load train images

train_images = os.listdir('data/train')

train_images[:10]
>>>
['cat.4213.jpg',
 'cat.7203.jpg',
 'dog.8250.jpg',
 'dog.7907.jpg',
 'dog.2318.jpg',
 'cat.6480.jpg',
 'dog.7973.jpg',
 'dog.2225.jpg',
 'dog.611.jpg',
 'dog.5955.jpg']
 
 train_images_data = []
train_images_labels = []

random.shuffle(train_images)

for image in tqdm(train_images):
    image_data = cv2.imread('data/train/' + image)
    
    #Convert to GrayScale
    gray = cv2.cvtColor(image_data, cv2.COLOR_BGR2GRAY)
    
    #convert color from BGR to RGB
    #image_data = cv2.cvtColor(image_data, cv2.COLOR_BGR2RGB)
    
    image_data = cv2.resize(gray, (64, 64))
    
    #turn to only borders
    image_data = cv2.Canny(image_data, 150, 150)
    
    train_images_data.append(image_data)
    train_images_data.append(image_data[:, ::-1]) #flipped image
    
    
    if image.startswith('cat'):
        train_images_labels.append(0)
        train_images_labels.append(0)
    else:
        train_images_labels.append(1)
        train_images_labels.append(1)