CutMix图像增广（无标签，批量增广）

# 不增广标签的图像增广
# 增广后和增广前的图像放在一个文件夹里

import os
import random
import numpy as np
from PIL import Image

# Set hyperparameters
alpha = 2.0
crop_size = 512

# Load images from folder
data_dir = 'origin_images'
images = []
for image_file in os.listdir(data_dir):
    image_path = os.path.join(data_dir, image_file)
    images.append(Image.open(image_path))

# Define CutMix function
def cutmix(images):
    # Randomly select two images
    index1 = random.randint(0, len(images) - 1)
    index2 = random.randint(0, len(images) - 1)
    image1, image2 = images[index1], images[index2]

    # Generate a random bounding box
    w, h = image1.size
    cx, cy = random.randint(0, w - 1), random.randint(0, h - 1)
    bbx1, bby1 = np.clip([cx - crop_size // 2, cy - crop_size // 2], 0, [w, h])
    bbx2, bby2 = np.clip([cx + crop_size // 2, cy + crop_size // 2], [0, 0], [w - 1, h - 1])

    # Replace pixels within bounding box with pixels from second image
    image1_array = np.array(image1)
    image2_array = np.array(image2)
    mixed_image_array = np.copy(image1_array)
    mixed_image_array[bbx1:bbx2, bby1:bby2, :] = image2_array[bbx1:bbx2, bby1:bby2, :]
    mixed_image = Image.fromarray(mixed_image_array)

    return mixed_image

# Apply CutMix to images and save the results
for i, image in enumerate(images):
    mixed_image = cutmix(images)
    mixed_image.save(os.path.join(data_dir, f'mixed_{i}.jpg'))