Aug 02, 2020 日誌

學習如何使用opencv。Chapter 8 線條及圖案偵測

Chapter 8 Contour/Shape Detection

drawContours

Draws contours outlines or filled contours.

arcLength

Calculates a contour perimeter or a curve length.The function computes a curve length or a closed contour perimeter.

approxPolyDP

Approximates a polygonal curve(s) with the specified precision.

findcontours

RETR_EXTERNAL

python
import cv2
import numpy as np

def stackImages(scale, imgArray):
    rows = len(imgArray)
    cols = len(imgArray[0])
    rowsAvailable = isinstance(imgArray[0], list)
    width = imgArray[0][0].shape[1]
    height = imgArray[0][0].shape[0]
    if rowsAvailable:
        for x in range(0, rows):
            for y in range(0, cols):
                if imgArray[x][y].shape[:2] == imgArray[0][0].shape[:2]:
                    imgArray[x][y] = cv2.resize(imgArray[x][y], (0, 0), None, scale, scale)
                else:
                    imgArray[x][y] = cv2.resize(imgArray[x][y], (imgArray[0][0].shape[1], imgArray[0][0].shape[0]),
                                                None, scale, scale)
                if len(imgArray[x][y].shape) == 2: imgArray[x][y] = cv2.cvtColor(imgArray[x][y], cv2.COLOR_GRAY2BGR)
        imageBlank = np.zeros((height, width, 3), np.uint8)
        hor = [imageBlank] * rows
        hor_con = [imageBlank] * rows
        for x in range(0, rows):
            hor[x] = np.hstack(imgArray[x])
        ver = np.vstack(hor)
    else:
        for x in range(0, rows):
            if imgArray[x].shape[:2] == imgArray[0].shape[:2]:
                imgArray[x] = cv2.resize(imgArray[x], (0, 0), None, scale, scale)
            else:
                imgArray[x] = cv2.resize(imgArray[x], (imgArray[0].shape[1], imgArray[0].shape[0]), None, scale, scale)
            if len(imgArray[x].shape) == 2: imgArray[x] = cv2.cvtColor(imgArray[x], cv2.COLOR_GRAY2BGR)
        hor = np.hstack(imgArray)
        ver = hor
    return ver

def getContours(img):
    contours, hierarchy = cv2.find(img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
    for cnt in contours:
        area = cv2.contourArea(cnt)
        print(area)
                if area > 500:
            cv2.drawContours(imgContour, cnt, -1, (255, 0, 0), 3)
            peri = cv2.arcLength(cnt, True)
            # print(peri)
            approx = cv2.approxPolyDP(cnt, 0.02 * peri, True)
            print(len(approx))
            objCor = len(approx)
            x, y, w, h = cv2.boundingRect(approx)

            if objCor == 3:
                objectType = "Tri"
            elif objCor == 4:
                aspRatio = w / float(h)
                if aspRatio > 0.98 and aspRatio < 1.03:
                    objectType = "Square"
                else:
                    objectType = "Rectangle"
            elif objCor > 4:
                objectType = "Circles"
            else:
                objectType = "None"

            cv2.rectangle(imgContour, (x, y), (x + w, y + h), (0, 255, 0), 2)
            cv2.putText(imgContour, objectType,
                        (x + (w // 2) - 10, y + (h // 2) - 10), cv2.FONT_HERSHEY_COMPLEX, 0.7,
                        (0, 0, 0), 2)

path = 'shapes.png'
img = cv2.imread(path)
imgContour = img.copy()

imgGray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
imgBlur = cv2.GaussianBlur(imgGray,(7,7),1)
imgCanny = cv2.Canny(imgBlur,50,50)
getContours(imgCanny)
imgBlank = np.zeros_like(img)
imgStack = stackImages(0.6,([img,imgGray,imgBlur],
                            [imgCanny,imgContour,imgBlank]))

# cv2.imshow("Original", img)
# cv2.imshow("Gray", imgGray)
# cv2.imshow("Blur", imgBlur)
cv2.imshow("Stack", imgStack)

cv2.waitKey(0)