python - 保存多个csv文件并从数据集中加载图像

Question

我正在尝试加载具有5k图像的数据集，但出现此错误:

image = cv2.resize(image2, (224, 224))
TypeError: Expected Ptr<cv::UMat> for argument 'src'

但是，当我只放置一张图像时，一切正常。
最后一个问题:当加载了这么多图像的数据集以某种CSV文件形式保存其特征(从我正在使用的滑动窗口中)时，是否可以以某种方式进行？例如: fashion1.png-> fashion1.csv， fashion2.png-> fashion2.csv，... fashion5000.png-> fashion5000.csv吗？

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

#image2 = cv2.imread("fashion1.png")# your image path
image2 = r"C:\Users\John\Desktop\new\fashion\img\*.png"
image = cv2.resize(image2, (224, 224))
tmp = image  # for drawing a rectangle
stepSize = 20
(w_width, w_height) = (60, 60 )  # window size
for x in range(0, image.shape[1] - w_width, stepSize):
    for y in range(0, image.shape[0] - w_height, stepSize):
        window = image[x:x + w_width, y:y + w_height, :]
        cv2.rectangle(tmp, (x, y), (x + w_width, y + w_height), (255, 0, 0), 2)
        plt.imshow(np.array(tmp).astype('uint8'))
        plt.show()
        mean_values=[]
        mean_val, std_dev = cv2.meanStdDev(image)
        mean_val = mean_val[:3]
        mean_values.append([mean_val])
        mean_values = np.asarray(mean_values)
        mean_values2 = mean_values.reshape(1,3)
        result = mean_values2.flatten()
        print(result)
        for i in range(len(result)):
            result_file = open('fashion1.csv', 'a')
            result_file.write("{}{}".format(result[i], '\n'))

Answer 1

第一:要调整图像大小，您必须将其读取到内存中-resize()不能使用文件名。
第二:要读取*.png，您必须使用glob.glob()来获取所有与此模式匹配的文件名，然后使用for -loop单独读取每个图像，调整其大小，甚至创建扩展名为.csv的文件名

import glob
import cv2

pattern = r"C:\Users\John\Desktop\new\fashion\img\*.png"    

for filename in glob.glob(pattern):
    print('PNG:', filename)

    image = cv2.imread(filename)
    image = cv2.resize(image, (224, 224))
    
    csv_filename = filename.replace('.png', '.csv')
    print('CSV:', csv_filename)

    result = [1,2,3,4,5,6]
    
    with open(csv_filename, 'w') as fh:
        for value in result:
            fh.write('{}\n'.format(value))
    

BTW:如果我理解代码，它可能会更简单

import glob
import cv2

# --- functions ---

def process(filename):
    
    print('image:', filename)

    image = cv2.imread(filename)
    image = cv2.resize(image, (224, 224))
    
    step_size = 20
    window_width = 60
    window_height = 60
    
    width  = image.shape[1] - window_width
    height = image.shape[0] - window_height
    
    # --- get all results ---
    
    results = []
    
    for x in range(0, width, step_size):
        for y in range(0, height, step_size):
            image_temp = image.copy()  # for drawing a rectangle
    
            window = image[y:y+window_height, x:x+window_width]
            
            cv2.rectangle(image_temp, (x, y), (x+window_width, y+window_height), (255, 0, 0), 2)

            cv2.imshow('image', image_temp.astype('uint8'))
            # cv2.imshow() needs cv2.waitKey() to update image in window
            cv2.waitKey(1) # wait only 1 ms for key
            #cv2.waitKey(0) # wait until you press any key
            
            mean_val, std_dev = cv2.meanStdDev(window)
            mean_val = mean_val[:3].flatten()
            #print(mean_val)
            results.extend(mean_val)

    cv2.destroyAllWindows() # close window at the end

    # --- write all results ---

    csv_filename = filename.replace('.png', '.csv')

    print('  csv:', csv_filename)

    with open(csv_filename, 'w') as fh:
        for value in results:
            fh.write("{}\n".format(value))

    print('------')

# --- main ---            

pattern = r"C:\Users\John\Desktop\new\fashion\img\*.png"    

for filename in glob.glob(pattern):
    process(filename)