在Pycharm中用OpenCV的imutils模塊矯正圖片

在OpenCV中有一個imutils模塊在圖形變換中非常方便，下面就是用該模塊對圖片進行仿射變換的代碼。

from imutils import perspective
from skimage.filters import threshold_local
import cv2
import imutils
# 邊緣掃描
image = cv2.imread("C:\\Users\\lenovo\\Pictures\\t1.png")
ratio = image.shape[0] / 500.0# 比例
orig = image.copy()
image = imutils.resize(image, height = 500)
# 灰度轉換及邊緣查找
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (5, 5), 0)
edged = cv2.Canny(gray, 75, 200)                          # 邊緣檢測
# 只保留輪廓
cnts = cv2.findContours(edged.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)#通過邊緣圖像找到輪廓
cnts = cnts[0] if imutils.is_cv2() else cnts[1]
# 用以區分OpenCV2.4和OpenCV3
cnts = sorted(cnts, key = cv2.contourArea, reverse = True)[:5] # 保留最大輪廓
for c in cnts:
    peri = cv2.arcLength(c, True)
    approx = cv2.approxPolyDP(c, 0.02 * peri, True)            # 輪廓點
    if len(approx) == 4:                                       # 表明找到四個輪廓點
        screenCnt = approx
        break
# 轉為鳥瞰圖
warped = perspective.four_point_transform(orig, screenCnt.reshape(4, 2) * ratio)
warped = cv2.cvtColor(warped, cv2.COLOR_BGR2GRAY)              # 灰度轉換
T = threshold_local(warped, 11, offset = 10, method = "gaussian")
warped = (warped > T).astype("uint8") * 255
cv2.imshow("Original", imutils.resize(orig, height = 650))
cv2.imshow("Scanned", imutils.resize(warped, height = 650))
cv2.waitKey(0)

變換后的圖片如下圖所示