我嘗試檢測下圖中的黃線，但陰影遮住了黃色道路。我們有什么方法可以處理嗎？編碼如下：import cv2import numpy as npimage = cv2.imread('Road.jpg')hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)low_yellow = np.array([18, 94, 140])up_yellow = np.array([48, 255, 255])mask = cv2.inRange(hsv, low_yellow, up_yellow)edges = cv2.Canny(mask, 75, 150)lines = cv2.HoughLinesP(edges, 1, np.pi / 180, 50, maxLineGap=250)for line in lines:? x1, y1, x2, y2 = line[0]? cv2.line(image, (x1, y1), (x2, y2), (0, 255, 0), 5)? # cv2.imshow('image', img)? cv2.imwrite("result.jpg", edges)
1 回答
幕布斯6054654
TA貢獻1876條經(jīng)驗 獲得超7個贊
這是轉(zhuǎn)換為實驗室和自動閾值的代碼您必須使用適當(dāng)?shù)姆椒z測線條。一種高級解決方案是訓(xùn)練數(shù)據(jù)集進行分割（神經(jīng)網(wǎng)絡(luò) Ex：Unet）
import cv2
import numpy as np
img = cv2.imread('YourImagePath.jpg')
cv2.imshow("Original", img)
k = cv2.waitKey(0)
# Convert To lab
lab = cv2.cvtColor(img, cv2.COLOR_BGR2LAB)
# display b channel
cv2.imshow("Lab", lab[:, :, 2])
k = cv2.waitKey(0)
# auto threshold using Otsu
ret , mask = cv2.threshold(lab[:, :, 2] , 0 , 255 , cv2.THRESH_BINARY+
cv2.THRESH_OTSU)
#display Binary
cv2.imshow("Binary", mask)
k = cv2.waitKey(0)
cv2.destroyAllWindows()
輸出：
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