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<p>我对OpenCV(Python)还是个新手,我正在尝试<code>cv2.adaptiveThreshold()</code>在光线变化时使用网络摄像头绘制合适的轮廓。主要的问题是绘制等高线时会产生大量的噪音,所以我尝试设置一个<code>cv2.countourArea()</code>阈值,但这似乎不是最好的解决方案</p>
<p>后来,我决定尝试用一个简单的轨迹栏操纵<code>cv2.adaptiveThreshold</code>的值</p>
<p>特别是<code>blockSize</code>和<code>CValue</code>。在CValue上一切都很好,但在<code>blockSize</code>上我确实很挣扎,因为它需要是奇数。我尝试了检查<code>empty</code>回调函数的值是否为偶数并添加+1。但这似乎并不正常。稍后我很可能会使用机器学习来更改这些值,但现在我希望轨迹栏能够用于调试目的</p>
<p>使用轨迹栏操纵<code>blockSize</code>的最佳解决方案是什么</p>
<p>先谢谢你!:)</p>
<p/><div class="snippet" data-lang="js" data-hide="false" data-console="true" data-babel="false">
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<pre class="snippet-code-js lang-js prettyprint-override"><code>import cv2
import numpy as np
#####################################
winWidth = 640
winHeight = 840
brightness = 100
cap = cv2.VideoCapture(0)
cap.set(3, winWidth)
cap.set(4, winHeight)
cap.set(10, brightness)
kernel = (5, 5)
bSize_default = 1
#######################################################################
def empty(a):
pass
cv2.namedWindow("TrackBars")
cv2.resizeWindow("TrackBars", 640, 240)
cv2.createTrackbar("cVal", "TrackBars", 2, 20, empty)
def preprocessing(frame, cVal):
imgGray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# mask = cv2.inRange(imgHsv, lower, upper)
imgBlurred = cv2.GaussianBlur(imgGray, kernel, 3)
gaussC = cv2.adaptiveThreshold(imgBlurred, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 11, cVal)
imgDial = cv2.dilate(gaussC, kernel, iterations=3)
imgErode = cv2.erode(imgDial, kernel, iterations=1)
return imgDial
def getContours(imPrePro):
contours, hierarchy = cv2.findContours(imPrePro, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
for cnt in contours:
area = cv2.contourArea(cnt)
if area > 60:
cv2.drawContours(imgCon, cnt, -1, (255, 0, 0), 3)
#######################################################################################################
while (cap.isOpened()):
success, frame = cap.read()
cVal = cv2.getTrackbarPos("cVal", "TrackBars")
if success == True:
frame = cv2.flip(frame, 1)
imgCon = frame.copy()
imPrePro = preprocessing(frame, cVal)
getContours(imPrePro)
cv2.imshow("Preprocessed", imPrePro)
cv2.imshow("Original", imgCon)
if cv2.waitKey(1) & 0xFF == ord("q"):
cv2.destroyAllWindows()
break</code></pre>
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