In this program, we will draw a filled polygon using the opencv function fillPoly(). The function takes in an image and the endpoints of the polygon.AlgorithmStep 1: Import cv2 and numpy. Step 2: Define the endpoints. Step 3: Define the image using zeros. Step 4: Draw the polygon using the fillpoly() function. Step 5: Display the output.Example Codeimport cv2 import numpy as np contours = np.array([[50,50], [50,150], [150,150], [150,50]]) image = np.zeros((200,200)) cv2.fillPoly(image, pts = [contours], color =(255,255,255)) cv2.imshow("filledPolygon", image)Output

In this article, we will draw a circle on an image using the OpenCV function circle().Original ImageAlgorithmStep 1: Import OpenCV. Step 2: Define the radius of circle. Step 3: Define the center coordinates of the circle. Step 4: Define the color of the circle. Step 5: Define the thickness. Step 6: Pass the above arguments into cv2.circle() along with the image. Step 7: Display the output.Example Codeimport cv2 image = cv2.imread('testimage.jpg') radius = 100 center = (350, 175) color = (255,255,0) thickness = 15 image = cv2.circle(image, center, radius, color, thickness) cv2.imshow('Circle', image)Output

In this program, we will draw a rectangle using the OpenCV function rectangle(). This function takes some parameters like starting coordinates, ending coordinates, color and thickness and the image itself.Original ImageAlgorithmStep 1: Import cv2. Step 2: Read the image using imread(). Step 3: Define the starting coordinates. Step 5: Define the ending coordinates. Step 6: Define the color and the thickness. Step 7: Draw the rectangle using the cv2.reactangle() function. Step 8: Display the rectangle.Example Codeimport cv2 image = cv2.imread('testimage.jpg') height, width, channels = image.shape start_point = (0, 0) end_point = (width, height) color = (0, 0, 255) thickness ... Read More

Using Pandas, we can create a dataframe and can create a figure and axes variable using subplot() method. After that, we can use the ax.scatter() method to get the required plot.StepsMake a list of the number of students.Make a list of marks that have been obtained by the students.To represent the color of each scattered point, we can have a list of colors.Using Pandas, we can have a list representing the axes of the data frame.Create fig and ax variables using subplots method, where default nrows and ncols are 1.Set the “Students count” label using plt.xlabel() method.Set the “Obtained marks” ... Read More

To prevent scientific notation, we must pass style='plain' in the ticklabel_format method.StepsPass two lists to draw a line using plot() method.Using ticklabel_format() method with style='plain'. If a parameter is not set, the corresponding property of the formatter is left unchanged. Style='plain' turns off scientific notation.To show the figure, use plt.show() method.Examplefrom matplotlib import pyplot as plt plt.plot([1, 2, 3, 4, 5], [11, 12, 13, 14, 15]) plt.ticklabel_format(style='plain')    # to prevent scientific notation. plt.show()Output

Using plt.legend() method, we can create a legend, and passing frameon would help to keep the border over there.StepsSet the X-axis label using plt.xlabel() method.Set the Y-axis label using plt.ylabel() method.Draw lines using plot() method.Location and legend drawn flags can help to find a location and make the flag True for the border.Set the legend with “blue” and “orange” elements.To show the figure use plt.show() method.Exampleimport matplotlib.pyplot as plt plt.ylabel("Y-axis ") plt.xlabel("X-axis ") plt.plot([9, 5], [2, 5], [4, 7, 8]) location = 0 # For the best location legend_drawn_flag = True plt.legend(["blue", "orange"], loc=0, frameon=legend_drawn_flag) plt.show()OutputRead More

In this program, we will draw an ellipse on an image in using the OpenCV library. We will use the OpenCV function ellipse() for the same.Original ImageAlgorithmStep 1: Import cv2. Step 2: Read the image using imread(). Step 3: Set the center coordinates. Step 4: Set the axes length. Step 5: Set the angle. Step 6: Set start and end angle. Step 6: Set the color. Step 7: Set the thickness. Step 8: Draw the ellipse by passing the above parameters in the cv2.ellipse function along with the original image. Step 9: Display the final output.Example Codeimport cv2 image = ... Read More

In this program, we will draw a simple line on an image using the OpenCV function line().Original ImageAlgorithmStep 1: Import cv2. Step 2: Read the image using imread(). Step 3: Get the dimensions of the image using the image.shape method. Step 4: Define starting point of the line. Step 5: Define the end point of the line. Step 6: Define the thickness of the line. Step 7: Draw the line using the cv2.line() function and pass Step 3 to Step 4 as parameters.Example Codeimport cv2 image = cv2.imread('testimage.jpg') height, width, channels = image.shape startpoint = (0, 0) endpoint = ... Read More

In this program, we will change the color scheme of an image from rgb to grayscaleAlgorithmStep 1: Import OpenCV. Step 2: Read the original image using imread(). Step 3: Convert to grayscale using cv2.cvtcolor() function.Example Codeimport cv2 image = cv2.imread('colourful.jpg') cv2.imshow('Original',image) grayscale = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) cv2.imshow('Grayscale', grayscale)OutputOriginal Image:Grayscale Image:

To find the sum of every n values in R data frame columns if there exist missing values, we can use rowsum function along with rep function that will repeat the sum for rows and na.rm=TRUE to exclude the rows with missing values. For example, if we have a data frame called df that contains 4 columns each containing twenty values with some missing values then we can find the row sums for every 5 rows by using the command rowsum(df,rep(1:5,each=4),na.rm=TRUE).Example Live Demox1