Revision history [back]

the code to extract the green boxes from the picture "Python-Interview.jpg" and copy them to a folder.

# Import relevant libraries
image = cv.imread(fpath, -1)
# convert to gray and binarize
gray_img = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
binary_img = cv.adaptiveThreshold(gray_img, 255, cv.ADAPTIVE_THRESH_MEAN_C, cv.THRESH_BINARY, 9, 9)
 # note: erosion and dilation works on white forground
binary_img = cv.bitwise_not(binary_img)
 # dilate the image
kernel = cv.getStructuringElement(cv.MORPH_RECT, (1,1))
dilated_img = cv.morphologyEx(binary_img, cv.MORPH_DILATE, kernel,iterations=1)

# find contours, discard contours which do not belong to a rectangle
(cnts, _) = cv.findContours(dilated_img.copy(), cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE)
sq_cnts = []  # contours of interest to us
for cnt in cnts:
    approx = cv.approxPolyDP(cnt,0.01*cv.arcLength(cnt,True),True)
    if len(approx) == 4:
        (x, y, w, h) = cv.boundingRect(cnt)
#///////// fill remaining code here

for i in range(len(sq_cnts)):
    # find squares
    (x, y, w, h) = cv.boundingRect(sq_cnts[i])
    newimg = image[y:y+h,x:x+w] # crop the image   
    # Write the image

The image

image description

the code to extract the green boxes from the picture "Python-Interview.jpg" and copy them to a folder.

# Import relevant libraries
image = cv.imread(fpath, -1)
# convert to gray and binarize
gray_img = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
binary_img = cv.adaptiveThreshold(gray_img, 255, cv.ADAPTIVE_THRESH_MEAN_C, cv.THRESH_BINARY, 9, 9)
 # note: erosion and dilation works on white forground
binary_img = cv.bitwise_not(binary_img)
 # dilate the image
kernel = cv.getStructuringElement(cv.MORPH_RECT, (1,1))
dilated_img = cv.morphologyEx(binary_img, cv.MORPH_DILATE, kernel,iterations=1)

# find contours, discard contours which do not belong to a rectangle
(cnts, _) = cv.findContours(dilated_img.copy(), cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE)
sq_cnts = []  # contours of interest to us
for cnt in cnts:
    approx = cv.approxPolyDP(cnt,0.01*cv.arcLength(cnt,True),True)
    if len(approx) == 4:
        (x, y, w, h) = cv.boundingRect(cnt)
#///////// fill remaining code here

for i in range(len(sq_cnts)):
    # find squares
    (x, y, w, h) = cv.boundingRect(sq_cnts[i])
    newimg = image[y:y+h,x:x+w] # crop the image   
    # Write the image

The image

image description