerasrc ! "video/x-raw(memory:NVMM),width=3264,height=2464,format=NV12,framerate=21/1" !  nvvidconv flip-method=2 ! video/x-raw,width=640,height=480 ! autovideoconvert  ! agingtv ! ximagesink

gst-launch-1.0 nvarguscamerasrc ! "video/x-raw(memory:NVMM),width=3264,height=2464,format=NV12,framerate=21/1" !  nvvidconv flip-method=2 ! video/x-raw,width=640,height=480 ! autovideoconvert  ! agingtv ! ximagesink


gst-launch-1.0 nvarguscamerasrc ! "video/x-raw(memory:NVMM),width=3264,height=2464,format=NV12,framerate=21/1" !  nvvidconv flip-method=2 ! video/x-raw,width=1280,height=960 ! autovideoconvert  ! agingtv ! coloreffects preset=sepia ! ximagesink

gst-launch-1.0  v4l2src device=/dev/video1 ! xvimagesink

gst-launch-1.0  v4l2src device=/dev/video1 ! video/x-raw,framerate=20/1,width=864,height=480 ! xvimagesink

gst-launch-1.0 audiotestsrc ! alsasink

gst-inspect-1.0 audiotestsrc

gst-launch-1.0 audiotestsrc freq=500 ! alsasink

gst-inspect-1.0 audiotestsrc

gst-launch-1.0 audiotestsrc freq=500 ! audio/x-raw, format=U8 ! alsasink

gst-launch-1.0 audiotestsrc freq=500 ! audio/x-raw, format=U18LE ! alsasink

gst-launch-1.0 audiotestsrc freq=500 ! audio/x-raw, format=U18LE ! audioconvert ! audio/x-raw, format=U8 ! alsasink

gst-launch-1.0 videotestsrc ! ximagesink

gst-inspect-1.0 videotestsrc

gst-launch-1.0 videotestsrc pattern=11 ! ximagesink

gst-launch-1.0 videotestsrc pattern=0 ! video/x-raw, format=BGR ! ximagesink

gst-inspect-1.0 autovideoconvert

gst-launch-1.0 videotestsrc pattern=0 ! video/x-raw, format=BGR ! autovideoconvert ! ximagesink

gst-launch-1.0 videotestsrc pattern=0 ! video/x-raw, format=BGR ! autovideoconvert ! videoconvert ! video/x-raw, width=1280, height=960 ! ximagesink

gst-launch-1.0 videotestsrc pattern=0 ! video/x-raw, format=BGR ! autovideoconvert ! videoconvert ! video/x-raw, width=1280, height=960, framerate=30/1 ! ximagesink

gst-launch-1.0 videotestsrc pattern=0 ! video/x-raw, format=BGR ! autovideoconvert ! videoconvert ! video/x-raw, width=1280, height=960, framerate=1/1 ! ximagesink

gst-launch-1.0 nvarguscamerasrc ! autovideo

gst-launch-1.0 nvarguscamerasrc ! nvvidconv flip-method=2 ! video/x-raw,width=1280,height=840 ! autovideoconvert ! ximagesink

gst-launch-1.0 nvarguscamerasrc ! "video/x-raw(memory:NVMM),width=3264,height=2464,format=NV12,framerate=21/1" ! nvvidconv flip-method=2 ! video/x-raw,width=640,height=480 ! autovideoconvert ! ximagesink

gst-launch-1.0 nvarguscamerasrc ! "video/x-raw(memory:NVMM),width=3264,height=2464,format=NV12,framerate=21/1" ! nvvidconv flip-method=2 ! video/x-raw,width=1280,height=960 ! autovideoconvert ! agingtv ! coloreffects preset=sepia ! ximagesink

gst-launch-1.0 v4l2src device=/dev/video1 ! xvimagesink

gst-launch-1.0 v4l2src device=/dev/video1 ! video/x-raw,framerate=20/1,width=864,height=480 ! xvimagesink

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

Category Archives: NVIDIA Jetson Xavier NX

Jetson Xavier NX Lesson 15: Training the Face Recognition Program to Recognize People

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

Jetson Xavier NX Lesson 2: Installing Visual Studio Code on NVIDIA Jetpack 4.4

Jetson Xavier NX Lesson 4: Understanding and Using Gstreamer for Absolute Beginners

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!