I’m trying to use matplotlib to read in an RGB image and convert it to grayscale.

In matlab I use this:

In the matplotlib tutorial they don’t cover it. They just read in the image

I am trying to convert an image from RGB to grayscale. My image looks like this after reading. Img = cv2.imread('sample.png') plt.imshow(img) I tried converting this to grayscale using cv2 function and the image looks as below after conversion: gray = cv2.cvtColor(img, cv2.COLORBGR2GRAY) plt.imshow(gray). It also does this when using cv2.cvtColor(img, cv2.COLORBGR2RGB). In my case, I'm debayering a greyscale image and then saving as a 3 channel colour image. When saving both the 'rgb' and 'bgr' images, they turn out identical, and clearly are saving an rgb image as though it's bgr with red things appearing blue and vice versa. Steps to reproduce.

and then they slice the array, but that’s not the same thing as converting RGB to grayscale from what I understand.

EDIT:

I find it hard to believe that numpy or matplotlib doesn’t have a built-in function to convert from rgb to gray. Isn’t this a common operation in image processing?

I wrote a very simple function that works with the image imported using imread in 5 minutes. It’s horribly inefficient, but that’s why I was hoping for a professional implementation built-in.

Sebastian has improved my function, but I’m still hoping to find the built-in one.

matlab’s (NTSC/PAL) implementation:

How about doing it with PIL:

Using matplotlib and the formula

you could do:

You can also use scikit-image, which provides some functions to convert an image in ndarray, like rgb2gray.

Notes: The weights used in this conversion are calibrated for contemporary CRT phosphors: Y = 0.2125 R + 0.7154 G + 0.0721 B

Alternatively, you can read image in grayscale by:

You can always read the image file as grayscale right from the beginning using imread from OpenCV:

Furthermore, in case you want to read the image as RGB, do some processing and then convert to Gray Scale you could use cvtcolor from OpenCV:

The fastest and current way is to use Pillow, installed via pip install Pillow.

The code is then:

The tutorial is cheating because it is starting with a greyscale image encoded in RGB, so they are just slicing a single color channel and treating it as greyscale. The basic steps you need to do are to transform from the RGB colorspace to a colorspace that encodes with something approximating the luma/chroma model, such as YUV/YIQ or HSL/HSV, then slice off the luma-like channel and use that as your greyscale image. matplotlib does not appear to provide a mechanism to convert to YUV/YIQ, but it does let you convert to HSV.

Try using matplotlib.colors.rgb_to_hsv(img) then slicing the last value (V) from the array for your grayscale. It’s not quite the same as a luma value, but it means you can do it all in matplotlib.

Background:

Alternatively, you could use PIL or the builtin colorsys.rgb_to_yiq() to convert to a colorspace with a true luma value. You could also go all in and roll your own luma-only converter, though that’s probably overkill.

If you’re using NumPy/SciPy already you may as well use:

scipy.ndimage.imread(file_name, mode='L')

Hth,
dtk

I came to this question via Google, searching for a way to convert an already loaded image to grayscale.

Here is a way to do it with SciPy:

Three of the suggested methods were tested for speed with 1000 RGBA PNG images (224 x 256 pixels) running with Python 3.5 on Ubuntu 16.04 LTS (Xeon E5 2670 with SSD).

Average run times

pil : 1.037 seconds

scipy: 1.040 seconds

sk : 2.120 seconds

PIL and SciPy gave identical numpy arrays (ranging from 0 to 255). SkImage gives arrays from 0 to 1. In addition the colors are converted slightly different, see the example from the CUB-200 dataset.

SkImage:

PIL :

SciPy :

Original:

Diff :

Code

1. Performance

   for k, v in run_times.items():
print('{:5}: {:0.3f} seconds'.format(k, sum(v) / len(v)))


2. Output
3. Comparison
4. Imports
5. Versions

You can use greyscale() directly for the transformation.

Tags: image, python

How do I convert an image to grayscale in OpenCV?

So to convert the color image to grayscale we will be using cv2. imread(“image-name. png”,0) or you can also write cv2. IMREAD_GRAYSCALE in the place of 0 as it also denotes the same constant.

How do I convert a color image to grayscale in Python?

Cv2 Rgb To Gray Paint

Use numpy. dot() to convert an image from RGB to grayscale Call numpy. dot(a, b) with a as array[…,:3] and b as [0.2989, 0.5870, 0.1140] to convert the previous result array to grayscale.

How do I convert to grayscale?

An intuitive way to convert a color image 3D array to a grayscale 2D array is, for each pixel, take the average of the red, green, and blue pixel values to get the grayscale value. This combines the lightness or luminance contributed by each color band into a reasonable gray approximation.

How do I convert an image from grayscale to RGB?

You can convert a grayscale image into an RGB image using cat(): rgbImage = cat(3, grayImage, grayImage, grayImage); of course it will look all grayscale even though it is a “true color” RGB image – it’s just that all the “colors” are gray.

Why do we convert color image to grayscale?

The reason for differentiating such images from any other sort of color image is that less information needs to be provided for each pixel. In addition, grayscale images are entirely sufficient for many tasks and so there is no need to use more complicated and harder-to-process color images.

What is the difference between RGB and grayscale image?

The RGB colour space You have 256 different shades of red, green and blue (1 byte can store a value from 0 to 255). So you mix these colours in different proportions, and you get your desired colour. And, the channels is a grayscale image (because each channel has 1-byte for each pixel).

How do I convert RGB to grayscale?

Average method is the most simple one. You just have to take the average of three colors. Since its an RGB image, so it means that you have add r with g with b and then divide it by 3 to get your desired grayscale image. Its done in this way.

What is the use of grayscale?

Buried inside your iPhone and Android are settings which change the way your display looks. It’s called ‘greyscale’ (or grayscale, in US spelling) and turns the screen black and white, reducing its grabbiness and potentially liberating you from a very modern addiction.

What is the RGB for Gray?

Grey color codes chartHTML / CSS Color NameHex Code #RRGGBBDecimal Code (R,G,B)lightgray / lightgrey#D3D3D3rgb(silver#C0C0C0rgb(darkgray / darkgrey#A9A9A9rgb(gray / grey#808080rgb(6

What is the difference between gray and GREY?

As a noun, gray usually refers to the color. Gray is more common in the U.S., while grey is more common in other English-speaking countries. In proper names—like Earl Grey tea and the unit Gray, among others—the spelling stays the same, and they need to be memorized.

How do I convert RGB to color code?

RGB to hex conversionConvert the red, green and blue color values from decimal to hex.Concatenate the 3 hex values of the red, green and blue togather: RRGGBB.

What color looks good on GREY background?

If your grey is a dark one, choose a bright, vivid color to stand out. Neons will probably look good. If it’s a 50% black grey, you can go for either black or white. If the grey background is a lighter shade, use rich, darker tones of which ever color you prefer.

What color goes well with white background?

Most colors will go with a white background and black text. Pastels will give the appears of something simple and soft. Bold colors like red and yellow will demand attention. Grays will give a more predictable monochromatic look.

What is the best color for a backdrop?

Solid color backgrounds are a good option if you’re trying to create a classic look for family portraits and other types of simple portraiture. Neutral background colors like grey or tan are simple, versatile, and easy to color correct in post processing.

What are two good color combinations?

Rgb To Gray Python Cv2

Here are some of our favorite two-color combinations.Yellow and Blue: Playful and Authoritative. Navy and Teal: Soothing or Striking. Black and Orange: Lively and Powerful. Maroon and Peach: Elegant and Tranquil. Deep Purple and Blue: Serene and Dependable. Navy and Orange: Entertaining yet Credible.

What is the most annoying color?

Which color is the most irritating? Yellow, pure bright lemon yellow is the most fatiguing color.

What is a color that matches with everything?

Cv2 Rgb To Gray Color

White: combines with everything, especially blue, red and black. Beige: combines with blue, brown, emerald, black, red, white. Gray: combines with fuchsia, red, violet, pink, blue. Pink: combines with brown, white, mint green, olive, gray, turquoise, light blue.