Detect rectangular focus on picture

edge_detection.py

import numpy as np
import imutils

try:
    import cv2
except ImportError:
    from cv2 import cv2


def order_points(pts):
    rect = np.zeros((4, 2), dtype="float32")
    s = pts.sum(axis=1)
    rect[0] = pts[np.argmin(s)]
    rect[2] = pts[np.argmax(s)]

    diff = np.diff(pts, axis=1)
    rect[1] = pts[np.argmin(diff)]
    rect[3] = pts[np.argmax(diff)]

    return rect


def four_point_transform(img, pts):
    rect = order_points(pts)
    (tl, tr, br, bl) = rect

    width_a = np.sqrt(((br[0] - bl[0]) ** 2) + ((br[1] - bl[1]) ** 2))
    width_b = np.sqrt(((tr[0] - tl[0]) ** 2) + ((tr[1] - tl[1]) ** 2))
    max_width = max(int(width_a), int(width_b))

    height_a = np.sqrt(((tr[0] - br[0]) ** 2) + ((tr[1] - br[1]) ** 2))
    height_b = np.sqrt(((tl[0] - bl[0]) ** 2) + ((tl[1] - bl[1]) ** 2))
    max_height = max(int(height_a), int(height_b))

    dst = np.array([
        [0, 0],
        [max_width - 1, 0],
        [max_width - 1, max_height - 1],
        [0, max_height - 1]], dtype="float32")

    matrix = cv2.getPerspectiveTransform(rect, dst)
    warped = cv2.warpPerspective(img, matrix, (max_width, max_height))

    return warped


def main():
    img = cv2.imread("cni_2.jpg")
    shape = np.shape(img)
    ratio = shape[0] / shape[1]

    height = 500
    width = int(float(height) / ratio)

    img = cv2.resize(img, (height, width), interpolation=cv2.INTER_AREA)

    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    gray = cv2.GaussianBlur(gray, (5, 5), 0)
    edged = cv2.Canny(gray, 75, 200)

    print("STEP 1: Edge Detection")
    cv2.imshow("Image", img)
    cv2.imshow("Edged", edged)

    cnts = cv2.findContours(edged, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
    cnts = imutils.grab_contours(cnts)
    cnts = sorted(cnts, key=cv2.contourArea, reverse=True)[:5]
    
    screen_cnt = None

    for c in cnts:
        peri = cv2.arcLength(c, True)
        approx = cv2.approxPolyDP(c, 0.02 * peri, True)
        print(len(approx))
        if len(approx) == 4:
            screen_cnt = approx

    print("STEP 2: Find contours of card")
    if screen_cnt is not None:
        cv2.drawContours(img, [screen_cnt], -1, (0, 255, 0), 2)
        cv2.imshow("Outline", img)
        warped = four_point_transform(img, screen_cnt.reshape(4, 2) * ratio)
        cv2.imshow("Warped", warped)
    else:
        print("Cannot find contours")

    
    cv2.waitKey(0)
    cv2.destroyAllWindows()


main()