53 lines
1.9 KiB
Python
53 lines
1.9 KiB
Python
# from imutils.perspective import four_point_transform
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# from imutils import contours
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#import imutils
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import numpy as np
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import argparse
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import cv2
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import csv
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from photoAnalysisUtils import *
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# Utworzenie plików z koordynatami do punktu odniesienia, oraz poszczegolnymi checkboxami
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f= open("referencePoint.txt","w+")
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f_check = open("checkBoxesCords.txt", "w+")
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image = cv2.imread("emptyTemplate.jpg")
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# Funkcja wyszukujaca punkt odniesienia
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image, x, y = searchReferencePointCorner(image)
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f.write(str(x) + " " + str(y) + "\n")
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#Szukanie konturów oraz koordynatów checkboxów
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edged = cv2.Canny(image, 20, 200)
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gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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thresh = cv2.threshold(edged, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
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threshold_max_area = 5000
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threshold_min_area = 1000
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cnts = cv2.findContours(edged, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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cnts = cnts[0] if len(cnts) == 2 else cnts[1]
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i = 1
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last_x = -1
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last_y = -1
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for c in cnts:
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peri = cv2.arcLength(c, True)
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approx = cv2.approxPolyDP(c, 0.035 * peri, True)
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x,y,w,h = cv2.boundingRect(approx)
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aspect_ratio = w / float(h)
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area = cv2.contourArea(c)
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if len(approx) == 4 and area < threshold_max_area and area > threshold_min_area and (aspect_ratio >= 0.9 and aspect_ratio <= 1.1):
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# Odiltrowanie dublowania konturów oraz zapisywanie ich koordynatów do pliku
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if ( abs(x - last_x) > 0.01*last_x ) or ( abs(y - last_y) > 0.01*last_y ):
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last_x = x
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last_y = y
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f_check.write(str(x)+' '+str(y)+' '+str(w)+' '+str(h)+''+"\n")
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cv2.rectangle(image, (x, y), (x + w, y + h), (36,255,12), 2)
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print("X: "+str(x)+" Y: "+str(y)+" I:", str(i))
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cv2.putText(image, str(i), (x+50,y+50), cv2.FONT_HERSHEY_SIMPLEX, 2,(0,255,0),2)
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i=i+1
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cv2.drawContours(image, [c], 0, (0, 255, 0), 3)
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cv2.imwrite("templateProcess.jpg", image)
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f.close();
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f_check.close(); |