python opencv度图像进行批量resize操作(OCR文本图)

环境win10+python3.9+opencv-python

将OCR文本图放到一个固定尺寸上：

resize到32x640的尺寸上：

python脚本：

import os
import random

import cv2
import glob
import pathlib
import numpy as np

# 批量resize图片

data_path = r'E:\datasets\gen_number_str_hw\train_enhance'

save_path = r'E:\datasets\gen_number_str_hw\train_enhance_resize'

if not os.path.exists(save_path):
    os.makedirs(save_path)

best_width = 0
resize_width = 640
width_limit_cnt = 0

for img_path in glob.glob(data_path + '/*.jpg', recursive=True):
    d = pathlib.Path(img_path)
    img = cv2.imread(img_path, cv2.IMREAD_UNCHANGED)
    if img is None:
        continue
    dim = (int(img.shape[1] * 32 / img.shape[0]), 32)
    # resize image
    resized = cv2.resize(img, dim, interpolation=cv2.INTER_AREA)

    # print(resized.shape[0],resized.shape[1])
    if resized.shape[1] > best_width:
        best_width = resized.shape[1]
        print(best_width, img_path)
    if resized.shape[1] > 640:
        width_limit_cnt = width_limit_cnt + 1
        print('limit:' + str(width_limit_cnt), img_path)
    img = np.zeros((32, resize_width, 3), np.uint8)  # 创建一个空白图像
    img.fill(0)
    fill_w = resize_width - resized.shape[1]
    fill_img = np.zeros((32, fill_w, 3), np.uint8)
    fill_img.fill(random.randint(0, 255))
    img.fill(0)
    img[:, resized.shape[1]:resize_width] = fill_img
    img[:, 0:resized.shape[1]] = resized
    # c = cv2.addWeighted(resized, 0.4, img, 0.6, 0, 0)
    # cv2.imshow('img', img)
    # cv2.waitKey(0)
    # save_img_path = os.path.join(save_path, (str(d.stem) + '.jpg'))
    save_img_path = save_path + '/' + str(d.stem) + '.jpg'
    # cv2.imwrite(save_img_path,resized)

    cv2.imwrite(save_img_path, img)
    # cv2.namedWindow("test")
    # cv2.imshow('test', resized)
    # cv2.waitKey(300) # 显示 10000 ms 即 10s 后消失
    # cv2.destroyAllWindows()