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from __future__ import print_function
import cv2 as cv
import numpy as np
import argparse
import random as rng
rng.seed(12345)
def thresh_callback(val):
threshold = val
# Detect edges using Canny
canny_output = cv.Canny(src_gray, threshold, threshold * 2)
# Find contours
contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
# Find the convex hull object for each contour
hull_list = []
for i in range(len(contours)):
hull = cv.convexHull(contours[i])
hull_list.append(hull)
# Draw contours + hull results
drawing = np.zeros((canny_output.shape[0], canny_output.shape[1], 3), dtype=np.uint8)
for i in range(len(contours)):
color = (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256))
cv.drawContours(drawing, contours, i, color)
cv.drawContours(drawing, hull_list, i, color)
# Show in a window
cv.imshow('Contours', drawing)
# Load source image
parser = argparse.ArgumentParser(description='Code for Convex Hull tutorial.')
parser.add_argument('--input', help='Path to input image.', default='stuff.jpg')
args = parser.parse_args()
src = cv.imread(cv.samples.findFile(args.input))
if src is None:
print('Could not open or find the image:', args.input)
exit(0)
# Convert image to gray and blur it
src_gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
src_gray = cv.blur(src_gray, (3,3))
# Create Window
source_window = 'Source'
cv.namedWindow(source_window)
cv.imshow(source_window, src)
max_thresh = 255
thresh = 100 # initial threshold
cv.createTrackbar('Canny thresh:', source_window, thresh, max_thresh, thresh_callback)
thresh_callback(thresh)
cv.waitKey()
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