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Sadaival authored Feb 11, 2018
1 parent df74070 commit c49ceed
Showing 1 changed file with 156 additions and 0 deletions.
156 changes: 156 additions & 0 deletions gesture.py
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import cv2
import numpy as np
import math
cap = cv2.VideoCapture(0)

while(1):

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 = cap.read()
frame=cv2.flip(frame,1)
kernel = np.ones((3,3),np.uint8)

#define region of interest
roi=frame[100:300, 100:300]


cv2.rectangle(frame,(100,100),(300,300),(0,255,0),0)
hsv = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)



# define range of skin color in HSV
lower_skin = np.array([0,20,70], dtype=np.uint8)
upper_skin = np.array([20,255,255], dtype=np.uint8)

#extract skin colur imagw
mask = cv2.inRange(hsv, lower_skin, upper_skin)



#extrapolate the hand to fill dark spots within
mask = cv2.dilate(mask,kernel,iterations = 4)

#blur the image
mask = cv2.GaussianBlur(mask,(5,5),100)



#find contours
_,contours,hierarchy= cv2.findContours(mask,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)

#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>30:
l += 1
cv2.circle(roi, far, 3, [255,0,0], -1)

#draw lines around hand
cv2.line(roi,start, end, [0,255,0], 2)


l+=1

#print corresponding gestures which are in their ranges
font = cv2.FONT_HERSHEY_SIMPLEX
if l==1:
if areacnt<2000:
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,'0',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)
elif arearatio<17.5:
cv2.putText(frame,'Best of luck',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

else:
cv2.putText(frame,'1',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

elif l==2:
cv2.putText(frame,'2',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

elif l==3:

if arearatio<27:
cv2.putText(frame,'3',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)
else:
cv2.putText(frame,'ok',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

elif l==4:
cv2.putText(frame,'4',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

elif l==5:
cv2.putText(frame,'5',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

elif l==6:
cv2.putText(frame,'reposition',(0,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

else :
cv2.putText(frame,'reposition',(10,50), font, 2, (0,0,255), 3, cv2.LINE_AA)

#show the windows
cv2.imshow('mask',mask)
cv2.imshow('frame',frame)
except:
pass


k = cv2.waitKey(5) & 0xFF
if k == 27:
break

cv2.destroyAllWindows()
cap.release()





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