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[OpenCV] リアルタイムで物体の輪郭を抽出する

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#はじめに
OpenCVによる画像処理の基礎を整理します。
100本ノックのように、毎日追加していきたいと思います。

#やりたいこと
写真や動画の物体の輪郭を抽出したいと思います。

#輪郭抽出までの手順

  1. 画像を読み込む。(動画の場合、各フレームを読み込む。)
  2. ノイズ除去のため、GaussianBlurを行う。
  3. ColorをGrayScaleに変換する。
  4. Canny変換を行う。この時、Threshold1,2で調節を行う。(大事!)
  5. Dilation(拡張処理)を行う。
  6. Contourを検出する。
  7. 元の画像に検出したContourを描画する。

#実行結果

[オリジナル動画、GaussianBlur処理後、GrayScaleh変換
Canny変換、Dilation処理、輪郭抽出描画]

bandicam-2020-12-02-17-52-01-508.gif

#全体コード


import cv2
import numpy as np

frameWidth = 640
frameHeight = 480

cap = cv2.VideoCapture('videos/rectangle.mp4')
#cap = cv2.VideoCapture(0)

# Properties
cap.set(3, frameWidth)
cap.set(4, frameHeight)


def empty(a):
    pass


cv2.namedWindow('Parameters')
cv2.resizeWindow('Parameters', 1600, 400)
cv2.createTrackbar('Threshold1', 'Parameters', 0, 255, empty)
cv2.createTrackbar('Threshold2', 'Parameters', 0, 255, empty)
cv2.createTrackbar('Area', 'Parameters', 5000, 30000, empty)


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, imgContour):
    contours, hierarchy = cv2.findContours(img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
    #cv2.findContours(入力画像、contour retrieval mode, 輪郭研修津方法)
    for cnt in contours:
        area = cv2.contourArea(cnt)
        areaMin = cv2.getTrackbarPos("Area", "Parameters")
        if area > areaMin:
            #輪郭描画
            cv2.drawContours(imgContour, cnt, -1, (255, 0, 255), 7)
            peri = cv2.arcLength(cnt, True)
            approx = cv2.approxPolyDP(cnt, 0.02 * peri, True)
            print(len(approx))
            x, y, w, h = cv2.boundingRect(approx)
            cv2.rectangle(imgContour, (x, y), (x + w, y + h), (0, 255, 0), 5)

            cv2.putText(imgContour, "Points: " + str(len(approx)), (x + w + 20, y + 20), cv2.FONT_HERSHEY_COMPLEX, .7,
                        (0, 255, 0), 2)
            cv2.putText(imgContour, "Area: " + str(int(area)), (x + w + 20, y + 45), cv2.FONT_HERSHEY_COMPLEX, 0.7,
                        (0, 255, 0), 2)

while True:
    ret, img = cap.read()
    img = cv2.resize(img, (frameWidth, frameHeight))
    imgContour = img.copy()

    # Gaussian Blur
    imgBlur = cv2.GaussianBlur(img, (7, 7), 1)
    # Gray
    imgGray = cv2.cvtColor(imgBlur, cv2.COLOR_BGR2GRAY)
    # Canny
    threshold1 = cv2.getTrackbarPos('Threshold1', 'Parameters')
    threshold2 = cv2.getTrackbarPos('Threshold2', 'Parameters')
    imgCanny = cv2.Canny(imgGray, threshold1=threshold1, threshold2=threshold1)
    # Dialation
    kernel = np.ones((5, 5))
    imgDil = cv2.dilate(imgCanny, kernel=kernel, iterations=1)
    #Contours
    getContours(imgDil, imgContour)


    imgStack = stackImages(0.8, ([img, imgBlur, imgGray],
                                 [imgCanny, imgDil, imgContour]))
    cv2.imshow('Result', imgStack)

    # qを押すと止まる。
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

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