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@SatyakiDe2019
Created Mar 21, 2022
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This is the main class to calculate the number of stacked coins after reading using computer vision
##################################################
#### Written By: SATYAKI DE ####
#### Written On: 17-Jan-2022 ####
#### Modified On 20-Mar-2022 ####
#### ####
#### Objective: This python class will ####
#### learn the number of coins stacks on ####
#### top of another using computer vision ####
#### with the help from Open-CV after ####
#### manually recalibarting the initial ####
#### data (Individual Coin Heights needs to ####
#### adjust based on the distance of camera.) ####
##################################################
import cv2
from clsAutoDetector import *
import numpy as np
import os
import platform as pl
# Custom Class
from clsConfig import clsConfig as cf
import clsL as cl
# Initiating Log class
l = cl.clsL()
# Load Aruco detector
arucoParams = cv2.aruco.DetectorParameters_create()
arucoDict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_5X5_50)
# Load Object Detector
detector = clsAutoDetector()
class clsCountRealtime:
def __init__(self):
self.sep = str(cf.conf['SEP'])
self.Curr_Path = str(cf.conf['INIT_PATH'])
self.coinDefH = float(cf.conf['COIN_DEF_HEIGHT'])
self.pics2cm = float(cf.conf['PIC_TO_CM_MAP'])
def learnStats(self, debugInd, var):
try:
# Per Coin Default Size from the known distance_to_camera
coinDefH = self.coinDefH
pics2cm = self.pics2cm
# Load Cap
cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
while True:
success, img = cap.read()
if success == False:
break
# Get Aruco marker
imgCorners, a, b = cv2.aruco.detectMarkers(img, arucoDict, parameters=arucoParams)
if imgCorners:
# Draw polygon around the marker
imgCornersInt = np.int0(imgCorners)
cv2.polylines(img, imgCornersInt, True, (0, 255, 0), 5)
# Aruco Perimeter
arucoPerimeter = cv2.arcLength(imgCornersInt[0], True)
# Pixel to cm ratio
pixelCMRatio = arucoPerimeter / pics2cm
contours = detector.detectObjects(img)
# Draw objects boundaries
for cnt in contours:
# Get rect
rect = cv2.boundingRect(cnt)
(x, y, w, h) = rect
print('*'*60)
print('Width Pixel: ')
print(str(w))
print('Height Pixel: ')
print(str(h))
# Get Width and Height of the Objects by applying the Ratio pixel to cm
objWidth = round(w / pixelCMRatio, 1)
objHeight = round(h / pixelCMRatio, 1)
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
cv2.putText(img, "Width {} cm".format(objWidth), (int(x - 100), int(y - 20)), cv2.FONT_HERSHEY_PLAIN, 2, (100, 200, 0), 2)
cv2.putText(img, "Height {} cm".format(objHeight), (int(x - 100), int(y + 15)), cv2.FONT_HERSHEY_PLAIN, 2, (100, 200, 0), 2)
NoOfCoins = round(objHeight / coinDefH)
cv2.putText(img, "No Of Coins: {}".format(NoOfCoins), (int(x - 100), int(y + 35)), cv2.FONT_HERSHEY_PLAIN, 2, (250, 0, 250), 2)
print('Final Height: ')
print(str(objHeight))
print('No Of Coins: ')
print(str(NoOfCoins))
cv2.imshow("Image", img)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
return 0
except Exception as e:
x = str(e)
print('Error: ', x)
return 1
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