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Hand posture detection with OpenCV.
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#!/usr/bin/env python | |
import cv2 | |
import numpy as np | |
def main(): | |
cap = cv2.VideoCapture(0) | |
while(cap.isOpened()): | |
ret, img = cap.read() | |
skinMask = HSVBin(img) | |
contours = getContours(skinMask) | |
cv2.drawContours(img, contours, -1, (0, 255, 0), 2) | |
cv2.imshow('capture', img) | |
k = cv2.waitKey(10) | |
if k == 27: | |
break | |
def getContours(img): | |
kernel = np.ones((5,5),np.uint8) | |
closed = cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel) | |
closed = cv2.morphologyEx(closed, cv2.MORPH_CLOSE, kernel) | |
contours, h = cv2.findContours(closed, cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE) | |
validContours = []; | |
for cont in contours: | |
if cv2.contourArea(cont) > 9000: | |
# x,y,w,h = cv2.boundingRect(cont) | |
# if h/w > 0.75: | |
validContours.append(cv2.convexHull(cont)) | |
# rect = cv2.minAreaRect(cont) | |
# box = cv2.cv.BoxPoints(rect) | |
# validContours.append(np.int0(box)) | |
return validContours | |
def HSVBin(img): | |
hsv = cv2.cvtColor(img, cv2.COLOR_RGB2HSV) | |
lower_skin = np.array([100, 50, 0]) | |
upper_skin = np.array([125, 255, 255]) | |
mask = cv2.inRange(hsv, lower_skin, upper_skin) | |
# res = cv2.bitwise_and(img, img, mask=mask) | |
return mask | |
if __name__ == '__main__': | |
main() |
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