imgDial = cv2.dilate(imgThreshold, kernel, iterations=2) # APPLY DILATION
imgThreshold = cv2.erode(imgDial, kernel, iterations=1) # APPLY EROSION
## FIND ALL COUNTOURS
imgContours = img.copy() # COPY IMAGE FOR DISPLAY PURPOSES
imgBigContour = img.copy() # COPY IMAGE FOR DISPLAY PURPOSES
contours, hierarchy = cv2.findContours(imgThreshold, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # FIND ALL CONTOURS
cv2.drawContours(imgContours, contours, -1, (0, 255, 0), 10) # DRAW ALL DETECTED CONTOURS
# FIND THE BIGGEST COUNTOUR
biggest, maxArea = utlis.biggestContour(contours) # FIND THE BIGGEST CONTOUR
if biggest.size != 0:
biggest=utlis.reorder(biggest)
cv2.drawContours(imgBigContour, biggest, -1, (0, 255, 0), 20) # DRAW THE BIGGEST CONTOUR
imgBigContour = utlis.drawRectangle(imgBigContour,biggest,2)
pts1 = np.float32(biggest) # PREPARE POINTS FOR WARP
pts2 = np.float32([[0, 0],[widthImg, 0], [0, heightImg],[widthImg, heightImg]]) # PREPARE POINTS FOR WARP
matrix = cv2.getPerspectiveTransform(pts1, pts2)
imgWarpColored = cv2.warpPerspective(img, matrix, (widthImg, heightImg))
#REMOVE 20 PIXELS FORM EACH SIDE
imgWarpColored=imgWarpColored[20:imgWarpColored.shape[0] - 20, 20:imgWarpColored.shape[1] - 20]
imgWarpColored = cv2.resize(imgWarpColored,(widthImg,heightImg))
# APPLY ADAPTIVE THRESHOLD
imgWarpGray = cv2.cvtColor(imgWarpColored,cv2.COLOR_BGR2GRAY)
imgAdaptiveThre= cv2.adaptiveThreshold(imgWarpGray, 255, 1, 1, 7, 2)
imgAdaptiveThre = cv2.bitwise_not(imgAdaptiveThre)
imgAdaptiveThre=cv2.medianBlur(imgAdaptiveThre,3)
## FIND ALL COUNTOURS
imgConts = img.copy()
imgBigConts = img.copy()
contours, hierarchy = cv2.findContours(
imgThreshold, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE) # FIND ALL CONTOURS
cv2.drawContours(imgConts, contours, -1, (0, 255, 0),
10) # DRAW ALL DETECTED CONTOURS
# FIND THE LARGEST COUNTOUR IN THE FRAME
big, maxArea = utlis.biggestContour(contours) # FIND THE BIGGEST CONTOUR
if big.size != 0:
big = utlis.reorder(big)
cv2.drawContours(imgBigConts, big, -1, (0, 255, 0),
20) # DRAW THE BIGGEST CONTOUR
imgBigConts = utlis.drawRectangle(imgBigConts, big, 2)
pts1 = np.float32(big) # PREPARE POINTS FOR WARP
pts2 = np.float32([[0, 0], [widthImg, 0], [0, heightImg],
[widthImg, heightImg]]) # PREPARE POINTS FOR WARP
matrix = cv2.getPerspectiveTransform(pts1, pts2)
imgWarpColored = cv2.warpPerspective(img, matrix,
(widthImg, heightImg))
#REMOVE EXTRA UNWANTED PIXELS FROM THE SIDES
imgWarpColored = imgWarpColored[20:imgWarpColored.shape[0] - 20,
20:imgWarpColored.shape[1] - 20]
imgWarpColored = cv2.resize(imgWarpColored, (widthImg, heightImg))
# APPLY ADAPTIVE THRESHOLD
imgWarpGray = cv2.cvtColor(imgWarpColored, cv2.COLOR_BGR2GRAY)
imgAdaptiveThre = cv2.adaptiveThreshold(imgWarpGray, 255, 1, 1, 7, 2)