Raspberry Pi-Open CV和C ++

Question

We're doing a project in school where we need to do basic image processing. What we want to do in our project is take a picture every 50ms (or faster) with our Raspberry Pi and do real time image processing.

We've tried to include raspistill in our python-program but so far nothing has worked. The goal of our project is to design a RC-car which follows a blue/red/whatever coloured line with help from image processing.

We thought it would be a good idea to make a python-program which does all image processing necessary, but we currently struggle with the idea of bringing recorded images into the python program. Is there a way to do this with picamera or should we try a different way?

Thanks in advance, anthrx.

Answer 1

I'm just going to gloss over how to do this without writing up a full program. The short answer is this is VERY possible and relatively simple.

Step 1 : Get an image from the camera
For this I would recommend just using VideoCapture and processing each image that comes in. This can be done like so:

import numpy as np
import cv2
cap = cv2.VideoCapture(0)

while True:
    ret, frame = cap.read() # Read the current frame

Step 2 : Detecting the color (I'll give an example of red)
For this you will need to define some boundaries in the RGB colorspace. For this you really just need to determine some lower and upper boundaries

boundaries = [
([17, 15, 100], [50, 56, 200]),
([25, 146, 190], [62, 174, 250])
]

This is the lower and upper bounds of two boundaries. For instance ([17, 15, 100], [50, 56, 200]) is saying we are looking for R>=17 , B>=15 , G>=100 and R<=50 , B<=56 , G<=200 . And yes, the format is RBG for this because of the default scheme in OpenCV

Step 3 : Put it together

while True:
    ret, frame = cap.read() # Read the current frame
    for (lo, up) in boundaries:
        lo = np.array(lo, dtype='uint8')
        up = np.array(up, dtype='uint8')

        # Find the colors within those boundaries in the image
        mask = cv2.inRange(frame, lo, up)
        out = cv2.bitwise_and(frame, frame, mask=mask)

out now contains the current frame but only the red that is in the image within those boundaries. You can then determine if there is enough red in the image to follow, or turn or what. If you want to actually determine if it's a line of some sort, you can also use findContours to determine the shape of the object that is in red, and then figure out if it's a line that way.