COLOR_BGR2GRAY) cv2. OpenCV provides us with the cv2. Jan 3, 2023 · Step 4: Plot histograms. Suggested: Matplotlib Histogram from Basic to Advanced. Mar 18, 2024 · Definition. from matplotlib import pyplot as plt. matches that of a target image. hist it computes the histogram and plots it from a raw data: plt. Image array. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. The equalized image [ 1] has a roughly linear cumulative distribution function for each pixel neighborhood. The vertical axis denotes the frequency of each intensity. Jul 11, 2017 · Histogram Equalization is the process taking a low contrast image and increasing the contrast between the image’s relative highs and lows in order to bring out subtle differences in shade and create a higher contrast image. Keep in mind that histogram equalization is often more effective on grayscale images. Note: this argument is ignored for integer images, for which each integer is its own bin. import numpy as np. Startup commands# First, let's start IPython. By the… Read More »NumPy Histogram: Understanding the np Dec 16, 2021 · Numpy has a built-in numpy. array. Histogram. In the last tutorial ( Histogram Equalization) we talked about a particular kind of histogram called Image Mar 14, 2023 · Algorithm for Histogram plotting. histogram (data, bins=10, range=None, normed=None, weights=None Figure 6: Plotly histogram with bin size equal to 5. The rectangles having equal horizontal size corresponds to class interval called bin and variable height corresponding to the frequency. Here's the code: import cv2. This code uses these images to make a histogram comparison. Dec 14, 2023 · An image histogram is the distribution of image pixels’ values. Create a Histogram in Matplotlib. def build_histogram(image, bins=256): # convert from BGR to RGB. If bins is an int, it defines the number of equal-width bins in the given range (10, by img = cv2. hist(arr, bins=bins) Here is the complete example for the histogram of image region of any shape: Code: import numpy as np. Parameters: aarray_like. Note we could have also performed this step using a dict object with compatible properties. To calculate histograms of arrays of images by using the OpenCV function cv::calcHist. Sep 30, 2021 · Step 3 – Getting RGB Histograms for Images. OpenCV has a function to do this, cv2. This is ideal for single-channel histograms and can be extended to multi-channel histograms by repeating the process for each channel and using matplotlib to plot them. com Apr 29, 2021 · I am new to Histogram comparisons. It’s a technique for adjusting the pixel values in an image to enhance the contrast by making those Feb 14, 2015 · Using timeit, 'image_histogram_equalization' in Trilarion's answer has a mean execution time was 0. equalizeHist(img) res = np. In Matplotlib, we use the hist() function to create histograms. Here is an example of noise estimation using Opencv: import cv2. (Both methods increase the contrast of the images. Histogram plots are a great way to visualize distributions of data - In a histogram, each bar Add this topic to your repo. For example, an RGB image is a combined set of three individual 2-D pixel arrays that are interpreted as red, green, and blue color components. py <source_image> <ref_image> [<mask_image>] For example (put this command all on one line): Mar 25, 2019 · Histogram Equalization is one of the fundamental tools in the image processing toolkit. 6). Xbins instance and defined the bin size we want as a parameter of that instance. Increment a counter corresponding to each gray level. Constructing histograms with NumPy to summarize the underlying data. imread("photo. calcHist (). template: np. The results can be striking, especially for grayscale images. The following code was found here. addWeighted () function, which allows you to adjust the brightness by adding a scalar value to each pixel in the image, and the contrast by scaling the pixel values. Application to Image Search Engines The histogram is returned as a list of pixel counts, one for each pixel value in the source image. Histogram equalization is a technique used to enhance the contrast of an image by adjusting the distribution of pixel intensities. Histogram matching can be used as a lightweight normalisation Mar 14, 2024 · We now use the function np. Morphological Filtering. The hist() function will use an array of numbers to create a histogram, the array is sent into the function as an argument. flip(image, 2) # show the image. Face detection using a cascade classifier. The result was impressive with a 0. However this implementation also relies on skimage. Aug 18, 2020 · Histogram Equalization is an image processing technique that adjusts the contrast of an image by using its histogram. import matplotlib. Jan 8, 2013 · For color image, you can pass [0], [1] or [2] to calculate histogram of blue, green or red channel respectively. Note: This implementation demonstrates how to plot a histogram in Python using Matplotlib, utilizing a sample dataset from the Seaborn library. histogram () etc. Histogram calculates the frequency of values in an array within bins determined by min, max, and bins. 3. A histogram is used to represent the spread of your data. Obtain the size of the image. In OpenCV, you can perform histogram equalization using the cv2. imread () method, the image read is in BGR format. (Remember, for 1D histogram, we converted from BGR to Grayscale). In order to improve the contrast of a color image, we need to first plot the histogram of a color image. 1 . 3. It is a most excellent enhancement to the standard Python prompt, and it ties in especially well with Matplotlib. source: np. #!/usr/bin/env python. This method uses numpy. cvtColor(image, cv2. spatial import distance as dist import matplotlib. This chapter describes how to use scikit-image on various image processing tasks, and insists on the link Dec 16, 2019 · Then put that file, as well as your source, reference, and mask images all in the same directory (or folder) in your computer. misc import face. mu = 100 # mean of distribution. In the code above, we set the xbins parameter in the go. matplotlib provides the hist method which is used to draw the histogram on specified data. The x-axis of the graph represents the class interval, and the y-axis shows the various frequencies corresponding to different class intervals. To find histogram of full image, it is given as "None". zeros((300, HOG, also known as Histogram of Oriented Gradients, is a feature descriptor similar to the Canny Edge Detector, SIFT (Scale Invariant and Feature Transform). # example data. histogram to compute the histogram of our image which, after all, is a NumPy array: PYTHON. To associate your repository with the histogram-equalization topic, visit your repo's landing page and select "manage topics. Create Histogram. From there, open a shell and execute the following command: $ python adaptive_equalization. This transform flattens the gray-level histogram so that all intensities are as equally common as possible. In a histogram data is grouped into continuous number ranges and each range corresponds to a vertical bar. 2D histograms. Dec 28, 2015 · Adjust the pixel values of a grayscale image such that its histogram. Jan 3, 2023 · Python OpenCV – cv2. The histogram is computed over the flattened array. Here is an example of how to adjust the This combined cell-level 1-D histogram forms the basic “orientation histogram” representation. Arguments: -----------. The method is useful in images with backgrounds and foregrounds that are both bright or both dark. def hist_eq(image): Here is a Python script to load an image in grayscale instead of full color, and then create and display the corresponding histogram. mask ndarray of bools or 0s and 1s, optional Scikit-image: image processing — Scipy lecture notes. Image to transform; the histogram is computed over the flattened. Learn how to implement it with OpenCV-Python and see the applications and examples. This hist function takes a number of arguments, the key one being the bins argument, which specifies the number of equal-width bins in the range. histogram(a, bins=10, range=None, density=None, weights=None) [source] #. In this video on OpenCV Python Tutorial For Beginners, I am going to show How to use image Histograms using OpenCV Python. The following example illustrates the importance of the bins argument. Each orientation histogram divides the gradient angle range into a fixed number of predetermined bins. Histograms are frequency distribution of these intensity values that occur in an image. My code for the same is: hist1 = cv2. Dec 6, 2016 · Visualizing Histogram of Oriented Gradients. import sys. Nov 21, 2017 · The equalize_image() function equalizes the image by interpolating from the normal pixel range (which is range(0,256)) to your cumulative distribution function. mask : mask image. Author: Emmanuelle Gouillart. Horizontal axis displays the number range. On dCode, this work is done automatically, upload an image file (JPG, PNG, etc. Here's how you could use it: new_images = sitk. Jun 3, 2024 · A histogram is a graphical representation of the frequency distribution of continuous series using rectangles. Dec 26, 2018 · plt. The histogram is the summary table of these values, which can then be displayed in graphic form. py --image images/boston. The transform function is a cumulative distribution function (cdf) of the pixel values in the image (normalized to map the range of pixel values to the desired range). jpg',0) equ = cv2. The labels and index keywords can limit the scope of the histogram to specified sub-regions within the array. from skimage import exposure. For simplicity we use NumPy to randomly generate an array with 250 values, where the values will concentrate around 170, and the standard Jan 4, 2023 · Histogram equalization accomplishes this by effectively spreading out the most frequent intensity values. calcHist (), np. Tip! If you’re working in the Jupyter environment, be sure to include the %matplotlib inline Jupyter magic to Feb 15, 2023 · There are several ways to adjust the brightness and contrast of an image using OpenCV and Python. 0+. For python 3. waitKey(0) But after this I need to convert the image Jun 22, 2020 · To create a histogram in Python using Matplotlib, you can use the hist() function. You will see these functions : cv. The image histogram describes an image by its intensity distribution. code for plotting the histogram on the plane: plt. (I will show an example later. h(i) = the number of pixels in I(image) with the intensity value i. It is a very robust and straightforward package that is widely used in data science for visualization purposes. hist(x) Now combine the whole program: #important library to show the image. For all the intensity levels rk= 0 to 255. ndarray. Matplotlib is one of the most widely used data visualization libraries in Python. title("HIstogramm for given Image' ") plt. This post will give you an OpenCV histogram example, from start to finish. png',res) So now you can take different images with different light conditions, equalize it and check the results. Plotting the resulting histogram with Matplotlib, pandas, and Seaborn. * Generate a grayscale histogram for an image. Compare the histogram of the base image with respect to the 2 test histograms, the histogram of the lower half base image and with the same base image histogram. LogNorm instance to the norm keyword argument. You can now change the size and orientation of an image. Input data. To enhance the image’s contrast, it spreads out the most frequent pixel For example, take the image below — it was transformed using the exact same algorithm, however, you can see that it didn’t enhance the photo as much as it utterly destroyed it: Histogram equalization isn’t always the perfect tool for the job. from PIL import Image, ImageDraw. xlabel("Value") plt. pyplot as plt. In essence, what we do is first convert the image to greyscale. ) Nov 1, 2019 · Images are stored as pixels values, each pixel value represents a color intensity value. Feb 28, 2024 · OpenCV’s calcHist allows for flexible histogram computation by specifying the image, channels, mask, histo size, and ranges. In your case call to function should look like: normalize(src_image, dst_image, 0, 65535, NORM_MINMAX); if you are trying to improve contrast of image, first try normalization and only if this is not working try equalization. In the next section, we will implement the above steps using some Python libraries such as CV2, matplotlib and numpy. The image object is mentioned in Mar 13, 2023 · Introduction. Many things can be added to a histogram such as a fit line, labels and so on. Now, let’s take a look at the image Histogram for the image shown at starting of the article. mask: mask image. Syntax: numpy. numpy. Traverse all the rows ‘m’ and columns ‘n’. Axes. It is useful for avoiding the over-plotted scatterplots. Its input is just grayscale image and output is our histogram equalized image. # create the histogram histogram, bin_edges = np. Below is the code i tried: import cv2 import numpy as np import time img = cv2. 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. Visual image comparison. This example enhances an image with low contrast, using a method called local histogram equalization, which spreads out the most frequent intensity values in an image. From simple to complex visualizations, it's the go-to library for most. Vertical axis (frequency) represents See full list on pyimagesearch. # import the necessary packages from scipy. 4. For color image, you can pass [0],[1] or [2] to calculate histogram of blue,green or red channel, respectively. Tip! If you’re working in the Jupyter environment, be sure to include the %matplotlib inline Jupyter magic to Jul 12, 2024 · Generate 1 image that is the lower half of the base image; Convert the images to HSV format; Calculate the H-S histogram for all the images and normalize them in order to compare them. py <fiilename>. Accordingly, this technique can’t guarantee to always improve the quality of the May 25, 2023 · It is possible to display the image histogram in Python in different ways. rgb_image = np. The code below creates a more advanced histogram. OpenCV doesn't have any function for contrast stretching and google yields the same result because histogram equalization does stretch the histogram horizontally but its just the difference of the transformation function. In the next section, you’ll learn about different types of images in the Python Pillow library. For 2D histograms, its parameters will be modified as follows: Jan 8, 2013 · Generate 1 image that is the lower half of the base image; Convert the images to HSV format; Calculate the H-S histogram for all the images and normalize them in order to compare them. Jul 13, 2024 · In this tutorial you will learn: 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? It is a graphical representation of the intensity distribution of an image. imread('wiki. This Use the OpenCV function cv::split to divide an image into its correspondent planes. but in this program Pillow and Numpy module were used. png. The bins, range, density, and weights parameters are forwarded to numpy. Getting Ready. histogram(plant_seedling, bins=256, range=(0, 1)) The parameter bins determines the number of “bins” to use for the histogram. ArgumentParser () ap. hist (density = True ) plt . By using NumPy to calculate histograms, you can easily calculate and access the frequencies (relative or absolute) of different values. We have explained the DataFrame. pyplot as plt import numpy as np import argparse import glob import cv2 # construct the argument parser and parse the arguments ap = argparse. min, max int. Scikit-image: image processing ¶. The HOG descriptor of an image patch is usually visualized by plotting the 9×1 normalized histograms in the 8×8 cells. imshow(rgb_image) # convert to a vector. 99 %, however I think that the result resulted in 99% because of the background color. Using the Matplotlib library in Python, we can create many types of histograms. In this tutorial, we'll take a look at how to plot a histogram plot in Matplotlib. Estimate anisotropy in a 3D microscopy image. Once you have done that, run the code using the following command (note: mask image is optional): python histogram_matching. calcHist([image],[0],None,[256],[0,256]) We will add this to a function called build_histogram that will take our image array image and a number of bins and build a histogram for us. Can someone tell me how can I ignore the white color and compare the actual fruit. In this tutorial, we covered how to use the in-built Pandas function DataFrame. This is the pyplot wrapper for axes. nbins int, optional. Transformation function transfers the pixel intensity levels from the May 28, 2024 · Essentially, it summarises discrete or continuous data. Plot histograms, using OpenCV and Matplotlib functions. The following sample code displays the histogram of each individual RGB channel as well as the histogram with the three 5 days ago · For color image, you can pass [0], [1] or [2] to calculate histogram of blue, green or red channel respectively. show () In this example, the density=True argument ensures that the area under the histogram sums up to 1, effectively giving us a probability density function. jpg') h = np. . Histogram equalization is good when histogram of the image is confined to a particular region. You will notice that dominant direction of the histogram captures the shape of the person, especially around the torso and legs. calcHist method. Python OpenCV – Histogram Equalization. However, if we want to get histogram of Dec 30, 2020 · Adjusted Images. Sep 23, 2022 · In this tutorial, you’ll learn how to use the NumPy histogram function to calculate a histogram of a given dataset. See image on the side. plt. Feb 1, 2024 · Using graphs to graphically represent the findings is a very important step in data analysis. Histogram instance to a go. In the confined area of a picture, the method counts instances of gradient orientation. Start IPython either directly at a shell, or with the Jupyter Notebook (where IPython as a running kernel). Before diving into our first example, let’s state that we’ll consider an image to be a matrix or matrices of pixels. show(). Parameters: input array_like. By simply examining the histogram of an image, you get a general understanding regarding the contrast, brightness, and intensity distribution. A complete matplotlib python histogram. In this section, the histogram was calculated by implementation of python programming code (Python 3. We can define the histogram of an image as a 2D bar plot. Rendering the histogram with a logarithmic color scale is accomplished by passing a colors. A histogram is a two-dimensional diagram in which the width of the rectangles shows the 2 days ago · Learn to. The Matplotlib module is a comprehensive Python module for creating static and interactive plots. image as mpimg. Compute the histogram of a dataset. Dec 7, 2017 · A combination of multiple monochrome images results in a color image. skimage. Description: On the X axis, I have the values from 0-255, that each pixel ranges from, and on Y axis, I have the number of pixels that have that particular X value. Histogram is a tool for visualising the distribution of data across a continuous interval or period. " GitHub is where people build software. Bands and Modes of an Image in the Python Pillow Library. imread('zzz. X/OpenCV 3. from scipy. For color histograms, we need to convert the image from BGR to HSV. data)); The first input is the image you want to process, the second input defines the block size and It the index of channel for which we calculate histogram. Render text onto an image. Minimum and maximum values of range of histogram The histogram for any image acts as the graphical representation of the distribution of the intensity of the image. To find histogram of full image, it is set as None. This example uses image 4 (im4). histogram () function which represents the frequency of data distribution in the graphical form. However the glaring brightness of the bulbs are still very evident. I need to do a histogram equalization for a colored image. equalizeHist() function. binsint or sequence of scalars or str, optional. exposure. Excellent! We see that the image has improved greatly. Feb 12, 2014 · but image normalization in OpenCV is not limited to 8 bit data. For example, if input is grayscale image, its value is [0]. One common way of handling lighting issues is through Histogram Manipulation. Python Code to Divide Image into Blocks Building histograms in pure Python, without use of third party libraries. Algorithm Mar 25, 2017 · This processes distinct blocks in your image and applies some function to it. We’ll use matplotlib to plot our histograms so we can visualize them before and after histogram matching is applied. When we read the image using cv2. mlab as mlab. Similar to before, we will import OpenCV and our helper function to display images in Jupyter lab. calcHist () function to calculate the image histograms. Image tutorial# A short tutorial on plotting images with Matplotlib. Data for which to calculate histogram. Template image; can have different dimensions to source. img = cv2. Read the image. Jul 3, 2024 · Line 25: Finally, we display the histogram plot using plt. 6, There are a lot of common modules using in image processing such as Pillow, Numpy, OpenCV, etc. The fourth stage computes normalisation Longer examples and demonstrations #. 38. 2D histograms are useful when you need to analyse the relationship between 2 numerical variables that have a huge number of values. Apr 10, 2019 · Histogram matching is a technique that modifies the intensity distribution of an image to match a desired histogram. SimpleITK does have an AdaptiveHistogramEqualization function, and it does work on float32 images. Plot the graph of intensity values versus number of pixels in each intensity value. It serves the aim of object detection in computer vision and image processing. histogram. What is Histogram Equalization? It is a method that improves the contrast in an image, in order to stretch out the intensity range (see also the corresponding Wikipedia entry ). Count the number of pixels for each intensity level. ) and click on Analyze. Number of bins for image histogram. It quantifies the number of pixels for each intensity value considered. """. Sep 18, 2018 · Computing the histogram. add_argument ("-d", "--dataset Oct 15, 2020 · For ease of use, if the input image of the generate_histogram function is a color image, we first convert to a grayscale image(see line# 6). Feb 1, 2021 · Let’s now apply adaptive histogram equalization with OpenCV! Access the “Downloads” section of this tutorial to retrieve the source code and example images. Iterate over each pixel in the image and calculate the gray level of the pixel. An image is a two-dimensional array of pixels, where each pixel corresponds to a color. Note. An image histogram is a graph of pixel intensity (on the x-axis) versus number of pixels (on the y-axis). As a consequence, pixels can achieve values between 0 and 255 ( 2 8 = 256). To normalize an array by using the function cv::normalize. imread(raw_input('Please enter the name of your image:'),0) #The ',0' makes it read the image as a grayscale image. In order to get RGB histograms we would be using the cakHist function which requires a number of parameters including the image object, the bin count, the range of values needed, and the channel ( blue, red, or green ). jpg") image = cv2. If the data has already been binned and counted, use bar or stairs to plot the distribution: counts Jun 22, 2020 · To create a histogram in Python using Matplotlib, you can use the hist() function. May 22, 2023 · patches :This returns the list of individual patches used to create the histogram. [ ] Feb 22, 2012 · I was just trying to draw histogram using new OpenCV Python interface ( cv2 ). You can explicitly tell how many bins you want for the X and the Y axis. Jan 8, 2013 · 2D Histogram in OpenCV. equalize_hist (image, nbins = 256, mask = None) [source] # Return image after histogram equalization. imshow("equalizeHist", image) cv2. In Python, you can use the Matplotlib library to plot histograms with the help of the pyplot hist function. To make it clearer, from the image above, you can see that the pixels seem clustered around the middle of the available range of intensities. A histogram shows the frequency of numerical data in bins of grouped ranges. hist() to plot a histogram in Python. pie(x, bins) In the above Python matplotlib pyplot histogram syntax, x represents the numeric data that you want to use in the Y-Axis, and bins will use in the X-Axis. In the last tutorial ( Histogram Equalization) we talked about a particular kind of histogram called Image Dec 21, 2020 · The above image has some clear lighting issues, but we should be able to correct this using the power of Python. hist() function in easy words with examples. 7 and OpenCV 2. The horizontal axis represents the pixel intensities. hist (data,color=”value”) Example: As per the above steps, First imported the required modules, and next we loaded an image using imread () method and using calcHist () method to get the RGB colors from Jun 24, 2022 · 1. histogram to bin the data in x and count the number of values in each bin, then draws the distribution either as a BarContainer or Polygon. The image histogram for each intensity value considered quantifies the number of Jan 28, 2020 · 2. Here are some examples: Jul 21, 2019 · The simplest technique used for estimating the noise of a image is by finding the most smooth part of the image, find histogram of that part and estimate noise distribution of the whole image based on the part. 3696 seconds, while this function has a mean execution time of 0. Data type uint8 (which is mostly used one) represents that each pixel is represented using 8 bits. Let us see a few examples to better understand the functionality of hist() function. Each pixel can be represented by one or more Sep 11, 2021 · Different from before, as we will have 3-4 channels in a color image, we need to adapt our approach slightly. It is quite simple and calculated using the same function, cv. The histogram plots the number of pixels according to the intensity values. One common method is to use the cv2. hist2d. The gradient magnitudes of the pixels in the cell are used to vote into the orientation histogram. * Usage: python GrayscaleHistogram. ylabel("pixels Frequency") #hist function is used to plot the histogram of an image. *. See its description here. Histograms Organize data into gro Aug 16, 2023 · Here's an example of how to plot a normalized histogram: # Plot a normalized histogram df [ 'values1' ]. The first few lines are: """. hstack((img,equ)) #stacking images side-by-side cv2. Currently hist2d calculates its own axis limits, and any limits previously set are ignored. I have B,G,R histograms that look like the following: Image Histogram for B channel of an image. The image object is mentioned in Feb 8, 2021 · We need scikit-image’s exposure library to compute image histograms, cumulative distribution functions, and apply histogram matching. Assuming your histogram equalization function is called hsteq, you would simply do this: rows = 100; cols = 100; out = blockproc (im, [rows, cols], @ (s) hsteq (s. If you wanted to do it on a slice-by-slice basis, it'd look something like this: 14. We pass in 256 because we want to see the pixel Use the OpenCV function cv::split to divide an image into its correspondent planes. 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 Mar 4, 2014 · You can use newer OpenCV python interface which natively uses numpy arrays and plot the histogram of the pixel intensities using matplotlib hist. Counts are grouped into 256 bins for each band, even if the image has more than 8 bits per band. How to equalize an image histogram? Histogram equalization is commonly used in order to enhance the contrast of the image. 0534 seconds. pyplot. If the images have multiple channels, the matching is done independently for each channel, as long as the number of channels is equal in the input image and the reference. To this end let us explore alternative ways to adjust the histogram of images. Interact with 3D images (of kidney tissue) Use pixel graphs to find an object's geodesic center. ) Jan 22, 2014 · OpenCV and Python versions: This example will run on Python 2. imwrite('res. We could apply it to calculate the histogram of the constituent color channels (blue, green, and red) of the image. Following these steps lets you visualize the data distribution and gain insights into its characteristics. bar(bins, hist) Another option is using matplotlib plt. For example, if i = 0, the h (0) is the number of pixels with a value of 0. It takes less than second on my computer. The local version [ 2] of the histogram equalization emphasized every Feb 28, 2024 · Feature Extraction: These histograms can be further used for analyzing the image data and classification tasks. Find histograms, using both OpenCV and Numpy functions. It manipulates the pixels of an input image so that its histogram matches the histogram of the reference image. matplotlib. AdaptiveHistogramEqualization(images) Note that this would do equalization across the whole 3d image. Example 1: Feb 2, 2024 · Create a Normalized Histogram Using the Matplotlib Library in Python. First I convert the colored image to gray and give it to the equalizeHist function: image = cv2. The code for the same is mentioned below. equalizeHist (). We will add this to a function called build_histogram that will take our image array image and a number of bins and build a histogram for us. equalizeHist(image) cv2. scikit-image is a Python package dedicated to image processing, and using natively NumPy arrays as image objects. Let m=rows and n=columns. In the case of a grayscale image, this Sep 30, 2021 · Step 3 – Getting RGB Histograms for Images. Matplotlib can be used to create a normalized histogram. Syntax: matplotlib. Parameters: image array. Here’s an example: Jul 14, 2014 · 3 Ways to Compare Histograms Using OpenCV and Python. The hist syntax to draw a histogram is. ec ud kc oo ib gp rb va yl ri