出力画像とマスク画像（正解データ）を比較して、一致しない画素値を出力したい

Question

下のコードを実行すると、以下のエラー分と出力結果が出てきます。
1.0と出力されている部分がおかしいです。
ちゃんと読み込めてはいると思うのですが。。。

DeprecationWarning: elementwise comparison failed; this will raise an error in the future.
  target_diff = np.count_nonzero(result_img != target_img)
00257_00264_00.png out00_01.png 0 0
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1.0 #マスク画像と比較
434 #隣と比較

import pathlib
import argparse
import sys

################################################################
def get_filenames_of_path(path: pathlib.Path, ext: str = "*"):
    """Returns a list of files in a directory/path. Uses pathlib."""
    filenames = [file for file in path.glob(ext) if file.is_file()]
    filenames.sort()
    return filenames

################################################################
def get_args():
    parser = argparse.ArgumentParser(description='Evaluate result',
                                     formatter_class=argparse.ArgumentDefaultsHelpFormatter)
    parser.add_argument('target_dir', type=str)
    parser.add_argument('result_dir', type=str)

    return parser.parse_args()
    
################################################################
args = get_args()

result_dir = pathlib.Path.cwd() / args.result_dir
target_dir = pathlib.Path.cwd() / args.target_dir

################################################################
import numpy as np
import torch
from skimage.io import imread, imsave

# input and target files
result_names = get_filenames_of_path(result_dir)
target_names = get_filenames_of_path(target_dir)

# read images and store them in memory
result_imgs = [imread(str(result_name)) for result_name in result_names]
target_imgs = [imread(str(target_name)) for target_name in target_names]

if len(result_imgs) == 0 or len(target_imgs) == 0:
    print("result or target is empty!!")
    sys.exit()

img_num = min(len(target_imgs), len(result_imgs))

target_sum = 0
target_diff = 0

prev_sum = 0
prev_diff = 0
prev_img = None
for i in range(img_num):
    result_img = result_imgs[i] & 1
    # target_img = target_imgs[i] * 255
    target_img = target_imgs[i] & 1

    # print(result_img.shape)
    # print(target_img.shape)

    target_diff = np.count_nonzero(result_img != target_img)
    if i > 0:
        prev_diff = np.count_nonzero(result_img != prev_img)

    print(f"{result_names[i].name} {target_names[i].name} {target_diff} {prev_diff}")
    target_sum += target_diff
    prev_sum += prev_diff

    prev_img = result_img

print(target_sum/img_num)
print(prev_sum/(img_num-1))