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August 27, 2021 04:50
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Contour detection after pre-processing with diltion
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import cv2 | |
image = cv2.imread('foot2.jpeg', 1) # 1 for color, 0 for greyscale | |
img_gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) | |
# ******** # | |
# Dilation # | |
# ******** # | |
from skimage.morphology import (erosion, dilation) | |
from skimage.morphology import disk | |
footprint = disk(1) | |
dilated = dilation(img_gray, footprint) | |
cv2.imshow('gray', img_gray) | |
cv2.imshow('dilation', dilated) | |
# ************************************ # | |
# Binary Thresholding on Dilated image # | |
# ************************************ # | |
ret, thresh = cv2.threshold(dilated, 30, 255, cv2.THRESH_BINARY) | |
cv2.imshow('binary thresholding', thresh) | |
# detect the contours on the binary image using cv2.CHAIN_APPROX_SIMPLE | |
contours, hierarchy = cv2.findContours(image=thresh, mode=cv2.RETR_EXTERNAL, 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('None approximation', image_copy) | |
cv2.waitKey(0) | |
cv2.destroyAllWindows() |
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