Created
August 27, 2021 04:54
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Contour detection - TREE mode
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import cv2 | |
import numpy as np | |
# https://learnopencv.com/read-display-and-write-an-image-using-opencv/ | |
# https://learnopencv.com/contour-detection-using-opencv-python-c/ | |
image = cv2.imread('foot2.jpeg', 1) # 1 for color, 0 for greyscale | |
# stored as <class 'numpy.ndarray'> | |
img_gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) | |
# apply binary thresholding | |
ret, thresh = cv2.threshold(img_gray, 28, 255, cv2.THRESH_BINARY) | |
print(type(image)) | |
cv2.imshow('primary', image) # first argument (primary) is the window_name | |
# specify a new window name for each image | |
cv2.imshow('gray', img_gray) | |
cv2.imshow('binary', thresh) | |
# detect the contours on the binary image using cv2.CHAIN_APPROX_SIMPLE | |
contours, hierarchy = cv2.findContours(image=thresh, mode=cv2.RETR_TREE, method=cv2.CHAIN_APPROX_SIMPLE) | |
print(hierarchy) | |
# result format [Next, Previous, First_Child, Parent] | |
# draw contours on the original image | |
image_copy = image.copy() | |
cv2.drawContours(image=image_copy, contours=contours, contourIdx=-1, color=(0, 255, 0), thickness=2, | |
lineType=cv2.LINE_AA) | |
# see the results | |
cv2.imshow('Approx simple', image_copy) | |
# waitKey() waits for a key press to close the window and 0 specifies indefinite loop | |
# without this command, cv2 will open and close windows immediately | |
cv2.waitKey(0) | |
# save result | |
# cv2.imwrite('contours_none_foot2_v2.jpg', image_copy) | |
cv2.destroyAllWindows() |
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