Created
October 9, 2016 16:04
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from imutils.perspective import four_point_transform | |
from imutils import contours | |
import numpy as np | |
import argparse | |
import imutils | |
import cv2 | |
ap = argparse.ArgumentParser() | |
ap.add_argument("-i", "--image", required = True, | |
help = 'path to the input image') | |
args = vars(ap.parse_args()) | |
ANSWER_KEY = {0: 1, 1: 4, 2: 0, 3: 3, 4: 1} | |
image = cv2.imread(args['image']) | |
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) | |
blurred = cv2.GaussianBlur(gray, (5, 5), 0) | |
edged = cv2.Canny(blurred, 75, 200) | |
cnts = cv2.findContours(edged.copy(), | |
cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) | |
cnts = cnts[0] if imutils.is_cv2() else cnts[1] | |
if len(cnts) > 0: | |
cnts = sorted(cnts, key=cv2.contourArea, reverse=True) | |
for c in cnts: | |
peri = cv2.arcLength(c, True) | |
approx = cv2.approxPolyDP(c, 0.02 * peri, True) | |
if len(approx) == 4: | |
docCnt = approx | |
break | |
paper = four_point_transform(image, docCnt.reshape(4, 2)) | |
warped = four_point_transform(gray, docCnt.reshape(4, 2)) | |
thresh = cv2.threshold(warped, 0, 255, | |
cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1] | |
cnts = cv2.findContours(thresh.copy(), | |
cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) | |
cnts = cnts[0] if imutils.is_cv2() else cnts[1] | |
questionCnts = [] | |
for c in cnts: | |
(x, y, w, h) = cv2.boundingRect(c) | |
ar = w / float(h) | |
if w >= 20 and h >= 20 and ar >= 0.9 and ar <= 1.1: | |
questionCnts.append(c) | |
questionCnts = contours.sort_contours(questionCnts, | |
method="top-to-bottom")[0] | |
correct = 0 | |
for (q, i) in enumerate(np.arange(0, len(questionCnts), 5)): | |
cnts = contours.sort_contours(questionCnts[i:i + 5])[0] | |
bubbled = None | |
for (j, c) in enumerate(cnts): | |
mask = np.zeros(thresh.shape, dtype = 'uint8') | |
cv2.drawContours(mask, [c], -1, 255, -1) | |
mask = cv2.bitwise_and(thresh, thresh, mask = mask) | |
total = cv2.countNonZero(mask) | |
if bubbled is None or total > bubbled[0]: | |
bubbled = (total, j) | |
color = (0, 0, 255) | |
k = ANSWER_KEY[q] | |
if k == bubbled[1]: | |
color = (0, 255, 0) | |
correct += 1 | |
cv2.drawContours(paper, [cnts[k]], -1, color, 3) | |
score = (correct / 5.0) * 100 | |
print("[INFO] score: {:.2f}%".format(score)) | |
cv2.putText(paper, "{:.2f}%".format(score), (10, 30), | |
cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 255), 2) | |
cv2.imshow("Original", image) | |
cv2.imshow("Exam", paper) | |
cv2.waitKey(0) |
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