YOLO数据增强代码
时间: 2023-08-14 16:13:04 浏览: 47
你可以使用以下代码来实现YOLO数据增强:
```python
import cv2
import numpy as np
def random_flip(image, boxes):
if np.random.rand() < 0.5:
image = cv2.flip(image, 1)
boxes[:, [0, 2]] = image.shape[1] - boxes[:, [2, 0]]
return image, boxes
def random_translate(image, boxes, translate=0.2):
if np.random.rand() < 0.5:
height, width, _ = image.shape
translate_x = int(width * translate * np.random.uniform(-1, 1))
translate_y = int(height * translate * np.random.uniform(-1, 1))
translation_matrix = np.float32([[1, 0, translate_x], [0, 1, translate_y]])
image = cv2.warpAffine(image, translation_matrix, (width, height))
boxes[:, [0, 2]] += translate_x
boxes[:, [1, 3]] += translate_y
return image, boxes
def random_scale(image, boxes, scale_range=(0.8, 1.2)):
if np.random.rand() < 0.5:
scale = np.random.uniform(scale_range[0], scale_range[1])
height, width, _ = image.shape
rescaled_dim = (int(width * scale), int(height * scale))
image = cv2.resize(image, rescaled_dim)
boxes[:, :4] *= [scale, scale, scale, scale]
return image, boxes
def random_brightness(image):
if np.random.rand() < 0.5:
hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
brightness = np.random.uniform(0.5, 1.5)
hsv_image[:, :, 2] *= brightness
image = cv2.cvtColor(hsv_image, cv2.COLOR_HSV2BGR)
return image
def random_hue(image):
if np.random.rand() < 0.5:
hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
hue = np.random.uniform(-0.1, 0.1)
hsv_image[:, :, 0] += hue * 255
image = cv2.cvtColor(hsv_image, cv2.COLOR_HSV2BGR)
return image
def random_saturation(image):
if np.random.rand() < 0.5:
hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
saturation = np.random.uniform(0.5, 1.5)
hsv_image[:, :, 1] *= saturation
image = cv2.cvtColor(hsv_image, cv2.COLOR_HSV2BGR)
return image
def random_augmentation(image, boxes):
image, boxes = random_flip(image, boxes)
image, boxes = random_translate(image, boxes)
image, boxes = random_scale(image, boxes)
image = random_brightness(image)
image = random_hue(image)
image = random_saturation(image)
return image, boxes
```
这里的代码包含了几种常用的数据增强方法,包括随机翻转、随机平移、随机尺度变换、随机亮度调整、随机色调调整和随机饱和度调整。你可以根据自己的需求进行选择和修改。