diff --git a/Image_Processing/src/get_perspective/README.md b/Image_Processing/src/get_perspective/README.md
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+# Perspective Transform
+using OpenCV methods
+## How It Works
+On selecting dimensions for a quadrilateral section, the code finds the maximum height and width of that selection and warps the selected area into a rectangle of dimensions `maxHeight * maxWidth`
+## Usage
+`python3 script.py --path image.jpg`
+
+- It opens the image for you need to select coordinates in clockwise manner
+ (top left -> top right -> bottom right -> bottom left).<br><br>
+<img src = "https://drive.google.com/u/0/uc?id=1-ojbLqqCncITEmPw80TU_mTqJCOZvL-I&export=download"/><br><br>
+- on pressing enter, it transforms the document.<br><br>
+<img src = "https://drive.google.com/u/0/uc?id=102QeYDxNEw8-vYaBniKexzlXw_-WkL-I&export=download"/>
diff --git a/Image_Processing/src/get_perspective/img.jpg b/Image_Processing/src/get_perspective/img.jpg
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diff --git a/Image_Processing/src/get_perspective/script.py b/Image_Processing/src/get_perspective/script.py
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+import cv2
+import numpy as np
+import argparse
+
+# global vars
+arr = []
+count = 0
+
+# setup argparse
+parser = argparse.ArgumentParser()
+parser.add_argument("-p", "--path", help = "path to image")
+args = vars(parser.parse_args())
+
+# transform image to perspective form using warpPerspective
+def transform(img, arr):
+       (tl, tr, br, bl) = arr
+
+       # find the maximum width of selected object
+       widthA = np.sqrt(((br[0] - bl[0]) ** 2) + ((br[1] - bl[1]) ** 2))
+       widthB = np.sqrt(((tr[0] - tl[0]) ** 2) + ((tr[1] - tl[1]) ** 2))
+       w = max(int(widthA), int(widthB))
+
+       # find the maximum height of selected object
+       heightA = np.sqrt(((tr[0] - br[0]) ** 2) + ((tr[1] - br[1]) ** 2))
+       heightB = np.sqrt(((tl[0] - bl[0]) ** 2) + ((tl[1] - bl[1]) ** 2))
+       h = max(int(heightA), int(heightB))
+
+       print("New Image Dimensions: \nWidth = {}\nHeight = {}".format(w,h))
+       # Create source and destination points
+       inp_pts = np.float32(arr)
+       op_pts = np.float32([[0,0],[w-1,0],[w-1,h-1],[0,h-1]])
+
+       # Create Perspective Transform and perform warp Perspective
+       M = cv2.getPerspectiveTransform(inp_pts,op_pts)
+       out = cv2.warpPerspective(img, M, (w, h))
+
+       return out
+
+# read image
+img = cv2.imread(args["path"])
+
+# resize image
+width = 500
+height = int((img.shape[0] * 500)/(img.shape[1]))
+dim = (width, height)
+img = cv2.resize(img, dim, interpolation = cv2.INTER_AREA)
+
+cv2.imshow('image', img)
+
+# helper function to append coordinates
+def points(x,y):
+    if len(arr) <= 4:
+        arr.append((x,y))
+    return len(arr)
+
+# helper function to draw connector lines
+def draw(count, img):
+    if(count == 2):
+        cv2.line(img, arr[0], arr[1], (255,255,255), 2)
+    if(count == 3):
+           cv2.line(img, arr[1], arr[2], (255,255,255), 2)
+    if(count == 4):
+           cv2.line(img, arr[2], arr[3], (255,255,255), 2)
+           cv2.line(img, arr[3], arr[0], (255,255,255), 2)
+
+# mouseclick events
+def onClick(event, x, y, flags, param):
+    if event == cv2.EVENT_LBUTTONDOWN:
+        count = points(x,y)
+        if count <= 4:
+            cv2.circle(img, (x,y), 2, (255,255,0), 10)
+            draw(count, img)
+        cv2.imshow('image', img)
+
+cv2.setMouseCallback('image', onClick)
+cv2.waitKey(0)
+
+# transform image with mentioned coordinates
+out = transform(img, arr)
+
+cv2.imshow('final', out)
+cv2.waitKey(0)
+cv2.destroyAllWindows()