Chapter 7 Results 43
8.1 Future outlook
8.1.3 Smart Watches
Being low in size, in terms of storage, the data can be viewed on to much smaller screens like smart watches. Since some smart watches has a rectangular dial, e.g. Apple watch, positional data can be displayed on it using small dots This would allow more mobility, hence providing a better and faster way to analyze the data.
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APPENDIX A
Appendix A
A1 Background Subtraction Implementation code
A1.1 Extracting Background from Video
d e f e x t r a c t _ b a c k g r o u n d ( v i d e o F i l e ) :
" " " R e c e i v e s a v i d e o f i l e n a m e ( w i t h e x t e n s i o n ) and s a v e s t h e b a c k g r o u n d i m a g e i n s p e c i f i e d f o l d e r " " "
v i d e o = cv2 . V i d e o C a p t u r e ( v i d e o F i l e ) c = 0
w h i l e v i d e o . i s O p e n e d ( ) : _ , img = v i d e o . r e a d ( )
a v e r a g e _ = img f c = f l o a t ( c )
a v e r a g e _ = ( f c * avg_img + img ) / ( f c +1) c += 1
cv2 . i m w r i t e ( ’ p a t h _ o f _ f i l e ’ , a v e r a g e _ )
A1.2 Binary Masking
61
bg = cv2 . i m r e a d ( ’ img / b a c k g r o u n d . j p g ’ )
bg_img = cv2 . c v t C o l o r ( bg , cv2 . COLOR_BGR2GRAY)
d e f t r a c k _ p l a y e r ( v i d e o _ f i l e ) :
c a p = cv2 . V i d e o C a p t u r e ( v i d e o F i l e )
w h i l e c a p . I s O p e n e d ( ) :
r e t , f r a m e = c a p . r e a d ( ) i f n o t r e t :
break
g r a y _ i m g = cv2 . c v t C o l o r ( f r a m e , cv2 . COLOR_BGR2GRAY) b g _ d e l t a = cv2 . a b s d i f f ( bg_img , g r a y _ i m g )
t h r e s h o l d = cv2 . t h r e s h o l d ( b g _ d e l t a , 3 0 , 2 5 5 , cv2 . THRESH_BINARY ) [ 1 ]
t h r e s h o l d = cv2 . e r o d e ( t h r e s h o l d , ( 1 3 , 1 3 ) , i t e r a t i o n s = 1 ) t h r e s h o l d = cv2 . d i l a t e ( t h r e s h o l d , ( 1 0 , 1 0 ) , i t e r a t i o n s = 1 )
t h r e s h o l d = cv2 . e r o d e ( t h r e s h o l d , ( 1 1 , 1 1 ) , i t e r a t i o n s = 1 ) t h r e s h o l d = cv2 . d i l a t e ( t h r e s h o l d , ( 8 , 8 ) , i t e r a t i o n s = 1 )
c o n t o u r s , _ = cv2 . f i n d C o n t o u r s ( t h r e s h o l d . c o p y ( ) ,
cv2 . RETR_EXTERNAL , cv2 . CHAIN_APPROX_SIMPLE )
A1.3 Finding n-components for GMM
i m p o r t cv2
from s k l e a r n . m i x t u r e i m p o r t G a u s s i a n M i x t u r e a s GMM
A1 BACKGROUNDSUBTRACTIONIMPLEMENTATION CODE 63
f r a m e = cv2 . i m r e a d ( ’ img / 0 . png ’ ) img = f r a m e . r e s h a p e ( (−1 , 3 ) )
n _ c o m p o n e n t s = np . a r a n g e ( 1 , 1 0 )
gmm_model = [GMM( n , c o v a r i a n c e _ t y p e = ’ t i e d ’ ) . f i t ( img ) f o r n i n n _ c o m p o n e n t s ]
p l t . p l o t ( n _ c o m p o n e n t s , [m. b i c ( img ) f o r m i n gmm_model ] , l a b e l = " BIC " )
p l t . x l a b e l ( ’ n _ c o m p o n e n t s ’ )
A1.4 Gaussian Mixture Model
i m p o r t cv2
b a c k _ s u b = cv2 . bgsegm . c r e a t e B a c k g r o u n d S u b t r a c t o r M O G ( h i s t o r y = 5 , n m i x t u r e s = 8 )
v i d _ c a p = cv2 . V i d e o C a p t u r e ( v i d e o _ f i l e _ p a t h )
w h i l e v i d _ c a p . i s O p e n e d ( ) : r e t , img = v i d _ c a p . r e a d ( ) i f n o t r e t :
break
fgMask = b a c k _ s u b .a p p l y( img )
fgMask = cv2 . e r o d e ( fgMask , ( 1 3 , 1 3 ) , i t e r a t i o n s = 1 ) fgMask = cv2 . d i l a t e ( fgMask , ( 2 , 2 ) , i t e r a t i o n s = 1 ) fgMask = cv2 . e r o d e ( fgMask , ( 1 3 , 1 3 ) , i t e r a t i o n s = 1 ) fgMask = cv2 . d i l a t e ( fgMask , ( 2 , 2 ) , i t e r a t i o n s = 2 )
c o n t o u r s , _ = cv2 . f i n d C o n t o u r s ( fgMask . c o p y ( ) , cv2 . RETR_EXTERNAL , cv2 . CHAIN_APPROX_SIMPLE )
A1.5 Finding Contours
# F i n d i n g C o n t o u r s on e a c h f r a m e i n s i d e w h i l e l o o p
c o n t o u r s , _ = cv2 . f i n d C o n t o u r s ( fgMask . c o p y ( ) , cv2 . RETR_EXTERNAL , cv2 . CHAIN_APPROX_SIMPLE )
p l a y e r _ p o s = [ ]
# I t e r a t i n g o v e r c o n t o u r s : f o r cn i n c o n t o u r s :
( x , y , w , h ) = cv2 . b o u n d i n g R e c t ( cn )
f e e t _ c o o r d = [ f l o a t ( x + i n t(w / 2 . 0 ) ) , f l o a t ( y + h ) ] f e e t s = P o i n t ( f e e t _ c o o r d [ 0 ] , f e e t _ c o o r d [ 1 ] )
r e c t _ a r e a = cv2 . c o n t o u r A r e a ( cn )
# C h e c k i n g i f d e t e c t i o n i s i n s i d e t h e p o l y g o n d e f i n e d i f n o t f i e l d _ p o l y g o n _ p o i n t s . c o n t a i n s ( f e e t s ) :
c o n t i n u e
# P e r f o r m i n g S e v e r a l c h e c k s f o r p l a y e r d e t e c t i o n i f n o t h > w * 1 . 5 :
c o n t i n u e
i f r e c t _ a r e a < 1 0 0 : c o n t i n u e
i f w > h : c o n t i n u e
A2 DEEPLEARNINGIMPLEMENTATIONS CODE 65
i f y > 1000 and 600 < x < 2900 and r e c t _ a r e a < 1 0 0 0 : c o n t i n u e
i f 800 < y < 1000 and 600 < x < 2900 and r e c t _ a r e a < 5 0 0 : c o n t i n u e
i f 600 < y < 800 and 600 < x < 2900 and r e c t _ a r e a < 3 0 0 : c o n t i n u e
i f y > 1000 and x > 2900 and r e c t _ a r e a < 2 0 0 : c o n t i n u e
p l a y e r . a p p e n d ( [ x , y , x+w , y+h ] )
A2 Deep Learning Implementations code
A2.1 Faster R-CNN implementation
from o b j e c t _ d e t e c t i o n . u t i l s i m p o r t o p s a s u t i l s _ o p s from o b j e c t _ d e t e c t i o n . u t i l s i m p o r t l a b e l _ m a p _ u t i l from c o l l e c t i o n s i m p o r t d e f a u l t d i c t
i m p o r t t e n s o r f l o w a s t f i m p o r t numpy a s np
i m p o r t cv2
d e f l o a d _ m o d e l ( model_name ) :
m o d e l _ d i r = p a t h l i b . P a t h ( model_name ) / " s a v e d _ m o d e l "
model = t f . s a v e d _ m o d e l . l o a d (s t r( m o d e l _ d i r ) , None )
model = model . s i g n a t u r e s [ ’ s e r v i n g _ d e f a u l t ’ ]
A2 DEEPLEARNINGIMPLEMENTATIONS CODE 67
c o n f T h r e s h o l d = 0 . 3
A2 DEEPLEARNINGIMPLEMENTATIONS CODE 69
c l a s s I d s = [ ]
A3 DEEPSORTIMPLEMENTATION 71
o u t _ d u c t = r u n _ i n f e r e n c e _ f o r _ s i n g l e _ i m a g e ( d e t e c t i o n _ m o d e l , i m a g e )
i f l e n( t r a c k e r s ) < 23 & c o u n t % 30 == 0 : f o r i i n o u t _ d u c t [ ’ d e t e c t i o n _ b o x e s ’ ] :
ymin = i n t( i [ 0 ] * h ) xmin = i n t( i [ 1 ] * w) ymax = i n t( i [ 2 ] * h ) xmax = i n t( i [ 3 ] * w)
f e e t _ c o o r d = [ f l o a t ( ( xmin+xmax ) / 2 ) , f l o a t ( ymax ) ] f e e t s = P o i n t ( f e e t _ c o o r d [ 0 ] , f e e t _ c o o r d [ 1 ] )
i f n o t f i e l d _ p o l y g o n _ p o i n t s . c o n t a i n s ( f e e t s ) : c o n t i n u e
t = d l i b . c o r r e l a t i o n _ t r a c k e r ( )
r e c t = d l i b . r e c t a n g l e ( xmin , ymin , xmax , ymax ) t . s t a r t _ t r a c k ( r g b , r e c t )
t r a c k e r s . a p p e n d ( t ) f p s . u p d a t e ( )
e l s e :
f o r t i n t r a c k e r s :
# u p d a t e t h e t r a c k e r and g r a b t h e p o s i t i o n o f t h e t r a c k e d
# o b j e c t
t . u p d a t e ( r g b )
p o s = t . g e t _ p o s i t i o n ( )
A3 DEEPSORTIMPLEMENTATION 73
cv2 . s e t M o u s e C a l l b a c k ( ’ i m a g e ’ , m o u s e _ p o i n t s ) i f cv2 . w a i t K e y ( 0 ) & 0 xFF == 2 7 :
break
p r i n t( ’ f i n a l p o i n t s c o l l e c t e d {} ’ .f o r m a t( p o s L i s t ) ) np . s a v e t x t ( p o s L i s t , p o i n t s _ f i l e )
A3.2 Point Checker
f r o m s h a p e l y . g e o m e t r y i m p o r t P o i n t
f r o m s h a p e l y . g e o m e t r y . p o l y g o n i m p o r t P o l y g o n
p o i n t s = np . l o a d t x t ( p o i n t s _ f i l e ) p o i n t s = p o i n t s . a s t y p e ( i n t )
f i e l d _ p o l y g o n _ p o i n t s = P o l y g o n ( p o i n t s )
f o r cn i n c o n t o u r s :
f e e t _ c o o r d = [ f l o a t ( x + i n t (w / 2 . 0 ) ) , f l o a t ( y + h ) ] f e e t s = P o i n t ( f e e t _ c o o r d [ 0 ] , f e e t _ c o o r d [ 1 ] )
i f n o t f i e l d _ p o l y g o n _ p o i n t s . c o n t a i n s ( f e e t s ) : c o n t i n u e
A3.3 HSV Color picker
i m p o r t cv2
i m p o r t numpy a s np
c a p = cv2 . V i d e o C a p t u r e ( v i d _ f i l e p a t h )
A3 DEEPSORTIMPLEMENTATION 75
d e f n o t h i n g ( x ) : p a s s
# C r e a t i n g a window f o r l a t e r u s e cv2 . namedWindow ( ’ r e s u l t ’ )
# S t a r t i n g w i t h 1 0 0 ’ s t o p r e v e n t e r r o r w h i l e m a s k i n g h , s , v = 1 0 0 , 1 0 0 , 1 0 0
# C r e a t i n g t r a c k b a r
cv2 . c r e a t e T r a c k b a r ( ’ h ’ , ’ r e s u l t ’ , 0 , 1 7 9 , n o t h i n g ) cv2 . c r e a t e T r a c k b a r ( ’ s ’ , ’ r e s u l t ’ , 0 , 2 5 5 , n o t h i n g ) cv2 . c r e a t e T r a c k b a r ( ’ v ’ , ’ r e s u l t ’ , 0 , 2 5 5 , n o t h i n g )
w h i l e ( 1 ) :
_ , f r a m e = c a p . r e a d ( )
# c o n v e r t i n g t o HSV
h s v = cv2 . c v t C o l o r ( f r a m e , cv2 . COLOR_BGR2HSV)
# g e t i n f o f r o m t r a c k b a r and a p p y t o r e s u l t h = cv2 . g e t T r a c k b a r P o s ( ’ h ’ , ’ r e s u l t ’ )
s = cv2 . g e t T r a c k b a r P o s ( ’ s ’ , ’ r e s u l t ’ ) v = cv2 . g e t T r a c k b a r P o s ( ’ v ’ , ’ r e s u l t ’ )
# Normal m a s k i n g a l g o r i t h m l o w e r _ b l u e = np . a r r a y ( [ h , s , v ] )
u p p e r _ b l u e = np . a r r a y ( [ 1 8 0 , 2 5 5 , 2 5 5 ] )
mask = cv2 . i n R a n g e ( hsv , l o w e r _ b l u e , u p p e r _ b l u e )
r e s u l t = cv2 . b i t w i s e _ a n d ( f r a m e , f r a m e , mask = mask )
cv2 . imshow ( ’ r e s u l t ’ , r e s u l t )
k = cv2 . w a i t K e y ( 5 ) & 0 xFF i f k == 2 7 :
b r e a k
c a p . r e l e a s e ( )
cv2 . d e s t r o y A l l W i n d o w s ( )
A3.4 Color Pixel Calculator
c l a s s D e t e c t i o n W i t h C o l o r : d e f _ _ i n i t _ _ ( s e l f ) :
s e l f . l o w e r _ w h i t e = np . a r r a y ( [ 6 0 , 0 , 2 0 4 ] ) s e l f . u p p e r _ w h i t e = np . a r r a y ( [ 1 7 9 , 3 8 , 2 5 5 ] )
s e l f . l o w e r _ b l a c k = np . a r r a y ( [ 0 , 0 , 0 ] )
s e l f . u p p e r _ b l a c k = np . a r r a y ( [ 3 6 0 , 1 0 0 , 5 0 ] )
s e l f . l o w e r _ y e l l o w = np . a r r a y ( [ 1 8 , 1 8 2 , 1 3 0 ] ) s e l f . u p p e r _ y e l l o w = np . a r r a y ( [ 6 7 , 2 5 5 , 2 5 5 ] ) d e f d e t e c t P i x e l C o u n t ( s e l f , p l a y e r _ i m g , x , y ) :
A3 DEEPSORTIMPLEMENTATION 77
p l a y e r _ h s v = cv2 . c v t C o l o r ( p l a y e r _ i m g , cv2 . COLOR_BGR2HSV)
mask3 = cv2 . i n R a n g e ( p l a y e r _ h s v ,
s e l f . l o w e r _ y e l l o w , s e l f . u p p e r _ y e l l o w )
r e s 3 = cv2 . b i t w i s e _ a n d ( p l a y e r _ i m g , p l a y e r _ i m g , mask=mask3 ) r e s 3 = cv2 . c v t C o l o r ( r e s 1 , cv2 . COLOR_HSV2BGR)
r e s 3 = cv2 . c v t C o l o r ( r e s 1 , cv2 . COLOR_BGR2GRAY) y e l l o w C o u n t = cv2 . c o u n t N o n Z e r o ( r e s 1 )
i f y e l l o w C o u n t > 5 0 : r e t u r n ’ r ’
mask1 = cv2 . i n R a n g e ( p l a y e r _ h s v , s e l f . l o w e r _ w h i t e , s e l f . u p p e r _ w h i t e , mask=mask1 )
r e s 1 = cv2 . b i t w i s e _ a n d ( p l a y e r _ i m g , p l a y e r _ i m g , mask=mask1 ) r e s 1 = cv2 . c v t C o l o r ( r e s 1 , cv2 . COLOR_HSV2BGR)
r e s 1 = cv2 . c v t C o l o r ( r e s 1 , cv2 . COLOR_BGR2GRAY) w h i t e C o u n t = cv2 . c o u n t N o n Z e r o ( r e s 1 )
mask2 = cv2 . i n R a n g e ( p l a y e r _ h s v ,
s e l f . l o w e r _ b l a c k , s e l f . u p p e r _ b l a c k )
r e s 2 = cv2 . b i t w i s e _ a n d ( p l a y e r _ i m g , p l a y e r _ i m g , mask=mask2 ) r e s 2 = cv2 . c v t C o l o r ( r e s 2 , cv2 . COLOR_HSV2BGR)
r e s 2 = cv2 . c v t C o l o r ( r e s 2 , cv2 . COLOR_BGR2GRAY) b l a c k C o u n t = cv2 . c o u n t N o n Z e r o ( r e s 2 )
i f w h i t e C o u n t > b l a c k C o u n t :
r e t u r n w h i t e C o u n t , "w"
A3 DEEPSORTIMPLEMENTATION 79
s e l f . f i r e b a s e = f i r e b a s e . F i r e b a s e A p p l i c a t i o n (
’ h t t p s : / / f o o t y−r e d a r . f i r e b a s e i o . com ’ , None )
# d a t a i s t h e a r r a y o f s c a l e d d e t e c t i o n s d e f p u t D a t a ( s e l f , d a t a ) :
n e w _ d i c t = {}
f o r i i n d a t a :
i f s t r ( i [ 1 ] ) n o t i n n e w _ d i c t . k e y s ( ) : n e w _ d i c t [ i [ 1 ] ] = [ ]
n e w _ d i c t [ i [ 1 ] ] . a p p e n d ( i [ 0 ] ) e l s e :
n e w _ d i c t [ i [ 1 ] ] . a p p e n d ( i [ 0 ] ) p r i n t ( ’ d i c t i o n a r y : ’ , n e w _ d i c t )
i f " b " i n n e w _ d i c t and "w" i n n e w _ d i c t : r e s u l t = s e l f . f i r e b a s e . p u t ( ’ / p o i n t s / ’ ,
’/−M7−fgFoB4YiVX4LVQQ8 / ’ , n e w _ d i c t )