标签: opencv-contour

我想找到一个图像的轮廓然后画出它的凸包.我正在做的是加载图像,阈值,找到它的轮廓,然后绘制凸包.

gray = cv2.imread(test_paths[i], 0)
ret, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY_INV)
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnt = contours[0]

检测到的轮廓数量等于1.如果我尝试绘制轮廓,问题就出现了

cv2.drawContours(cnt_dst, cnt, -1, (255, 0, 0), 3)
plt.imshow(cnt_dst)

如果我将代码更改为以下内容:

cv2.drawContours(cnt_dst, contours, 0, (255, 0, 0), 3)
plt.imshow(cnt_dst)

轮廓不同:

请注意,我得到了相同(好)的结果:

cv2.drawContours(cnt_dst, contours, -1, (255, 0, 0), 3)

有关为什么会发生这种情况的任何想法？

我画了一个极端点周围的轮廓.里面的多边形图我有其他点.如何检查它们是否在轮廓内？

我使用了find contours和boundingrect并在我的项目中显示它.然后我想找到最大的轮廓并显示它.这可能吗？我是OpenCV java lang的新手.

到目前为止我的代码:

@Override
public void onCameraViewStarted(int width, int height) {
    mRgba = new Mat(height, width, CvType.CV_8UC4);
    mHsv = new Mat(height,width,CvType.CV_8UC3);
    hierarchy = new Mat();
    mHsvMask = new Mat();
    mDilated = new Mat();
    mEroded = new Mat();
}

@Override
public void onCameraViewStopped() {
    mRgba.release();
    mHsv.release();
    mHsvMask.release();
    mDilated.release();
    hierarchy.release();

}

@Override
public Mat onCameraFrame(CameraBridgeViewBase.CvCameraViewFrame inputFrame) {

    mRgba =inputFrame.rgba();
    contours = new ArrayList<MatOfPoint>();
    hierarchy =new Mat();
    mHsv = new Mat();
    mHsvMask =new Mat();

    Imgproc.cvtColor(mRgba, mHsv, Imgproc.COLOR_RGB2HSV);

    Scalar lowerThreshold = new …

所以我试图从python中的轮廓绘制convexHull,但是当我打印图像时它没有改变.

roi=mask[y:y+h,x:x+w]
roi = cv2.fastNlMeansDenoisingColored(roi,None,15,15,7,21)
hull = cv2.convexHull(cnt)
cv2.drawContours(roi,[hull],0,(147,0,255),2)
cv2.imshow(str(i),roi)
blank_image[y:y+h,x:x+w] = roi

但是,如果我不包含代码,则显示的图像完全相同.我在网上看了,但似乎找不到答案.这是一个示例图片:

我有两个二值图像，我试图检测其中白色斑块的轮廓（拼贴右侧的粉红色轮廓是轮廓结果）。

cv2.contourFind() Contour1 工作正常：

但是对于 Contour2，它的表现很奇怪：

这是它的函数调用

#Convert Image to grayscale
img = cv2.imread(file_name)
img2gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, mask = cv2.threshold(img2gray, 0, 255, cv2.THRESH_OTSU + cv2.THRESH_BINARY_INV)

kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
dilated = cv2.dilate(mask, kernel, iterations=2)
image, contours, hierarchy = cv2.findContours(dilated.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

for contour in contours:
    [x, y, w, h] = cv2.boundingRect(contour)
    cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 255), 2)

使用这个contours变量，我围绕找到的点绘制矩形。我不明白为什么它适用于 Contour1，但在它们看起来非常相似时却无法用于 Contour2。

我正在尝试将OpenCV与Python结合使用，以便检测来自Raspberry Pi摄像机的实时视频源中的正方形。但是，下面的代码中的cv2.GaussianBlur和cv2.Canny函数导致以下错误：“ TypeError：numpy.ndarray'对象不可调用”。

我似乎无法解决该错误。任何帮助表示赞赏。

代码取自https://www.pyimagesearch.com/2015/05/04/target-acquired-finding-targets-in-drone-and-quadcopter-video-streams-using-python-and-opencv/#comment- 446639

import cv2

# load the video
camera = cv2.VideoCapture(0)

# keep looping
while True:
  # grab the current frame and initialize the status text
  (grabbed, frame) = camera.read()
  status = "No Targets"

  # check to see if we have reached the end of the
  # video
  if not grabbed:
     break

  # convert the frame to grayscale, blur it, and detect edges
  gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
  blurred = …

我想裁剪图像中最大的对象（字符）。该代码仅在没有行的情况下才有效（如第一个图像所示）。但是我需要忽略这条线并制作第二张图像。仅裁剪最大的对象图像。

import cv2
x1, y1, w1, h1 = (0,0,0,0)
points = 0

# load image
img = cv2.imread('Image.jpg') 
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # convert to grayscale
# threshold to get just the signature
retval, thresh_gray = cv2.threshold(gray, thresh=100, maxval=255, type=cv2.THRESH_BINARY)

# find where the signature is and make a cropped region
points = np.argwhere(thresh_gray==0) # find where the black pixels are
points = np.fliplr(points) # store them in x,y coordinates instead of row,col indices
x, y, w, h = cv2.boundingRect(points) …

我正在尝试在图像周围绘制轮廓。我可以看到找到了轮廓，但我无法绘制轮廓。轮廓的颜色似乎是两种（黑色和白色）颜色之一。

import cv2
import numpy as np
import matplotlib.pyplot as plt
from skimage import io
%matplotlib inline
im = io.imread('http://matlabtricks.com/images/post-35/man.png')
plt.imshow(im)
imgray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
plt.figure()
plt.imshow(imgray)

#Contoured image
ret,thresh = cv2.threshold(imgray, 120,255,cv2.THRESH_BINARY)
image, contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
c_img = cv2.drawContours(image, contours, -1, (0, 255, 0), 1)
plt.figure()
plt.imshow(c_img)

我在图像中有对象集合。在此处检查样本输入图像。

我想找到每个对象的轮廓。我正在按照以下方法使用OpenCV2识别轮廓

gray = cv2.cvtColor(input_image, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (7, 7), 0)
edged = cv2.Canny(gray, 50, 100)
dilate= cv2.dilate(edged, None, iterations=1)
erode= cv2.erode(dilate, None, iterations=1)
cnts = cv2.findContours(erode, cv2.RETR_EXTERNAL,
        cv2.CHAIN_APPROX_SIMPLE)