leftwar.blogg.se - Contour lines in art example

#Contour lines in art example install
#Contour lines in art example full
#Contour lines in art example code
#Contour lines in art example download

What this is saying now is you can display the images indefinitely until you push a key. You won't see any output until you invoke cv2.waitKey(0). I call imshow to show what the original donut image looks like (grayscale) and what the output contour looks like. Last thing we want to do is show what the results look like. After, you specify how thick you want the contour to be drawn. You then specify what colour you want the contour to look like. If it all works out, you should only have one contour detected. You specify the image you want to show the contours in, the contours structure that was created from earlier, and the -1 flag says to draw all of the contours in the image. Once we create this image, we run the drawContours method. This will contain our detected outer contour of the donut.

Once we detect the contours, we create a new output image that is entirely black.

#Contour lines in art example full

I also specify the CHAIN_APPROX_NONE flag to ensure we get the full contour without any approximations. Take note that I specified RETR_EXTERNAL to detect the outer most contour of the object.

hierarchy - This contains additional information about the contours you've detected, like the topology, but let's skip this for the sake of this post.

contours - This is an array structure that gives you the (x,y) co-ordinates of each contour detected in your image.

Once I load in the image, I then run findContours, and the output of this function outputs a tuple of two things: I set the flag to be 0 to make the image grayscale to make things simple.

#Contour lines in art example install

OpenCV and NumPy work with each other, which is why you need to install both packages. I imported NumPy as np, and if you look at numpy docs and tutorials everywhere, they do this to minimize typing. First we import the OpenCV and NumPy packages. # Wait indefinitely until you push a key. # (in grayscale) and the detected contour # Spawn new windows that shows us the donut # in white, and set the thickness to be 3 pixelsĬv2.drawContours(out, contours, -1, 255, 3) # On this output, draw all of the contours that we have detected # Create an output of all zeroes that has the same shape as the input # Also, we want to find the best contour possible with CHAIN_APPROX_NONEĬontours, hierarchy = cv2.findContours(im.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) # Run findContours - Note the RETR_EXTERNAL flag # Read in the image as grayscale - Note the 0 flag

#Contour lines in art example download

Once you download this image, save it as donut.png, then go ahead and run this code: import cv2 # Import OpenCV So long as you have only a single object contained in this image, we actually don't need tho access the alpha channel at all.

In other words, I created this image:Īs for your images being PNG and having an alpha channel, that actually doesn't matter. In any case, I took your donut image, and I extracted just the image with the donut. If you're using Windows, the best way to get this to work is through Christoph Gohlke's unofficial Python packages for Windows: - Check the OpenCV package and install all of the dependencies it is asking for, including NumPy which you can find on this page.If you're using Mac OS, install Homebrew, then install via brew install opencv then brew install numpy.sudo apt-get install libopencv-dev python-numpy). If you're using Linux, simply do an apt-get on libopencv-dev and python-numpy (i.e.I'm not sure what platform you're using, but: You first need to install OpenCV and NumPy to get this going.

#Contour lines in art example code

Here's some reproducible code for you to illustrate this point. As with his/her post, use the findContours method and use the RETR_EXTERNAL flag to get the outer most contour of the shape. OpenCV in Python is one of the best tools you can use if you want to find contours.