Created
June 29, 2017 20:33
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| import numpy as np | |
| import argparse | |
| import glob | |
| import cv2 | |
| import json | |
| def auto_canny(image, sigma=0.33): | |
| otsu_thresh_val, ret = cv2.threshold(image, 0, 255, cv2.THRESH_BINARY|cv2.THRESH_OTSU) | |
| lower = otsu_thresh_val * 0.3 | |
| upper = otsu_thresh_val * 1 | |
| edged = cv2.Canny(image, lower, upper) | |
| return edged | |
| ap = argparse.ArgumentParser() | |
| ap.add_argument("-i", "--images", required=True, | |
| help="path to input dataset of images") | |
| args = vars(ap.parse_args()) | |
| for imagePath in glob.glob(args["images"] + "/*.jpg"): | |
| image = cv2.imread(imagePath) | |
| gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) | |
| blurred = cv2.GaussianBlur(gray, (3, 3), 0) | |
| edged = auto_canny(gray) | |
| kernel = np.ones((20, 20), np.uint8) | |
| morphed = cv2.morphologyEx(edged, cv2.MORPH_CLOSE, kernel) | |
| (_, contours, _) = cv2.findContours(morphed.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) | |
| main_contour = sorted(contours, key = cv2.contourArea, reverse = True)[0] | |
| peri = cv2.arcLength(main_contour, False) | |
| approx = cv2.approxPolyDP(main_contour, 0.0015 * peri, True) | |
| cv2.drawContours(image, [approx], -1, (0, 255, 0), 2) | |
| print(json.dumps(approx.tolist())); | |
| cv2.imshow("Result", image) | |
| cv2.waitKey(0) |
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