import cv2

import numpy as np

import os

import random

import pickle

t_d = []

directory = "C:\\Users\\AYUSH MISHRA\\Desktop"

categories = ["with_mask","without_mask"]

for i in categories :

path = os.path.join(directory,i)

c_n = categories.index(i)

for p in os.listdir(path):

img = cv2.imread(os.path.join(path,p))

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

img_resize= cv2.resize(gray,(224,224))

t_d.append([img_resize, c_n])

random.shuffle(t_d)

print(len(t_d))

label = []

feature = []

for f in t_d :

label.append(f)

feature.append(f)

label = label/255.0

labels = np.array(label).reshape((-1,224,224,3))

features = np.array(feature)

pickle_o = open("labels.pickle","wb")

pickle.dump(labels,pickle_o)

pickle_o.close()

pickle_o = open("features.pickle","wb")

pickle.dump(features,pickle_o)

pickle_o.close()

print(labels.shape,features.shape) # shape of the training data