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Alexandre Gut
2026-03-31 13:28:59 +02:00
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Divers/tutoriel18-1/README.md Normal file
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# Tutoriel 18 1artie 1
## Sudoku
La vidéo de ce tutoriel est disponible à l'adresse suivante: https://www.youtube.com/watch?v=WwPHs1SJrec

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Divers/tutoriel18-1/perspective.py Normal file
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import cv2
import numpy as np
import operator
marge=4
case=28+2*marge
taille_grille=9*case
methode=cv2.ADAPTIVE_THRESH_GAUSSIAN_C
v1=9
cap=cv2.VideoCapture(0)
while True:
ret, frame=cap.read()
gray=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray=cv2.GaussianBlur(gray, (5, 5), 0)
thresh=cv2.adaptiveThreshold(gray, 255, methode, cv2.THRESH_BINARY_INV, v1, 2)
#cv2.imshow("thresh", thresh)
contours, hierarchy=cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contour_grille=None
maxArea=0
for c in contours:
area=cv2.contourArea(c)
if area>25000:
peri=cv2.arcLength(c, True)
polygone=cv2.approxPolyDP(c, 0.01*peri, True)
if area>maxArea and len(polygone)==4:
contour_grille=polygone
maxArea=area
if contour_grille is not None:
cv2.drawContours(frame, [contour_grille], 0, (0, 255, 0), 2)
points=np.vstack(contour_grille).squeeze()
points=sorted(points, key=operator.itemgetter(1))
if points[0][0]<points[1][0]:
if points[3][0]<points[2][0]:
pts1=np.float32([points[0], points[1], points[3], points[2]])
else:
pts1=np.float32([points[0], points[1], points[2], points[3]])
else:
if points[3][0]<points[2][0]:
pts1=np.float32([points[1], points[0], points[3], points[2]])
else:
pts1=np.float32([points[1], points[0], points[2], points[3]])
pts2=np.float32([[0, 0], [taille_grille, 0], [0, taille_grille], [taille_grille, taille_grille]])
M=cv2.getPerspectiveTransform(pts1, pts2)
grille=cv2.warpPerspective(frame, M, (taille_grille, taille_grille))
cv2.putText(frame, "1", (points[0][0], points[0][1]), cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.9, (0, 0, 255), 1)
cv2.putText(frame, "2", (points[1][0], points[1][1]), cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.9, (0, 0, 255), 1)
cv2.putText(frame, "3", (points[2][0], points[2][1]), cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.9, (0, 0, 255), 1)
cv2.putText(frame, "4", (points[3][0], points[3][1]), cv2.FONT_HERSHEY_COMPLEX_SMALL, 0.9, (0, 0, 255), 1)
cv2.imshow("grille", grille)
txt="ADAPTIVE_THRESH_MEAN_C" if methode==cv2.ADAPTIVE_THRESH_MEAN_C else "ADAPTIVE_THRESH_GAUSSIAN_C"
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)
cv2.imshow("frame", frame)
key=cv2.waitKey(1)&0xFF
if key==ord('q'):
break
if key==ord('p'):
v1=min(21, v1+2)
if key==ord('m'):
v1=max(3, v1-2)
print(v1)
if key==ord('o'):
if methode==cv2.ADAPTIVE_THRESH_GAUSSIAN_C:
methode=cv2.ADAPTIVE_THRESH_MEAN_C
else:
methode=cv2.ADAPTIVE_THRESH_GAUSSIAN_C
cap.release()
cv2.destroyAllWindows()

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Divers/tutoriel18-1/poly.py Normal file
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import cv2
import numpy as np
import operator
methode=cv2.ADAPTIVE_THRESH_GAUSSIAN_C
v1=9
cap=cv2.VideoCapture(0)
while True:
ret, frame=cap.read()
gray=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray=cv2.GaussianBlur(gray, (5, 5), 0)
thresh=cv2.adaptiveThreshold(gray, 255, methode, cv2.THRESH_BINARY_INV, v1, 2)
cv2.imshow("thresh", thresh)
contours, hierarchy=cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contour_grille=None
maxArea=0
for c in contours:
area=cv2.contourArea(c)
if area>25000:
peri=cv2.arcLength(c, True)
polygone=cv2.approxPolyDP(c, 0.01*peri, True)
if area>maxArea and len(polygone)==4:
contour_grille=polygone
maxArea=area
if contour_grille is not None:
cv2.drawContours(frame, [contour_grille], 0, (0, 255, 0), 2)
txt="ADAPTIVE_THRESH_MEAN_C" if methode==cv2.ADAPTIVE_THRESH_MEAN_C else "ADAPTIVE_THRESH_GAUSSIAN_C"
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)
cv2.imshow("frame", frame)
key=cv2.waitKey(1)&0xFF
if key==ord('q'):
break
if key==ord('p'):
v1=min(21, v1+2)
if key==ord('m'):
v1=max(3, v1-2)
print(v1)
if key==ord('o'):
if methode==cv2.ADAPTIVE_THRESH_GAUSSIAN_C:
methode=cv2.ADAPTIVE_THRESH_MEAN_C
else:
methode=cv2.ADAPTIVE_THRESH_GAUSSIAN_C
cap.release()
cv2.destroyAllWindows()

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Divers/tutoriel18-1/threshold.py Normal file
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import cv2
import numpy as np
import operator
methode=cv2.ADAPTIVE_THRESH_GAUSSIAN_C
v1=9
cap=cv2.VideoCapture(0)
while True:
ret, frame=cap.read()
gray=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray=cv2.GaussianBlur(gray, (5, 5), 0)
thresh=cv2.adaptiveThreshold(gray, 255, methode, cv2.THRESH_BINARY_INV, v1, 2)
cv2.imshow("thresh", thresh)
txt="ADAPTIVE_THRESH_MEAN_C" if methode==cv2.ADAPTIVE_THRESH_MEAN_C else "ADAPTIVE_THRESH_GAUSSIAN_C"
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)
cv2.imshow("frame", frame)
key=cv2.waitKey(1)&0xFF
if key==ord('q'):
break
if key==ord('p'):
v1=min(21, v1+2)
if key==ord('m'):
v1=max(3, v1-2)
if key==ord('o'):
if methode==cv2.ADAPTIVE_THRESH_GAUSSIAN_C:
methode=cv2.ADAPTIVE_THRESH_MEAN_C
else:
methode=cv2.ADAPTIVE_THRESH_GAUSSIAN_C
cap.release()
cv2.destroyAllWindows()