We can now see the colour of the pixel we click on and iterate through multiple images. In Figure 2, we now have an image box (left) and colour box (right). We also have the line %matplotlib notebook (line 1). It is an alternative to passing the image as a parameter. This allows these variables to be updated within the onclick function. %matplotlib notebook global img fig = plt.figure(figsize=(5,5)) #Add an interactive widget to figure cid = _connect('button_press_event', onclick) #Load image and add count path = img_path img = mpimg.imread(path) plt.imshow(img) plt.show()Īnother thing to note is the use of a global variable (line 2).

Finally, we load one of our bird images (lines 10–11) and display it (line 13). You can see we have passed in the onclick function as a parameter. We then add interactive functionality to this figure using the mpl_connect function (line 7). To use this function, we start by creating a figure with matplotlib (line 4). def onclick(event): global img # get x,y of click x = round(event.xdata) y = round(event.ydata) # get RGB values rgb = img # save to clip board py(str(rgb)) Lastly, we save those channels as a string to our clipboard (line 13). We then get the RGB channels of the pixel at that coordinate (line 10). We get the x and y coordinates of the click (lines 5–6). This is run every time the image is clicked. To create this picker, we start with the onclick function. We can then paste that value straight into the notebook.įigure 1: demonstration of the simple colour picker (source: author) Every time we click on a location in the image, the RGB channels of that pixel is saved to our clipboard. In Figure 1, you can see our first picker in action. #Dataset read_path = '././data/birds/' img_path = glob.glob(read_path + '*.jpg') Simple colour picker We load all the image paths (line 3) at the given directory (line 2). You can also find the full dataset on Kaggle. You can see some examples of these in the article’s cover image. We’ll be picking colours from different images of birds. #Imports import numpy as np import matplotlib.pyplot as plt import matplotlib.image as mpimg import pyperclip import random import glob mpimg is used to load images, pyperclip is used to save strings to your clipboard and glob is used to handle file paths. You can also find the full project on GitHub. These are ways that I’ve used the colour pickers. To end, we discuss some applications in data science.

Complex picker-selects a list of colours from multiple images & displays the colours.Simple picker - selects a colour from a single image.Yet, I think you will find advantages to using one that works directly in a notebook.

I know, I know… there are loads of colour-picking tools out there.

Rgb color picker from image