create_validation.py

from os.path import join, exists
from os import listdir, makedirs
from shutil import move
import random

species = [
    "blasti",
    "bonegl",
    "brhkyt",
    "cbrtsh",
    "cmnmyn",
    "gretit",
    "hilpig",
    "himbul",
    "himgri",
    "hsparo",
    "indvul",
    "jglowl",
    "lbicrw",
    "mgprob",
    "rebimg",
    "wcrsrt",
]

train_dir = "./train/"
validation_dir = "./validation/"


def create_validation():
    """Validation data sepration from augmented training images.
    Number of images chosen for validation depends upon the
    number of images present in the directory. If less than 78,
    then 6 images are moved into validation folder. Similarly,
    two if conditions for cases with less than 81 and greater
    than 85. Images are selected using random sampling.
    """
    for bird_specie in species:

        train_imgs_path = join(train_dir, bird_specie)
        if not exists(join(validation_dir, bird_specie)):
            destination = makedirs(join(validation_dir, bird_specie))

        train_imgs = listdir(train_imgs_path)
        number = len(train_imgs)  # number of images in each category
        if number < 78:
            validation_separation = random.sample(train_imgs, 6)
            for img_file in validation_separation:
                move(join(train_imgs_path, img_file),
                     join(destination, img_file))

        elif 78 <= number <= 81:
            validation_separation = random.sample(train_imgs, 8)
            for img_file in validation_separation:
                move(join(train_imgs_path, img_file),
                     join(destination, img_file))

        elif number > 85:
            validation_separation = random.sample(train_imgs, 9)
            for img_file in validation_separation:
                move(join(train_imgs_path, img_file),
                     join(destination, img_file))


if __name__ == "__main__":

    create_validation()