#Install navit on raspberry pi install#
#Install navit on raspberry pi serial#
#Install navit on raspberry pi code#
#Install navit on raspberry pi Bluetooth#
#Install navit on raspberry pi free#

#Install navit on raspberry pi Bluetooth#

IMPORTANT: To get the Bluetooth adapter to connect automatially, there are a couple of extra steps that you need to take with the Raspberry Pi. Yes, the default speed values are in kilometers. Popping that in a hex to decimal converter, we get 50 km/hr. Here's a breakdown of what it means (here's a good website for more information):Ĥ1 - The response for our mode (01) commandĠD - The response for our PID (0D) command 010Dīut the result it gives us is another hex code. So my final value is 010D (as you can see by the chart above, RPM would be 010C), so I can type this into the terminal to get our result. The first set tells what mode we want to set. With that done, the next command tells the port what information we want to extract. atz #resets the device and returns the device IDĪtsp0 #automatically determines communication method To find out more about these commands, you can visit this website. Type each command (minus the # comments) and press enter.

The first few commands are standard for setting up communications. At this point we can start typing our commands. You should be presented with a blank screen. NOW we should finally be able to communicate with the adapter! A good program to use for communication is called 'screen'.

#Install navit on raspberry pi serial#

Since the OBD port is a serial port, before we can start talking to it, we need to bind it to a serial port on the Pi. Scan off #turn off scanning once your adapter has been foundĪt this point, the adapter should be connected and you should be back to your main terminal line. # If it asks for a pin, the default pin is 1234 # the OBDII adapter should read something Within the controller, you want to enter these commands in order (minus the # comments) power on # ensures bluetooth is on Just power on the pi, open up a terminal and launch the bluetooth controller. I've been using the Raspberry Pi 3 B+, which has bluetooth built in, so I don't need any other adapters. With the bluetooth adapter in place, we can now connect our Pi to it. It detected a lot of unnecessary objects, and I did notice that sometimes it would detect shadows as objects. #weed out the contours that are less than our thresholdĬv2.circle(image,(centerX, centerY), 7, (255, 255, 255), -1)Ĭv2.putText(image, 'ALERT!', (centerX -20, centerY -20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255),2)Īlright, saving it and testing out in small scale, it did pretty well. Output = cv2.bitwise_and(image, image, mask=mask)ĭilation = cv2.dilate(mask, kernel, iterations = 3)Ĭlosing = cv2.morphologyEx(dilation, cv2.MORPH_GRADIENT, kernel)Ĭlosing = cv2.morphologyEx(dilation, cv2.MORPH_CLOSE, kernel)Ĭontours, hierarchy = cv2.findContours(closing, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) #use the color range to create a mask for the image and apply it to the image YAlert = (heightAlert/2) + 100 #determine y coordinates for areaĬv2.line(image, (0,yAlert), (widthAlert,yAlert),(0,0,255),2) #draw a line to show area HeightAlert = np.size(image, 0) #get height of image WidthAlert = np.size(image, 1) #get width of image RawCapture = PiRGBArray(camera, size=(320, 240))įor still in camera.capture_continuous(rawCapture, format='bgr', use_video_port=True): I just named my file car_detector.py import timeĬamera.resolution = (320, 240) #a smaller resolution means faster processing For the fully documented code, you can visit my github repository. Once OpenCV is installed, we can create a new Python file and start on the code.

#Install navit on raspberry pi install#

Luckily the Pi can do this through the Python 'pip' command pip3 install opencv-python It worked like a charm, and there was practically no lag!īefore starting on the code, we have to install OpenCV on the Pi first. Saving it and testing it out by running 'python image_overlay.py', I tested it out on a small scale using a toy car to see how it worked. Img_overlay = camera.add_overlay(img.tobytes(), size=img.size) I just named the file image_overlay.py import picamera

#Install navit on raspberry pi code#

Next we'll create a python script that utilizes the PIL python image editor and the PiCamera (if you are not using a Pi Camera, then adjust the code for your video input).

#Install navit on raspberry pi free#

This was done intentionally, but feel free to change the image dimensions if you are streaming at a different resolution. The image above is exactly 640x480, which just so happens to be the same resolution my camera will be streaming at.