i have attached my original image and then i attached way I want to detect the contour. I have tried many ways (canny edge, sobel filter, shape recognition) but nothing worked for me. I have tried to make tracker bars to set the value of thresholding and canny edge detection but no combination works.
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import cv2 as cv
import numpy as np
# load the image
def load_image():
"""load the image in rgb format"""
img = cv.imread("images/test_pillar.png", cv.IMREAD_COLOR)
return img
# resize the image to 100 microns for marker length
def reshape_image(frame):
"""resize the image to 100 microns for marker length"""
scale_percent = 80 # percent of original size
width = int(frame.shape[1] * scale_percent / 100)
height = int(frame.shape[0] * scale_percent / 100)
dim = (width, height)
# resize image
frame = cv.resize(frame, dim, interpolation=cv.INTER_AREA)
return frame
def image_processing(img, lower_gray, upper_gray, lower_canny, upper_canny):
"""take an rgb image and returns a canny image"""
# convert image to rgb
img = cv.cvtColor(img, cv.COLOR_BGR2RGB)
gray_image = cv.cvtColor(img, cv.COLOR_RGB2GRAY) # gray image
blur_image = cv.GaussianBlur(gray_image, (5, 5), 0)
# canny edge detection
canny_image = cv.Canny(blur_image, lower_canny, upper_canny)
# # setting threshold of gray image
# _, threshold = cv.threshold(canny_image, lower_gray, upper_gray, cv.THRESH_BINARY)
eroded = cv.erode(canny_image, (5, 5), iterations=1) # type: ignore
dilated = cv.dilate(eroded, (5, 5), iterations=1) # type: ignore
thresh = cv.adaptiveThreshold(dilated, 255,
cv.ADAPTIVE_THRESH_GAUSSIAN_C, cv.THRESH_BINARY_INV, 11, 11)
return thresh
def nothing(x):
pass
def add_tracker_bars(window_name):
"""add four tracker bars to the window, two for thresholding and two for canny edge detection"""
cv.namedWindow(window_name)
cv.createTrackbar("lower_gray", window_name, 0, 255, nothing)
cv.createTrackbar("upper_gray", window_name, 0, 255, nothing)
cv.createTrackbar("lower_canny", window_name, 0, 255, nothing)
cv.createTrackbar("upper_canny", window_name, 0, 255, nothing)
# set initial values for tracker bar
cv.setTrackbarPos("lower_gray", window_name, 1)
cv.setTrackbarPos("upper_gray", window_name, 10)
cv.setTrackbarPos("lower_canny", window_name, 10)
cv.setTrackbarPos("upper_canny", window_name, 30)
# find contours and properties of contours like area, perimeter and approx
def find_contours_and_its_properties(canny_image):
# using a findContours() function
contours, _ = cv.findContours(
canny_image, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
return contours
# main function
def main():
# load the image
img = load_image()
# reshape the image
img = reshape_image(img)
# add tracker bars
window_name = "image"
add_tracker_bars(window_name)
while True:
lower_gray = cv.getTrackbarPos("lower_gray", window_name)
upper_gray = cv.getTrackbarPos("upper_gray", window_name)
lower_canny = cv.getTrackbarPos("lower_canny", window_name)
upper_canny = cv.getTrackbarPos("upper_canny", window_name)
# apply image processing
canny_image = image_processing(img, lower_gray, upper_gray, lower_canny, upper_canny)
# find contours and its properties
contours = find_contours_and_its_properties(canny_image)
# # draw the contours
img_copy = img.copy()
cv.drawContours(img_copy, contours, -1, (255, 0, 255), 5)
# display the image
cv.imshow(window_name, img_copy)
# cv.imshow("canny", canny_image)
if cv.waitKey(1) & 0xFF == ord("q"):
break
if __name__ == "__main__":
main()
