技術標籤：深度學習資料處理python

隨機擦除程式碼

import os  
import io  
import math
import sys
import random
import argparse
import cv2
import numpy as np

def get_files(dir, suffix): 
    res = []
    for root, directory, files in os.walk(dir): 
        for filename in files:
            name, suf = os.path.splitext(
 
filename) 
            if suf in suffix:
                #res.append(filename)
                res.append(os.path.join(root, filename))
    return res
 
class RandomErasing:
    """Random erasing the an rectangle region in Image.
    Class that performs Random Erasing in Random Erasing Data Augmentation by Zhong et al.
    Args:
        sl: min erasing area region 
        sh: max erasing area region
        r1: min aspect ratio range of earsing region
        p: probability of performing random erasing
    """
 

 
    def __init__(self, p=0.5, sl=0.02, sh=0.4, r1=0.3):
 
        self.p = p
        self.s = (sl, sh)
        self.r = (r1, 1/r1)
    
 
    def __call__(self, img):
        """
        perform random erasing
        Args:
            img: opencv numpy array in form of [w, h, c] range 
                 from [0, 255]
        
        Returns:
            erased img
        """
 

 
        assert len(img.shape) == 3, 'image should be a 3 dimension numpy array'
 
        if random.random() > self.p:
            return img
        
        else:
            while True:
                Se = random.uniform(*self.s) * img.shape[0] * img.shape[1]
                re = random.uniform(*self.r) 
 
                He = int(round(math.sqrt(Se * re)))
                We = int(round(math.sqrt(Se / re)))
 
                xe = random.randint(0, img.shape[1])
                ye = random.randint(0, img.shape[0])
 
                if xe + We <= img.shape[1] and ye + He <= img.shape[0]:
                    img[ye : ye + He, xe : xe + We, :] = np.random.randint(low=0, high=255, size=(He, We, img.shape[2]))
 
                    return img
 
 
if __name__ == "__main__":
    img = cv2.imread('C:\\Users\\Administrator\\Desktop\\000026.jpg')
    RE = RandomErasing(p=1)
    for i in range(20):
        img1 = RE(img.copy())
        cv2.imshow("test", img1)
        cv2.waitKey(1000)