lib.py

#Basic Library of Functions
#To Identify Various Chords and Strums
#Using openCV

import cv2
import numpy as np
import play

neck_len=500
neck_top=0
neck_bottom=500


#(post_fix_num,note)

#Notes making each chords in Standard Guitar Tuning

strums = {
	'A': [(3,7),(2,4),(3,0),(2,7),(1,0),(1,7)],
	'C': [(3,7),(2,3),(10,2),(2,7),(1,3),(1,7)],
	'D': [(3,9),(2,5),(3,0),(2,5),(1,0),(1,7)],
	'E': [(3,7),(2,2),(2,11),(2,7),(1,2),(1,7)],
	'G': [(3,10),(2,2),(2,10),(2,5),(1,2),(1,10)]}

#Array to go over each note in case of fret shift

notes_ar = [['A1','A#1','B1','C1','C#1','D1','D#1','E1','F1','F#1','G1','G#1'],
		['A2','A#2','B2','C2','C#2','D2','D#2','E2','F2','F#2','G2','G#2'],
		['A3','A#3','B3','C3','C#3','D3','D#3','E3','F3','F#3','G3','G#3'],
		['A4','A#4','B4','C4','C#4','D4','D#4','E4','F4','F#4','G4','G#4'],
		['A5','A#5','B5','C5','C#5','D5','D#5','E5','F5','F#5','G5','G#5']]

# HSV color ranges
ranges = [[(160, 179),(106, 255),(0, 255)], # Red
		[(60, 90),(81, 255),(0, 255)],	# Green
		[(100, 119),(136, 255),(0, 255)]] # Blue

#Clear noise when reading image contours

def clearNoise(img):
	kernel = np.ones((10, 10), np.uint8)
	clrimg = cv2.morphologyEx(img, cv2.MORPH_CLOSE, kernel)
	clrimg = cv2.erode(img, kernel, iterations=1)
	kernel = np.ones((15, 15), np.uint8)
	clrimg = cv2.dilate(img, kernel, iterations=2)
	# Clears noise from image
	return clrimg

#Filter Out Each ColorBand covered Finger

def filterFingers(img):
		
	height = img.shape[0]
	width = img.shape[1]

	imgcropped = img[0:(height/2), (width/2):(width-1)] # Cropping the ROI

	fingerArray = []

	min = np.array([ranges[0][0][0], ranges[0][1][0], ranges[0][2][0]], np.uint8)
	max = np.array([ranges[0][0][1], ranges[0][1][1], ranges[0][2][1]], np.uint8)
	red = cv2.inRange(imgcropped, min, max)
	red = clearNoise(red)
	fingerArray.append(red)

	min = np.array([ranges[1][0][0], ranges[1][1][0], ranges[1][2][0]], np.uint8)
	max = np.array([ranges[1][0][1], ranges[1][1][1], ranges[1][2][1]], np.uint8)
	green = cv2.inRange(imgcropped, min, max)
	green = clearNoise(green)
	fingerArray.append(green)

	min = np.array([ranges[2][0][0], ranges[2][1][0], ranges[2][2][0]], np.uint8)
	max = np.array([ranges[2][0][1], ranges[2][1][1], ranges[2][2][1]], np.uint8)
	blue = cv2.inRange(imgcropped, min, max)
	blue = clearNoise(blue)
	fingerArray.append(blue)

	# Returns an array of three filtered fingers images
	return fingerArray

#Get coordinates of each fingers/bands topmost point

def getPositions(imgArray):
	# Returns the topmost points of filtered blobs from given imgs

	positions=[]

	for img in imgArray:

		contours, hierarchy = cv2.findContours(img,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)

		if len(contours)<1:
			positions.append((0,0))
			continue


		cnt=contours[0]

		topmost = tuple(cnt[cnt[:,:,1].argmin()][0])

		positions.append(topmost)

	return positions

#Find the Chords to be played based on finger orientation

def getMode(positionArray):
	# Finds mode using by filtering three color strips and finding positions

	#Testing with Y coordinate Only

	R=positionArray[0][1]
	G=positionArray[1][1]
	B=positionArray[2][1]

	if R<G<B:
		mode='A'

	elif B<G<R:
		mode='C'

	elif R<B<G: 
		mode='D'

	elif G<B<R:
		mode='E'

	else:
		mode='G'

	return mode

#Keep tab of strumming hand

def getLowerBlob(img):
	# Filters lower blob and returns position
	position = (0, 0)
	height = img.shape[0]
	width = img.shape[1]

	imgcropped = img[(height/2):(height-1), 0:(width/2)] # Cropping the ROI

	min = np.array([ranges[0][0][0], ranges[0][1][0], ranges[0][2][0]], np.uint8)
	max = np.array([ranges[0][0][1], ranges[0][1][1], ranges[0][2][1]], np.uint8)
	lowerhand = [cv2.inRange(imgcropped, min, max)]
	lowerhand[0] = clearNoise(lowerhand[0])
	pos = getPositions(lowerhand)

	if pos != (0, 0):
		position = pos

	return position

#Generate notes combination based on fret shift, strum direction, chord 

def getPattern(mode,dist,direction):
	pattern=''
	for note in strums[mode]:
		if note[1]+dist>11:
			pattern=pattern+notes_ar[note[0]+1][(note[1]+dist)%12]+' '
		else:
			try:
				pattern=pattern+notes_ar[note[0]][(note[1]+dist)%12]+' '
			except IndexError:
				return ''

	if direction=='up':
		return pattern
	else:
		rev = ""
		_array = pattern.split(" ")
		for row2 in reversed(_array):
			rev += row2 + " "
		return rev[:-1]

#Init neck size

def initNeck(top,bottom):
	#Initialize the neck length
	neck_len=(top[0]-bottom[0][0])/2
	neck_bottom=bottom[0][0]
	neck_top=top[0]

#get fret shift

def getDistance(positions):
	#Get Distance on the neck
	mean=0

	for pos in positions:
		mean+=pos[0]

	mean=neck_top-mean/3

	if mean > 3*neck_len/4:
		return 3
	elif mean > 2*neck_len/4:
		return 2
	elif mean > neck_len/4:
		return 1
	else:
		return 0