text_plain_output_1.png
import os

import random

import os
import random
from multiprocessing import Pool
import numpy as np
import cv2
import albumentations as A
import matplotlib.pyplot as plt
from tqdm import tqdm
INPUT_PATH = '../input/happy-whale-and-dolphin'
IMG_SIZE = 600

train_files = os.listdir(os.path.join(INPUT_PATH, 'train_images'))
test_files = os.listdir(os.path.join(INPUT_PATH, 'test_images'))
all_files = [os.path.join(INPUT_PATH, 'train_images', f) for f in train_files] + [os.path.join(INPUT_PATH, 'test_images', f) for f in test_files]
print(f'Train files: {len(train_files)}, test files: {len(test_files)}, all_files: {len(all_files)}')
show_images = random.sample(all_files, 5)
print(show_images)