Pythonの画像サイズのバッチサイズ変更（二つのディレクトリ）

この手順は、適切な整列トレーニングセットのデータサイズであります

メインプログラム：align_dataset.py

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

from scipy import misc
import sys
import os
sys.path.append('./')
import numpy as np
import random
from time import sleep
from Configure import Parameters
para = Parameters()


class ImageClass():
    "Stores the paths to images for a given class"

    def __init__(self, name, image_paths):
        self.name = name
        self.image_paths = image_paths

    def __str__(self):
        return self.name + ', ' + str(len(self.image_paths)) + ' images'

    def __len__(self):
        return len(self.image_paths)

def get_image_paths(facedir):
    image_paths = []
    if os.path.isdir(facedir):
        images = os.listdir(facedir)
        image_paths = [os.path.join(facedir,img) for img in images]
    return image_paths

def get_dataset(path, has_class_directories=True):
    dataset = []
    path_exp = os.path.expanduser(path)
    classes = [path for path in os.listdir(path_exp) \
               if os.path.isdir(os.path.join(path_exp, path))]
    classes.sort()
    nrof_classes = len(classes)
    for i in range(nrof_classes):
        class_name = classes[i]
        facedir = os.path.join(path_exp, class_name)
        image_paths = get_image_paths(facedir)
        dataset.append(ImageClass(class_name, image_paths))

    return dataset

def to_rgb(img):
    w, h = img.shape
    ret = np.empty((w, h, 3), dtype=np.uint8)
    ret[:, :, 0] = ret[:, :, 1] = ret[:, :, 2] = img
    return ret

def main():
    sleep(random.random())
    op_dir = para.output_dir
    if not os.path.exists(op_dir):
        os.makedirs(op_dir)
    # Store some git revision info in a text file in the log directory
    src_path,_ = os.path.split(os.path.realpath(__file__))

    dataset = get_dataset(para.input_dir)


    # Add a random key to the filename to allow alignment using multiple processes
    random_key = np.random.randint(0, high=99999)
    bounding_boxes_filename = os.path.join(para.output_dir, 'bounding_boxes_%05d.txt' % random_key)
    
    with open(bounding_boxes_filename, "w") as text_file:
        nrof_images_total = 0
        nrof_successfully_aligned = 0
        if para.random_order:
            random.shuffle(dataset)
        for cls in dataset:
            n = 0
            output_class_dir = os.path.join(para.output_dir, cls.name)
            if not os.path.exists(output_class_dir):
                os.makedirs(output_class_dir)
                if para.random_order:
                    random.shuffle(cls.image_paths)
            for image_path in cls.image_paths:
                nrof_images_total += 1
                filename = os.path.splitext(os.path.split(image_path)[1])[0]
                output_filename = os.path.join(output_class_dir, str(n + 1)+'.png')
                print(image_path)
                if not os.path.exists(output_filename):
                    try:
                        img = misc.imread(image_path)
                    except (IOError, ValueError, IndexError) as e:
                        errorMessage = '{}: {}'.format(image_path, e)
                        print(errorMessage)
                    else:
                        if img.ndim<2:
                            print('Unable to align "%s"' % image_path)
                            text_file.write('%s\n' % (output_filename))
                            continue
                        if img.ndim == 2:
                            img = to_rgb(img)
                        img = img[:,:,0:3]

                        scaled = misc.imresize(img, (para.image_size, para.image_size), interp='bilinear')
                        nrof_successfully_aligned += 1
                        filename_base, file_extension = os.path.splitext(output_filename)
                        output_filename_n = "{}{}".format(filename_base, file_extension)
                        misc.imsave(output_filename_n, scaled)

                n = n+1
                            
    print('Total number of images: %d' % nrof_images_total)
    print('Number of successfully aligned images: %d' % nrof_successfully_aligned)
            


if __name__ == '__main__':
    main()

パラメータ設定：Configure.py