Project 1

For scaling to 50% of the original image

First we take the height, width and multiply it by scaling factor.
height = height*0.5
width = width*0.5
Then we take the scaled image and resize it to half of the image.

#Importing Libraries
import cv2
import numpy as np

#Reading the image
image = cv2.imread("Ch1.png")

#Image rotation func
def image_rotation(image,angle):
    height,width = image.shape[:2]
    center = (width/2,height/2)
    rot_matrix = cv2.getRotationMatrix2D(center,angle,scale=1) #rotation matrix for 140 
                                                               #degree rotation angle
    rotated_image = cv2.warpAffine(image,rot_matrix,(width,height))
    return rotated_image

#Func for resizing it to half of the image
def scaling(image,scale):
    resized_height = int(image.shape[0] * scale / 100)
    resized_width = int(image.shape[1] * scale / 100)
    dimensions = (resized_width, resized_height)
    resized_image = cv2.resize(image, dimensions, interpolation = cv2.INTER_AREA)
    return resized_image

#ROtation Angle = 140
angle=140
rotated_image = image_rotation(image,angle)
cv2.imwrite("rotated_img.jpg",rotated_image)

#50% scale percent
scale=50
resized_img = scaling(rotated_image,scale) 
cv2.imwrite("resized_image.jpg",resized_img)

#Func for cropping the image
def crop_image(image, dimensions):
    image_dims = image.shape
    h_s,h_e,w_s,w_e = dimensions
    height_dims = [h_s,h_e]
    width_dims = [w_s,w_e]
    np.clip(height_dims,a_min=0,a_max=image_dims[0])
    np.clip(width_dims,a_min=0,a_max=image_dims[1])
    crop_img = image[height_dims[0]:height_dims[1],width_dims[0]:width_dims[1]]
    return crop_img

dimensions = [100,540,165,852]
crop = crop_image(image,dimensions)
#Saving the result
cv2.imwrite("cropped_image.jpg",crop)