answer_84.py

import cv2
import numpy as np
import matplotlib.pyplot as plt
from glob import glob

## Dicrease color
def dic_color(img):
    img //= 63
    img = img * 64 + 32
    return img

## Database
def get_DB():
    # get image paths
    train = glob("dataset/train_*")
    train.sort()

    # prepare database
    db = np.zeros((len(train), 13), dtype=np.int32)

    # each image
    for i, path in enumerate(train):
        img = dic_color(cv2.imread(path))
        # get histogram
        for j in range(4):
            db[i, j] = len(np.where(img[..., 0] == (64 * j + 32))[0])
            db[i, j+4] = len(np.where(img[..., 1] == (64 * j + 32))[0])
            db[i, j+8] = len(np.where(img[..., 2] == (64 * j + 32))[0])

        # get class
        if 'akahara' in path:
            cls = 0
        elif 'madara' in path:
            cls = 1

        # store class label
        db[i, -1] = cls

        img_h = img.copy() // 64
        img_h[..., 1] += 4
        img_h[..., 2] += 8
        plt.subplot(2, 5, i+1)
        plt.hist(img_h.ravel(), bins=12, rwidth=0.8)
        plt.title(path)

    print(db)
    plt.show()

# get database
get_DB()