It is time for you to begin to put all the things you have learned about the arduino together into a practical application. In this series of lessons we will show how to apply what you learned in our most excellent arduino lessons to use. We will be building and programming the Elegoo Smart Car. If you home gamers want to play along, you can grab your gear HERE.
Robotics Training LESSON 3: Mechanical Build of the Upper Deck of the Elegoo Smart Car
In this lesson we complete the mechanical build of the Elegoo Smart Car Version 3.0. We build the lower deck, and then complete the assembly with the upper deck. We confirm electrical functionality by showing the motors operating. If you want to play along at home, grab your gear HERE.
Robotics Training LESSON 2: Mechanical Build of the Lower Deck of the Elegoo Smart Car
In this video lesson we take you through assembly of the lower deck of the Elegoo Smart Car Version 3.0. We show the complete build of the lower deck. If you want to play along at home, you can grab your gear HERE.
New Robotic Training Tutorials
We are excited to announce that we will be doing a robotic tutorial series. Our number one request from our followers over the last few years has been to do a training class for beginners on robotics. You ask for it, now you have it. This training series will be based on the Elegoo Smart Car Version 3. To play along at home, you can grab your gear HERE:
Jetson Xavier NX Lesson 5: Improving Raspberry Pi Camera Image Quality in Gstreamer
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.
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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() |