mosaic数据增强可视化代码
时间: 2023-08-14 18:20:33 浏览: 75
以下是用Python和OpenCV实现mosaic数据增强的可视化代码:
```python
import cv2
import numpy as np
# 读取原始图像和标签
img = cv2.imread('image.jpg')
label = cv2.imread('label.jpg', cv2.IMREAD_GRAYSCALE)
# 定义mosaic的大小和步长
mosaic_size = 10
mosaic_step = 5
# 对原始图像和标签进行mosaic数据增强
for y in range(0, img.shape[0], mosaic_step):
for x in range(0, img.shape[1], mosaic_step):
# 计算mosaic的坐标和大小
x1, y1 = x, y
x2, y2 = min(x + mosaic_size, img.shape[1]), min(y + mosaic_size, img.shape[0])
mosaic_w, mosaic_h = x2 - x1, y2 - y1
# 对原始图像进行mosaic数据增强
mosaic_img = cv2.resize(img[y1:y2, x1:x2], (mosaic_w // 4, mosaic_h // 4), interpolation=cv2.INTER_NEAREST)
mosaic_img = cv2.resize(mosaic_img, (mosaic_w, mosaic_h), interpolation=cv2.INTER_NEAREST)
img[y1:y2, x1:x2] = mosaic_img
# 对标签进行mosaic数据增强
mosaic_label = cv2.resize(label[y1:y2, x1:x2], (mosaic_w // 4, mosaic_h // 4), interpolation=cv2.INTER_NEAREST)
mosaic_label = cv2.resize(mosaic_label, (mosaic_w, mosaic_h), interpolation=cv2.INTER_NEAREST)
label[y1:y2, x1:x2] = mosaic_label
# 显示原始图像和标签
cv2.imshow('Original Image', img)
cv2.imshow('Label', label)
cv2.waitKey(0)
cv2.destroyAllWindows()
```
这段代码将原始图像和标签分别进行mosaic数据增强,其中mosaic_size和mosaic_step分别表示mosaic的大小和步长。对于每个mosaic区域,先计算其坐标和大小,然后对原始图像和标签分别进行mosaic数据增强。最后将增强后的图像和标签显示出来。