print(arr)
#do ml prediction here
decision = t.predict(arr, gnb_clf)
#print("MLsays:")
f = 1
ok = 0
if (f == 1):
print(decision)
cv2.imshow('res2', res2)
#return ok
cv2.waitKey(0)
#cv2.destroyAllWindows()
#train dataset
t = ml.Gaussian_Naive_Bayes()
X, Y = t.select_data("satellitePixel.csv")
X_train, X_test, y_train, y_test = t.split_data(X, Y)
gnb_clf = t.train_classifier(X_train, y_train)
t.get_accuracy_score(gnb_clf, X_test, y_test)
isok = 0
#take pics in loop
print(
"\nAquiring images and detecting pollution like from a real-time feed:\n")
for m in range(1, 37):
z = "E:/18.Win.Sem/Satellite/pic" + str(m) + ".jpg"
print("Image number - " + str(m))
#isok=isok+pollution(z)
pollution(z)
#print("Accuracy till now:")
#print(isok/m)
