computer_vision_YT/countersAndshapesYT.py at main · HitanshuSoni/computer_vision_YT · GitHub

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import cv2
import numpy as np


def getContours(img):
    contours, hierachy = cv2.findContours(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, (0, 0, 255), 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 = "Rect."

            elif objCor >4:
                objectType = "Circle"

            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)


            cv2.imshow("Contour", imgContour)


img = cv2.imread('./shapes.png')

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)

#cv2.imshow("img", img)
#cv2.imshow("Gray", imgGray)
#cv2.imshow("blur", imgBlur)
#cv2.imshow("Edge", imgCanny)


cv2.waitKey(0)