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; ARC:4258a5f9
; Submitted by Simon Strandgaard
; Program Type: advanced
mov $40,0 ; outline color
; process "train" vector
mov $80,$97 ; set iteration counter = length of "train" vector
mov $81,100 ; address of first training data train[0].input
mov $82,101 ; address of first training data train[0].output
lps $80
mov $0,$$81 ; load train[x].input image
mov $1,$$82 ; load train[x].output image
; analyze the output images
f12 $1,101070 ; least popular colors
mov $40,$2 ; get the outline color
; next iteration
add $81,100 ; jump to address of next training input image
add $82,100 ; jump to address of next training output image
lpe
; process "train"+"test" vectors
mov $80,$99 ; set iteration counter = length of "train"+"test" vectors
mov $81,100 ; address of vector[0].input
mov $82,102 ; address of vector[0].computed_output
lps $80
mov $0,$$81 ; load vector[x].input image
mov $5,$0
f11 $5,101060 ; most popular color
mov $1,$40 ; outline color
mov $2,$5 ; background color
f31 $0,101080 ; draw outline
mov $$82,$0 ; save vector[x].computed_output image
; next iteration
add $81,100 ; jump to address of next input image
add $82,100 ; jump to address of next computed_output image
lpe