2023-SavasanIHA/detection.py at main · behctas/2023-SavasanIHA · GitHub

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import cv2
import numpy as np
import time

from pyzbar import pyzbar
#from yolov4 import Detector
blueLower = (120,100,20)
blueUpper = (179,255,255)

def imageprocessing(imgOriginal):
    blurred = cv2.GaussianBlur(imgOriginal, (11, 11), 0)
    # hsv
    hsv = cv2.cvtColor(blurred, cv2.COLOR_BGR2HSV)
    # mavi için maske oluştur
    mask = cv2.inRange(hsv, blueLower, blueUpper)
    # maskenin etrafında kalan gürültüleri sil
    mask = cv2.erode(mask, None, iterations=2)
    mask = cv2.dilate(mask, None, iterations=2)


    # farklı sürüm için
    # (_, contours,_) = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    # kontur
    (contours, _) = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    center = None
    x1,x2,y1,y2 = int(imgOriginal.shape[1]*0.25),int(imgOriginal.shape[1]*0.75),int(imgOriginal.shape[0]*0.10),int(imgOriginal.shape[0]*0.90)
    cv2.rectangle(imgOriginal, (x1, y1), (x2, y2), (0, 0, 255), 2)
    if len(contours) > 0:
        return _extracted_from_imageprocessing_20(contours, imgOriginal)
    else:
        return 0,0,0,0,0,0,imgOriginal

# TODO Rename this here and in `imageprocessing`
def _extracted_from_imageprocessing_20(contours, imgOriginal):
    # en buyuk konturu al
    c = max(contours, key=cv2.contourArea)  # alanı en buyuk olan konturu al
    # dikdörtgene çevir
    x_c,y_c,w_c,h_c = cv2.boundingRect(c)# bu alanı kapsayacak en kucuk dıkdortgenı cız

    rect=cv2.minAreaRect(c)
    ((x, y), (width, height), rotation) = rect

    #s = "x: {}, y: {}, width: {}, height: {}, rotation: {}".format(np.round(x), np.round(y), np.round(width),
    #                                                              np.round(height), np.round(rotation))
    # print(s)

    # kutucuk
    box = cv2.boxPoints(rect)
    box = np.int64(box)  # nesnenın etrafını kaplıcagımız kutucuk

    # moment
    M = cv2.moments(c)  # merkez noktayı bulmamızı saglıyan sey
    center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))  # kutucugun orta noktası

    # konturu çizdir: sarı
    cv2.drawContours(imgOriginal,[box],0,(0,255,255),2)
    #cv2.rectangle(imgOriginal, (x,y),(x+w,y+h), (0, 255, 255), 2)  # kutucugu cızdırıyoruz orjinal frame e

    # merkeze bir tane nokta çizelim: pembe
    cv2.circle(imgOriginal, center, 5, (255, 0, 255), -1)

    # bilgileri ekrana yazdır
    #cv2.putText(imgOriginal, s, (25, 50), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (255, 255, 255), 2)

    return 1,center,x_c,y_c,w_c,h_c,imgOriginal

def qr_detection(imgOriginal):
    qr_code_list = pyzbar.decode(imgOriginal)
    x1, x2, y1, y2 = int(imgOriginal.shape[1] * 0.25), int(imgOriginal.shape[1] * 0.75), int(
    imgOriginal.shape[0] * 0.10), int(imgOriginal.shape[0] * 0.90)
    cv2.rectangle(imgOriginal, (x1, y1), (x2, y2), (0, 0, 255), 2)
    for qr_code in qr_code_list:
        return qr_code.data,imgOriginal
    return 0,imgOriginal