Gender Classification(Processing Images).py

# preparing data by processing images using opencv
ROWS = 64
COLS = 64
CHANNELS = 3

def read_image(file_path):
    img = cv2.imread(file_path, cv2.IMREAD_COLOR) #cv2.IMREAD_GRAYSCALE
    return cv2.resize(img, (ROWS, COLS), interpolation=cv2.INTER_CUBIC)


def prep_data(images):
    count = len(images)
    data = np.ndarray((count, CHANNELS, ROWS, COLS), dtype=np.uint8)

    for i, image_file in enumerate(images):
        image = read_image(image_file)
        data[i] = image.T
        if i%5 == 0: print('Processed {} of {}'.format(i, count))
    
    return data

train = prep_data(train_image_name)
test = prep_data(test_image_name)