基於透視的圖像矯正
- 獲取圖像四個頂點
- 形成變換矩陣
- 透視變換
from imutils.perspective import four_point_transform
import imutils
import cv2
def Get_Outline(input_dir):
image = cv2.imread(input_dir)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)
edged = cv2.Canny(blurred, 75, 200)
return image, gray, edged
def Get_cnt(edged): # 輪廓檢測 獲取四角點
cnts = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if imutils.is_cv2() else cnts[1]
docCnt = None
if len(cnts) > 0:
cnts = sorted(cnts, key=cv2.contourArea, reverse=True)
for c in cnts:
peri = cv2.arcLength(c, True) # 輪廓按大小降序排序
approx = cv2.approxPolyDP(c, 0.02 * peri, True) # 獲取近似的輪廓
if len(approx) == 4: # 近似輪廓有四個頂點
docCnt = approx
break
return docCnt
if __name__ == "__main__":
input_dir = "21.png"
image, gray, edged = Get_Outline(input_dir)
docCnt = Get_cnt(edged) # 四角點
result_img = four_point_transform(image, docCnt.reshape(4, 2)) # 對原始圖像進行四點透視變換
print(docCnt)
# 圈出四角點
for peak in docCnt:
peak = peak[0]
cv2.circle(image, tuple(peak), 10, (255, 0, 0))
cv2.imshow("original", image)
cv2.imshow("gray", gray)
cv2.imshow("edged", edged)
cv2.imshow("result_img", result_img)
cv2.waitKey(0)
cv2.destroyAllWindows()