transformations.py

import cv2 as cv
import numpy as np

img = cv.imread("./Resources/Photos/park.jpg")
cv.imshow("Cat", img)

# translation
def translate(img, x, y):
    transMat = np.float32([[1, 0 , x], [0, 1, y]])
    print(transMat)
    dimensions = (img.shape[1], img.shape[0])
    return cv.warpAffine(img, transMat, dimensions)

# -x --> Left
# -y --> Up
# x --> Right
# y --> Down

translated = translate(img, -100, 100)
cv.imshow('Translated', translated)


def rotate(img, angle, rotPoint=None):
    (height, width)= img.shape[:2]
    if rotPoint is None:
        rotPoint = (width//2, height//2)
    
    rotMat = cv.getRotationMatrix2D(rotPoint, angle, 1)
    dimensions= (width, height)
    return cv.warpAffine(img, rotMat, dimensions)
     
rotated = rotate(img, -45)
cv.imshow('Rotated', rotated)

rotated_rotated = rotate(rotated, -45)
cv.imshow('Rotated Rotated', rotated_rotated)

# Resizing
resized = cv.resize(img, (500,500), interpolation=cv.INTER_CUBIC)
cv.imshow('Resized', resized)

# Flipping
flip = cv.flip(img, -1)
cv.imshow('Flip', flip)

# Cropping
cropped = img[200:400, 300:400]
cv.imshow('Cropped', cropped)

# we can get the matrix of affine transform using points from the image and the transformed image using getAffineTransform
 




cv.waitKey(0)