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main.py
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# import the opencv library
import cv2
# import the numpy library as np
import numpy as np
# import the math library
import math
#import traceback library
import traceback
import wx
from pynput.mouse import Button, Controller
#display corresponding gestures which are in their ranges
def count_number_of_finger(l,frame,areacnt,arearatio):
font = cv2.FONT_HERSHEY_SIMPLEX
if l == 6:
cv2.putText(frame,'reposition',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)
pass
if areacnt<1000:
cv2.putText(frame,'Put hand in the box',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)
else:
if arearatio<12:
cv2.putText(frame,str(l-1),(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)
else:
cv2.putText(frame,str(l),(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)
print("Opening Camera")
# define a video capture object
vid = cv2.VideoCapture(0)
mouse = Controller()
app = wx.App(False)
(screenx,screeny) = wx.GetDisplaySize()
(capturex,capturey) = (700,400)#captures this size frame
kernelOpen = np.ones((5,5))#if noise are present other than yellow area
kernelClose = np.ones((20,20)) #if noise are present in yellow area
# range of the skin colour is defined
lower_skin = np.array([0,20,75], dtype=np.uint8)
upper_skin = np.array([45,255,255], dtype=np.uint8)
cd = 0
while(True):
try:
#an error comes if it does not find anything in window as it cannot find contour of max area
#therefore this try error statement
ret, frame = vid.read()
frame=cv2.flip(frame,1)
kernel = np.ones((3,3),np.uint8)
#define roi which is a small square on screen
roi=frame[100:400, 350:700]
cv2.rectangle(frame,(350,100),(700,400),(0,255,0),0)
hsv = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
#extract skin colour image
mask = cv2.inRange(hsv, lower_skin, upper_skin)
#extrapolate the hand to fill dark spots within
mask = cv2.dilate(mask,kernel,iterations = 4)
#image is blurred using GBlur
mask = cv2.GaussianBlur(mask,(5,5),100)
#find contours
contours,hierarchy= cv2.findContours(mask,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
if len(contours) != 0:
#find contour of max area(hand)
cnt = max(contours, key = lambda x: cv2.contourArea(x))
#approx the contour a little
epsilon = 0.0005*cv2.arcLength(cnt,True)
approx= cv2.approxPolyDP(cnt,epsilon,True)
#make convex hull around hand
hull = cv2.convexHull(cnt)
#define area of hull and area of hand
areahull = cv2.contourArea(hull)
areacnt = cv2.contourArea(cnt)
#find the percentage of area not covered by hand in convex hull
arearatio=((areahull-areacnt)/areacnt)*100
#find the defects in convex hull with respect to hand
hull = cv2.convexHull(approx, returnPoints=False)
defects = cv2.convexityDefects(approx, hull)
# l = no. of defects
l=0
#code for finding no. of defects due to fingers
for i in range(defects.shape[0]):
s,e,f,d = defects[i,0]
start = tuple(approx[s][0])
end = tuple(approx[e][0])
far = tuple(approx[f][0])
pt= (100,180)
# find length of all sides of triangle
a = math.sqrt((end[0] - start[0])**2 + (end[1] - start[1])**2)
b = math.sqrt((far[0] - start[0])**2 + (far[1] - start[1])**2)
c = math.sqrt((end[0] - far[0])**2 + (end[1] - far[1])**2)
s = (a+b+c)/2
ar = math.sqrt(s*(s-a)*(s-b)*(s-c))
#distance between point and convex hull
d=(2*ar)/a
# apply cosine rule here
angle = math.acos((b**2 + c**2 - a**2)/(2*b*c)) * 57
# ignore angles > 90 and ignore points very close to convex hull(they generally come due to noise)
if angle <= 90 and d>25:
l += 1
cv2.circle(roi, far, 3, [255,0,0], -1)
#draw lines around hand
cv2.line(roi,start, end, [0,255,0], 2)
west = tuple(cnt[cnt[:, :, 0].argmin()][0]) #gives the co-ordinate of the left extreme of contour
east = tuple(cnt[cnt[:, :, 0].argmax()][0]) #above for east i.e right
north = tuple(cnt[cnt[:, :, 1].argmin()][0])
south = tuple(cnt[cnt[:, :, 1].argmax()][0])
centre_x = (west[0]+east[0])/2
centre_y = (north[0]+south[0])/2
cv2.circle(frame, (int(centre_x),int(centre_y)), 6, (255,0,0), -1)#plots centre of the area
l+=1
if arearatio<12:
continue
elif l == 1:
mouse.position = (screenx-(centre_x*screenx/capturex),screeny-(centre_y*screeny/capturey))
elif l == 2:
print("left button")
#mouse.press(Button.left)
elif l == 3:
print("right button")
#mouse.press(Button.right)
count_number_of_finger(l,frame,areacnt,arearatio)
cv2.imshow('mask',mask)
cv2.imshow('frame',frame)
except:
print(traceback.print_exc())
pass
# the 'q' button is set as the
# quitting button you may use any
# desired button of your choice
if cv2.waitKey(1) & 0xFF == ord('q'):
print("Closing Camera")
break
# After the loop release the cap object
vid.release()
# Destroy all the windows
cv2.destroyAllWindows()