This is not exactly related to your original question but consider using a better algorithm for generating the histogram. The module also provides a number of factory functions, including functions to load images from files, and to create new images.Image.histogram() Returns a histogram for the image. How can I speed this up and be more Pythonic? How to Compute Image Moments in OpenCV Python? python histogram image-processing contrast-enhancement histogram-equalization image-contrast-enhancement imhist 2dhist hist2d im2dhisteq two-dimensional-histogram. To visualize colors in the image we need to follow the below steps- Stepwise Implementation Step 1: Import Necessary Modules To this Concept mainly we need 2 modules. import cv2 import matplotlib.pyplot as plt import numpy as np Step 2 - Let's read the image. Moreover, counts for values 254 and 255 are summed in last bin. You can vectorize this code with Numpy, or use Matplotlib to do it in an even more simple manner. In this article, we're going to program a histogram equalizer in python from scratch. Making statements based on opinion; back them up with references or personal experience. We can compute the 2D histograms for two color channels at a time. To compute and plot 2D histograms of an input image, one could follow the steps given below . The color image has three channels- Red, Green and Blue. You can use newer OpenCV python interface which natively uses numpy arrays and plot the histogram of the pixel intensities using matplotlib hist. it should be given in square brackets, ie, " [img . If img is already an array, you can skip that step. How do I delete a file or folder in Python? The histograms of two images can be compared using cv2.compareHist() function. On the other hand, according to this, what you get out from newer versions of openCV is already a numpy array. UPDATE: How to compute the extent of an object in image using OpenCV Python? Step 1 - Import the libraries required for the histogram of a grayscale image. For starters, convert an image to gray and black & white using the following code. By visualizing the histogram we can improve the visual presence of an image and also we can find out what type of image processing could have been applied by comparing the histograms of an image. This is what Histogram equalization means in simple terms. First I convert the colored image to gray and give it to the equalizeHist function: image = cv2.imread ("photo.jpg") image = cv2.cvtColor (image, cv2.COLOR_BGR2GRAY) cv2.equalizeHist (image) cv2.imshow ("equalizeHist", image) cv2.waitKey (0) But after this I need to convert the . This should take you through everything you want to do, and without the for loops. In simple words, we can also say that histogram represents the distribution of pixels of an image on the coordinate system. The histogram method returns the list of Values to plot Histogram. Color Adjusted Images. In image processing histograms are used to depict many aspects regarding the image we are working with. Split the input image into the respective channels Blue, Green and Red using cv2.split() function. On the x-axis, it contains the pixel values that range from 0-255, and on the y-axis, it has the frequency of these pixels . Please include what you were doing when this page came up and the Cloudflare Ray ID found at the bottom of this page. import numpy as np. A higher bar represents more observations per bin. A bi-level image (mode "1") is treated as a grayscale ("L") image by this method. Read the full article with source code here I hope you understand what is histogram and how to create histograms using skimage. But if you want to find histogram of particular region of image, you have to create a mask image for that and give it as mask. No need to use openCV for everything when there is pure numpy or numpy based libraries like scikit-image. import matplotlib.mlab as mlab. Typically, the histogram of an image will have something close to a normal distribution, but equalization aims for a uniform distribution. I understand you want to learn the language, but Python's utility is that there are so many tools that allow you to do all kinds of things easily and efficiently. The list will have all the counts concatenated for each band. this is very fast. It is a graph or plot which represents the intensity distribution of an image. Updated on 02-Dec-2022 10:41:58. Are the S&P 500 and Dow Jones Industrial Average securities? pixels_per_cell: Determines the size of the cell, as we mentioned earlier, it is 8x8. A histogram is basically used to represent data provided in a form of some groups.It is accurate method for the graphical representation of numerical data distribution.It is a type of bar plot where X-axis represents the bin ranges while Y-axis gives information about frequency. What is a histogram and how is it useful? A complete matplotlib python histogram. Would it be possible, given current technology, ten years, and an infinite amount of money, to construct a 7,000 foot (2200 meter) aircraft carrier? It looks like this: But a histogram is more than a simple bar chart. Such as. But images can be also represented using 2, 2 bits and so on. Would salt mines, lakes or flats be reasonably found in high, snowy elevations? Shahid Akhtar Khan. Agree I know tools already exist. You can use the plt.hist () method like so: import cv2 import matplotlib.pyplot as plt img = cv2.imread ('lena.png', 0) plt.hist (img.ravel (), 256, (0, 256)) plt.show () Output: Share Improve this answer Follow answered Jul 2, 2021 at 14:57 Ann Zen 26k 7 34 54 Add a comment Your Answer Post Your Answer Should teachers encourage good students to help weaker ones? Your IP: A histogram is a graphical representation of data. The main thing that makes python great isn't the language itself (though that's nice too (if slow)). mask : mask image. on my computer it's about 150 times faster than pure python. Explore image histograms using some complimentary tools in NumPy and Matplotlib. We saw in the Image Basics episode that we could use a histogram to visualise the differences in uncompressed and compressed image formats. The default mode is to represent the count of samples in each bin. Images are stored as pixels values, each pixel value represents a color intensity value. 5.5 v) Image Segmentation Results for Different Values of K. 6 2. In order to properly quantify the information the images often need to be segmented for. By using our site, you Image Histograms in OpenCV Python. This module attempts to enhance contrast of a given image by equalizing its two dimensional histogram. 5.2 ii) Preprocessing the Image. Learn more, # split the image into the respective channels Blue, Green and Red, # 2D color histogram for the red and green channels, # 2D color histogram for the blue and red channels. python histogram_matching.py <source_image> <ref_image> [<mask_image>] For example (put this command all on one line): python histogram_matching.py aspens_in_fall.jpg forest_resized.jpg mask.jpg Source Code #!/usr/bin/env python ''' Welcome to the Histogram Matching Program! How to compute the morphological gradient of an image using OpenCV in Python? Video Tutorial What is a Histogram? Just a kid that writes about data and the world. If a mask is provided, the method returns a histogram for those parts of the image where the mask image is non-zero. histogram (input, min, max, bins, labels = None, index = None) [source] # Calculate the histogram of the values of an array, optionally at labels. Python offers a handful of different options for building and plotting histograms. Normally, such loops are written in c/c++(most straightforward in my opinion) and then called from python, it's main role being that of a scripting language. The histogram () method provides information on counts of different colors/bands. Most people know a histogram by its graphical representation, which is similar to a bar graph: The counting itself will be very fast. An image is made up of elements called pixels; the smallest pieces of information. Asking for help, clarification, or responding to other answers. In such cases the intensity range is high and it is hard to represent each intensity value in a histogram. For example. imgpath = "4.2.07.tiff" img = cv2.imread (imgpath,0) Here while reading the image, we passed the second argument as 0 to read the image as a grayscale image. 5.4 iv) Applying K-Means for Image Segmentation. But good images will have pixels from all regions of the image. In the above code, we have loaded the grayscale image of Lenna and generated its histogram using matplotlib. Cloudflare Ray ID: 77816b46be28e259 The color image has three channels- Red, Green and Blue. Image To Histogram Sample The histogram focuses only on the proportion of the colors and not the location of the colors in the Images. To compute the 2D histogram for green and blue channels we apply below code snippet. It's a technique for adjusting the pixel values in an image to enhance the contrast by making those . We can apply the cv2.calcHist() function to compute a 2D histogram of an image. One-channel histogram (image converted to grayscale): import numpy as np import cv2 as cv from matplotlib import pyplot as plt img = cv.imread ('home.jpg',0) plt.hist (img.ravel (),256, [0,256]); plt.show () RGB histogram (each channel separately) 209.145.58.150 A histogram is collected counts of data organized into a set of bins. Another Example:Here used another image.Image Used: [970, 228, 158, 207, 258, 217, 257, 260, 256, 252, 224, 277, 247, 293, 294, 305, 303, 309, 318, 321, 343, 326, 313, 295, 346, 292, 356, 340, 305, 311, 360, 373, 350, 357, 384, 356, 325, 380, 373, 389, 355, 336, 328, 349, 364, 335, 390, 340, 343, 382, 343, 339, 351, 329, 364, 350, 356, 362, 381, 349, 386, 366, 351, 345, 357, 353, 339, 359, 387, 346, 371, 359, 319, 330, 321, 311, 300, 313, 325, 338, 322, 330, 303, 354, 335, 321, 313, 289, 286, 286, 264, 279, 267, 255, 277, 266, 297, 261, 282, 267, 254, 269, 246, 244, 265, 240, 231, 250, 210, 227, 202, 200, 217, 191, 187, 217, 199, 171, 180, 152, 195, 172, 158, 170, 177, 159, 151, 152, 143, 159, 183, 138, 169, 162, 145, 161, 147, 150, 160, 186, 163, 153, 139, 153, 149, 144, 148, 143, 167, 144, 184, 154, 160, 134, 130, 144, 176, 118, 140, 132, 115, 119, 130, 130, 120, 125, 121, 133, 105, 123, 105, 106, 92, 114, 101, 112, 103, 106, 98, 118, 110, 111, 99, 99, 107, 74, 109, 83, 94, 97, 87, 85, 88, 77, 77, 92, 94, 69, 91, 97, 71, 100, 83, 80, 83, 53, 89, 72, 68, 70, 58, 74, 67, 69, 64, 80, 81, 68, 57, 47, 60, 53, 59, 53, 64, 63, 69, 52, 48, 46, 51, 52, 41, 49, 45, 43, 41, 32, 43, 42, 47, 46, 34, 38, 39, 34, 33, 31, 21, 23, 28, 25, 15, 15, 24, 148], Python Programming Foundation -Self Paced Course, Data Structures & Algorithms- Self Paced Course, Python PIL | logical_and() and logical_or() method, Python PIL | ImageChops.subtract() method, Python PIL | ImageChops.subtract() and ImageChops.subtract_modulo() method. In this post, youll learn how to create histograms with Python, including Matplotlib and Pandas. A Medium publication sharing concepts, ideas and codes. To illustrate the effect of the histogram matching, we plot for each RGB channel, the histogram and the . In Combined Color Histogram the intensity count is the sum of all three color channels. Does Python have a ternary conditional operator? mu = 100 # mean of distribution. In image processing, a histogram is quite an important tool. If the image has more than one band, the histograms for all bands are concatenated (for example, the histogram for an "RGB" image contains 768 values). Python Quick Tip #2: Plotting Image Histograms. Using CV2 is like using a cannon to kill a mosquito. histogram of color image python. Now move on the program: 1st import the all required package : Creating a Histogram It consists of exactly 768 values for the three colors in the RGB Model of the given Image. Image Class consists of various builtin methods in which histogram is one of them. An example of spreading the histogram of an image is as . For color image, you can pass [0],[1] or [2] to calculate histogram of blue,green or red channel respectively. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. Click to reveal Histogram matching with OpenCV, scikit-image, and Python In the first part of this tutorial, we'll discuss histogram matching and implement histogram matching using OpenCV and scikit-image. 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It is used in image modification and enhancement so we can acquire image attributes that lead to a greater understanding of data. But if you want to find histogram of particular region of image, you have to create a mask image for that and give it as mask. You would have also heard of another term called 'Computer Vision. This is also observed on the histogram of pixel intensity value wherein the PDF is skewed on the lower . import cv2 import numpy as np. How to compute Hu-Moments of an image in OpenCV Python? Python's for loop construct has too many things going on to be fast. Enjoy unlimited access on 5500+ Hand Picked Quality Video Courses. . OpenCV Python How to compute and plot the histogram of a region of an image? Compute the 2D histograms for all three combinations of three color channels. If the image has more than one stripe, histograms for all stripes are combined (for example, the histogram for an "RGB" image contains 768 values). One-channel histogram (image converted to grayscale): Thanks for contributing an answer to Stack Overflow! Help us identify new roles for community members, Proposing a Community-Specific Closure Reason for non-English content, Formula to determine perceived brightness of RGB color, Speed up iteration over Numpy arrays / OpenCV cv2 image. Above specified number of bins not always provide desired result as min and max are calculated from actual values. Histograms in Image Processing with skimage-Python Visualizations are always been an efficient way to represent and explain many statistical details. Another way to speed it up would be to use numpy, but there again you are using a library to help you. It is actually one of the best methods to represent the numerical data distribution. [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 3, 1, 2, 3, 4, 3, 2, 3, 10, 7, 6, 7, 13, 14, 6, 22, 9, 19, 23, 21, 29, 23, 36, 42, 32, 46, 59, 51, 53, 69, 49, 61, 64, 79, 69, 55, 66, 73, 78, 64, 82, 84, 83, 67, 85, 87, 91, 84, 87, 63, 79, 86, 86, 77, 75, 78, 85, 77, 78, 92, 83, 78, 86, 90, 97, 96, 94, 90, 94, 76, 99, 97, 113, 108, 92, 120, 124, 110, 140, 121, 124, 132, 144, 132, 145, 151, 163, 145, 147, 184, 151, 161, 177, 199, 200, 205, 218, 223, 274, 237, 245, 254, 260, 281, 299, 301, 354, 361, 335, 392, 365, 375, 389, 367, 396, 387, 415, 398, 404, 417, 404, 405, 447, 483, 493, 484, 470, 440, 473, 472, 441, 462, 467, 461, 468, 474, 438, 449, 451, 431, 468, 470, 415, 452, 407, 379, 411, 358, 383, 418, 375, 414, 376, 375, 341, 361, 340, 350, 354, 293, 318, 325, 297, 316, 287, 326, 287, 307, 289, 314, 296, 275, 262, 281, 262, 278, 268, 320, 254, 288, 279, 280, 259, 252, 257, 257, 245, 227, 231, 254, 282, 263, 248, 218, 250, 246, 232, 244, 237, 208, 217, 215, 226, 205, 223, 212, 227, 220, 213, 198, 197, 224, 193, 200, 173, 190, 184, 190, 183, 3263]. How does legislative oversight work in Switzerland when there is technically no "opposition" in parliament? Here's a solution in numba without changing your looping code. Histogram actually provides how frequently various colors occur in an image but not the location of color in an image. At first glance, it is very similar to a bar chart. For color image, you can pass [0], [1] or [2] to calculate histogram of blue, green or red channel respectively. However, I want to use this as a learning opportunity for both the language and algorithms. So in that case you can skip the asarray completely. Step 1 Import the libraries required for the histogram of a grayscale image. Given an image x of dimensions 2048x1354 with 3 channels, efficiently calculate the histogram of the pixel intensities. Histogram Calculation in OpenCV So now we use cv.calcHist () function to find the histogram. Updated on Jul 16, 2021. Histograms Equalization using Python OpenCv Module. OpenCV can generate histograms for both color and gray scale images. In the United States, must state courts follow rulings by federal courts of appeals? A histogram of an image represents how frequently various color values occur in the image or the distribution of pixel intensities of a colour or gray-scale image. A histogram shows the number of occurrences of different values in a dataset. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. The code below creates a more advanced histogram. Method #1: Using the OpenCV cv2.compareHist function Perhaps not surprisingly, OpenCV has a built in method to facilitate an easy comparison of histograms: cv2.compareHist. The hog () function takes 6 parameters as input: image: The target image you want to apply HOG feature extraction. Make sure you have already installed them. The color image has three channels- Red, Green and Blue. Grayscale image Usually, the range of intensity values of images is from [0255] in 8bits representation(2). Histograms provide an easy understanding of the features of the pixels in an image such as contrast, brightness, intensity distribution, etc., X-axis represents the range of values a variable can take, and is divided into several series of intervals knows as bins Y-axis represents number of pixels that have particular intensity 32. # example data. We can compute the 2D histograms for two color channels at a time. For example, if i = 0, the h(0) is the number of pixels with a value of 0. Interestingly the way. Let me give you an example and you'll see immediately why. Since the image is stored in the form of a 2D ordered matrix we converted it to a 1D array using the ravel() method. let us plot the histogram of grayscale Lenna image again but this time with 8 bins. A histogram is a graph that represents the way numerical data is represented. So we have three combinations of the color channels taking two at a time- Red & Green (or Green & Red), Green & Blue (or Blue & Green) and Blue & Red (or Red & Blue). image histogram python without imhist. Python Histogram A histogram is one type of a graph and they are basically used to represent the data in the graph forms. It provides us a graphical representation of the intensity distribution of an image. To find the similarity between the two images we are going to use the following approach : Read the image files as an array. We use the following image as the Input File in the examples below. In image processing histograms are used to depict many aspects regarding the image we are working with. So we have three combinations of the . In color images, we have 3 color channels representing RGB. Plotting a Histogram in Python with Matplotlib and Pandas June 22, 2020 A histogram is a chart that uses bars represent frequencies which helps visualize distributions of data. It's its huge set of standard libraries, and if you don't use them, you're crippling python. A histogram is a great tool for quickly assessing a probability distribution that is intuitively understood by almost any audience. We see significant improvement per color channel, with all of them almost resembling a straight line. Histogram Calculation in OpenCV So now we use cv.calcHist () function to find the histogram. The cv2.compareHist() function accepts three input arguments- hist1, hist2, and compare_method.The hist1 and hist2 are histograms of the two input images and compare_method is a metric to compute the matching between the histograms. You can email the site owner to let them know you were blocked. Histogram of the Image | Digital Image Processing 1 | Python P&P Coding Laboratory 552 subscribers 63 Dislike Share 3,672 views Jul 5, 2020 An image histogram is a grey-scale value. Python OpenCV Histogram of Grayscale Image. It is a graphical representation of the intensity distribution of an image. Histogram Background Information Digital images are composed of two-dimensional integer arrays that represent individual components of the image, which are called picture elements, or pixels. The histogram is returned as a list of pixel counts, one for each pixel value in the source image. We'll then configure our development environment and review our project directory structure. Manually raising (throwing) an exception in Python. In Python, you can use the Matplotlib library to plot histograms with the help of the pyplot hist function. Find centralized, trusted content and collaborate around the technologies you use most. Is the EU Border Guard Agency able to tell Russian passports issued in Ukraine or Georgia from the legitimate ones? Does illicit payments qualify as transaction costs? Follow More from Medium Frank Andrade in Towards Data Science Predicting The FIFA World Cup 2022 With a Simple Model using Python Anmol Tomar in CodeX Say Goodbye to Loops in Python, and Welcome Vectorization! In your case: I'm using numpy.asarray here to make sure that img is a numpy array, so I can flatten it to the one-dimensional array bincount needs. Python isn't the best for 'for' loops. What is Histogram Equalization? We do not currently allow content pasted from ChatGPT on Stack Overflow; read our policy here. This is a vector of numbers and can be a list or a DataFrame column. It does this by effectively spreading out the intensity of pixels from dense areas in the histogram over the entire range of pixels, that is, from 0 to 255. rev2022.12.11.43106. Let us meet again and Ill tell you some use cases of histograms in Image Processing. histogram () method returns a list of pixel counts for each band present in the image. Cumulative histograms are useful in many image processing applications like histogram equalization and so on. In histogram, the x axis represents the bin ranges and the y axis represents the information about the frequency of the data. (Image by Author) Since the image was taken at nighttime, the features of the image are dim. It is basically used to improve the contrast of images. Does a 120cc engine burn 120cc of fuel a minute? Most of the time here will probably be spent in converting the cv matrix to an array. We can use projections to extract features onto an image, for example, if we want to recognize some characters. The Image module provides a class with the same name which is used to represent a PIL image. Introduction to Histograms As it pertains to images, a histogram is a graphical representation showing how frequently various colour values occur in the image. How do I access environment variables in Python? Syntax: Image.histogram(mask=None, extrema=None)Parameters:mask An optional mask.Returns: A list containing pixel counts. Grayscale image is an image in which the value of each pixel is a single sample, that is, it carries only intensity information where pixel value varies from 0 to 255. Not the answer you're looking for? Debian/Ubuntu - Is there a man page listing all the version codenames/numbers? Image Processing: Algorithm Improvement for 'Coca-Cola Can' Recognition. The mask image must have the same size as the image, and be either a bi-level image (mode 1) or a grayscale image (L). ''' USAGE: python hog_image_recognition.py --path person_car_cup python hog_image_recognition.py --path flowers ''' import os import cv2 import argparse from sklearn.svm import LinearSVC from skimage . local histogram processing in digital image processing python. Japanese girlfriend visiting me in Canada - questions at border control? With the histnorm argument, it is also possible to represent the percentage or fraction of samples in each bin (histnorm='percent' or probability), or a density histogram (the sum of all bar areas equals the total number of sample points, density), or a probability density histogram (the sum of all bar . PIL is the Python Imaging Library which provides the python interpreter with image editing capabilities. We make use of First and third party cookies to improve our user experience. It can be explained as follows 0 to 255 values indicate Red Colour Indices and many more. Actually this method usually increases the global contrast of many images, especially when the usable data of the image is represented by close contrast values and through this adjustment, the intensities can be better distributed on the histogram and it allows for areas of lower local contrast to gain a higher contrast. imgpath = "4.2.07.tiff"img = cv2.imread(imgpath,0) Here while reading the image, we passed the second argument as 0 to read the image as a grayscale image. In this post, you will learn how to compute the histogram of an image using Python OpenCV or cv2.calchist function. Image.histogram () Returns the histogram for the image. Let's look at some examples for a clear understanding about the question. How to compute the aspect ratio of an object in an image using OpenCV Python? To get a good image of a brighter picture. The histogram plot shows the intensity distribution of an image. From this section, we will start our python coding. Site design / logo 2022 Stack Exchange Inc; user contributions licensed under CC BY-SA. Here we quantize the range into several buckets. import cv2import matplotlib.pyplot as pltimport numpy as np Step 2 Let's read the image. Visualizations are always been an efficient way to represent and explain many statistical details. Histograms Equalization in OpenCV OpenCV Python Program to analyze an image using Histogram OpenCV C++ Program for Face Detection Opencv Python program for Face Detection Face Detection using Python and OpenCV with webcam OpenCV Python Tutorial Reading an image in OpenCV using Python Python OpenCV | cv2.imshow () method OpenCV Python Server Side Programming Programming. agree. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Read the input image using cv2.imread() method. Your home for data science. To find histogram of full image, it is given as "None". A huge part of python is learning what tools are available, and matplotlib is a huge library that I use in almost all of my code. If the image has more than one band, the histograms for all bands are concatenated (for example, the histogram for an RGB image contains 768 values).A bi-level image (mode 1) is treated as a grayscale (L) image by this method. the images of faces are histogram equalized to make them all with same lighting conditions. binsint or sequence of scalars or str, optional If bins is an int, it defines the number of equal-width bins in the given range (10, by default). A histogram is a graphical representation of statistical data that uses rectangles to represent the frequency of the data items. import matplotlib.pyplot as plt. The difference is that in image processing we take an input image, do required changes, and output the resulting image. Image Segmentation using K-means. To learn more, see our tips on writing great answers. In this very short blog, we will see how we can plot all 3 color channels histogram (red, green, blue) of an Image in Python using OpenCV. Python. Updated: Jun 11, 2020. ## code to plot histogram in python import numpy as np import cv2 from matplotlib import pyplot as plt img = cv2.imread('Chatth_Puja_Bihar_India.jpeg',0) . How to plot histograms of different colors of an image in OpenCV Python? December 5, 2020. Bonus. (I will show an example later.) What properties should my fictional HEAT rounds have to punch through heavy armor and ERA? So we have three combinations of the color channels taking two at a time- Red & Green (or Green & Red), Green & Blue (or Blue & Green) and Blue & Red (or Red & Blue). Image Recognition using Histogram of Oriented Gradients (HOG) Descriptor and Linear SVM. 5 1. It takes less than second on my computer. What an image histogram is and why it is useful To equalize histograms of images by using the OpenCV function cv::equalizeHist Theory What is an Image Histogram? If you just want to count the number of occurences of each value in an array, numpy can do that for you using numpy.bincount. Every bin shows the frequency. The hist syntax to draw a histogram is. We can simply solve this. Projection Histogram of image using Python and Opencv. (I will show an example later.) Affordable solution to train a team and make them project ready. A histogram is a graphical representation that displays how frequently various color values occur in an image. Connect and share knowledge within a single location that is structured and easy to search. Histograms are frequency distribution of these intensity values that occur in an image. Histogram equalization is a very basic and useful image processing technique. How to upgrade all Python packages with pip? To read the image, we use imread() function which is giving in opencv library. write the image histogram function in python other than histogram. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. matplotlib.pyplot.pie (x, bins) In the above histogram syntax, x represents the numeric data that you want to use in the Y-Axis, and bins will use in the X-Axis. Edit: According to this answer, you may need to use numpy.asarray(img[:,:]) (or possibly img[:,:,:]) in order to successfully convert the image to an array. How do I concatenate two lists in Python? Also, the number of bins decides the shape of the histogram. Histogram Equalization is one of the fundamental tools in the image processing toolkit. It is a plot with pixel values (ranging from 0 to 255, not always) in X-axis and corresponding number of pixels in the image on Y-axis. 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