October 2016
Intermediate to advanced
558 pages
12h 39m
English
Content preview from OpenCV: Computer Vision Projects with Python
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Detecting pupils
We are going to take a different approach here. Pupils are too generic to take the Haar cascade approach. We will also get a sense of how to detect things based on their shape. Following is what the output will look like:
Let's see how to build the pupil detector:
import math import cv2 import numpy as np img = cv2.imread('input.jpg') scaling_factor = 0.7 img = cv2.resize(img, None, fx=scaling_factor, fy=scaling_factor, interpolation=cv2.INTER_AREA) cv2.imshow('Input', img) gray = cv2.cvtColor(~img, cv2.COLOR_BGR2GRAY) ret, thresh_gray = cv2.threshold(gray, 220, 255, cv2.THRESH_BINARY) contours, hierarchy = cv2.findContours(thresh_gray, ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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