import cv2
import os

path = './dataset'
categories = os.listdir(path)
labels = [i for i in range(len(categories))]
print(categories, labels)
dic = dict(zip(categories,labels))
print(dic)

data = []
target = []

for i in categories:
    folder_path = os.path.join(path,i)
    img_names = os.listdir(folder_path)
    
    for img_name in img_names:
        img_path = os.path.join(folder_path,img_name)
        img = cv2.imread(img_path,0)
        
        try:
            resized = cv2.resize(img,(100,100))
            data.append(resized)
            target.append(dic[i])
        except Exception as e:
            print("Exception:",e)

import numpy as np

data = np.array(data)/255 # Normalizing

#CNN takes input as (n,(x_size,y_size,channels))
# n -> Number of images
# channels -> 3 for coloured and 1 for BandW
data = np.reshape(data,(data.shape[0],100,100,1)) 
target = np.array(target)

from keras.utils import np_utils
new_targets = np_utils.to_categorical(target)