70 lines
2.9 KiB
Python
70 lines
2.9 KiB
Python
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import cv2
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import numpy as np
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import operator
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marge=4
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case=28+2*marge
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taille_grille=9*case
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methode=cv2.ADAPTIVE_THRESH_GAUSSIAN_C
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v1=9
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cap=cv2.VideoCapture(0)
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while True:
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ret, frame=cap.read()
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gray=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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gray=cv2.GaussianBlur(gray, (5, 5), 0)
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thresh=cv2.adaptiveThreshold(gray, 255, methode, cv2.THRESH_BINARY_INV, v1, 2)
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#cv2.imshow("thresh", thresh)
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contours, hierarchy=cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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contour_grille=None
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maxArea=0
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for c in contours:
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area=cv2.contourArea(c)
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if area>25000:
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peri=cv2.arcLength(c, True)
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polygone=cv2.approxPolyDP(c, 0.01*peri, True)
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if area>maxArea and len(polygone)==4:
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contour_grille=polygone
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maxArea=area
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if contour_grille is not None:
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cv2.drawContours(frame, [contour_grille], 0, (0, 255, 0), 2)
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points=np.vstack(contour_grille).squeeze()
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points=sorted(points, key=operator.itemgetter(1))
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if points[0][0]<points[1][0]:
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if points[3][0]<points[2][0]:
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pts1=np.float32([points[0], points[1], points[3], points[2]])
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else:
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pts1=np.float32([points[0], points[1], points[2], points[3]])
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else:
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if points[3][0]<points[2][0]:
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pts1=np.float32([points[1], points[0], points[3], points[2]])
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else:
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pts1=np.float32([points[1], points[0], points[2], points[3]])
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pts2=np.float32([[0, 0], [taille_grille, 0], [0, taille_grille], [taille_grille, taille_grille]])
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M=cv2.getPerspectiveTransform(pts1, pts2)
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grille=cv2.warpPerspective(frame, M, (taille_grille, taille_grille))
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cv2.putText(frame, "1", (points[0][0], points[0][1]), cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.9, (0, 0, 255), 1)
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cv2.putText(frame, "2", (points[1][0], points[1][1]), cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.9, (0, 0, 255), 1)
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cv2.putText(frame, "3", (points[2][0], points[2][1]), cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.9, (0, 0, 255), 1)
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cv2.putText(frame, "4", (points[3][0], points[3][1]), cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.9, (0, 0, 255), 1)
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cv2.imshow("grille", grille)
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txt="ADAPTIVE_THRESH_MEAN_C" if methode==cv2.ADAPTIVE_THRESH_MEAN_C else "ADAPTIVE_THRESH_GAUSSIAN_C"
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cv2.putText(frame, "[p|m]v1: {:2d} [o]methode: {}".format(v1, txt), (10, 20), cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.9, (0, 0, 255), 1)
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cv2.imshow("frame", frame)
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key=cv2.waitKey(1)&0xFF
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if key==ord('q'):
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break
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if key==ord('p'):
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v1=min(21, v1+2)
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if key==ord('m'):
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v1=max(3, v1-2)
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print(v1)
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if key==ord('o'):
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if methode==cv2.ADAPTIVE_THRESH_GAUSSIAN_C:
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methode=cv2.ADAPTIVE_THRESH_MEAN_C
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else:
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methode=cv2.ADAPTIVE_THRESH_GAUSSIAN_C
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cap.release()
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cv2.destroyAllWindows()
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