Currencydetect

import RPi.GPIO as GPIO

import time

from utils import cv2, read_img

from gtts import gTTS

import os

import pygame

import time

from gtts import gTTS

from mutagen.mp3 import MP3

import time

GPIO.setwarnings(False)

GPIO.setmode(GPIO.BCM)

IR = 17

SW = 23

GPIO.setup(IR, GPIO.IN)

GPIO.setup(SW, GPIO.IN)

def Play(text):

myobj = gTTS(text=text, lang='en', slow =False)

myobj.save("voice.mp3")

print('\n--------------Playing------------\n')

song = MP3("voice.mp3")

pygame.mixer.init()

pygame.mixer.music.load('voice.mp3')

pygame.mixer.music.play()

time.sleep(song.info.length)

pygame.quit()

def helper(filename):

# from matplotlib import pyplot as plt

max_val = 8

max_pt = -1

max_kp = 0

orb = cv2.ORB_create(nfeatures=2500)

# orb is an alternative to SIFT

#test_img = read_img('files/test_100_2.jpg')

#test_img = read_img('files/test_50_2.jpg')

#test_img = read_img('files/500test.jpg')

#test_img = read_img('files/test_100_3.jpg')

#test_img = read_img('files/10test.jpg')

test_img = read_img(filename)

# resizing must be dynamic

# original = resize_img(test_img, 0.4)

# display('original', original)

# keypoints and descriptors

# (kp1, des1) = orb.detectAndCompute(test_img, None)

(kp1, des1) = orb.detectAndCompute(test_img, None)

training_set = os.listdir('currency')

for i in range(0, len(training_set)):

# train image

try:

print(i)

train_img = cv2.imread('currency/'+training_set[i])

(kp2, des2) = orb.detectAndCompute(train_img, None)

# brute force matcher

bf = cv2.BFMatcher()

all_matches = bf.knnMatch(des1, des2, k=2)

good = []

# give an arbitrary number -> 0.789

# if good -> append to list of good matches

for (m, n) in all_matches:

if m.distance < 0.80 * n.distance:

good.append([m])

if len(good) > max_val:

max_val = len(good)

max_pt = i

max_kp = kp2

print(i, ' ', 'currency/'+training_set[i], ' ', len(good))

except:

continue

print(max_val)

if max_val > 50:

print('currency/'+training_set[max_pt])

print('good matches ', max_val)

train_img = cv2.imread('currency/'+training_set[max_pt])

img3 = cv2.drawMatchesKnn(test_img, kp1, train_img, max_kp, good, 4)

note = training_set[max_pt].split('(')[0]

note = int(note.replace(' ', ''))

print('\nDetected denomination: Rs. ', note)

return note

else:

print('No Matches')

return "-1"

import cv2

amount = 0

print('Starting...')

while True:

if GPIO.input(IR) == False:

print("Inserting")

time.sleep(5)

vs = cv2.VideoCapture(0)

print("Capturing")

counting = 0

while True:

ret, img = vs.read()

counting +=1

cv2.imshow('img', img)

if cv2.waitKey(100) & 0xFF == ord('q'):

vs.release()

cv2.destroyAllWindows()

break

if counting > 50:

cv2.imwrite('frame.jpg', img)

amt = helper('frame.jpg')

if amt != '-1':

amount += amt

Play(f'detected amount is {amt}')

vs.release()

cv2.destroyAllWindows()

break

print('Amount ', amount)

if GPIO.input(SW) == False:

print("Total amount is ", amount)

Play(f'total amount is {amount} rupees')

amount = 0

time.sleep(1)