目标：利用CV2通过对图像旋转、翻转，实现图像扩增
功能1：图像翻转
函数：cv2.flip（src, flipCode[, dst]）
| flipCode | Anno |
|---|---|
| 1 | 水平翻转 |
| 0 | 垂直翻转 |
| -1 | 水平垂直翻转 |
参考地址：https://blog.csdn.net/jningwei/article/details/78753607
水平翻转目标框坐标
| 原目标框：左上角（w0,h0） 右下角（w1,h1） | 水平翻转后：左上角（W-w0-w,h0） 右下角（W-w1+w,h1） |
 |
 |
代码功能：
def img_flip(image_path,annotation_path,image_save_path,annotation_save_path):
num_i = 10000000
list_img = os.listdir(image_path) #image_path文件夹下文件名称列表
path_img = [os.path.join(image_path, path) for path in list_img] #image_path文件夹下文件路径列表
for path in path_img:
num_i += 1
txt = os.path.basename(path).replace('.jpg', '') # 返回文件名
txt_path = txt + '.txt'
annot_path = os.path.join(annotation_path, txt_path)
with open(annot_path, encoding='utf-8') as fp:
text = fp.read()
data = text.split(' ')
if len(data) == 6:
img = cv2.imread(path)
img_h, img_w, _ = img.shape #获取图像高度、宽度、通道数
cv2.flip(img, 1) #图像水平翻转
img_name = 'core_battery' + str(num_i) + '.jpg'
cv2.imwrite(os.path.join(image_save_path, img_name), img)
w_0, w_1, = int(data[2]), int(data[4])
annot_w = w_1 - w_0
w_0_0 = img_w - w_0 - annot_w
w_1_0 = img_w - w_1 + annot_w
string = data[0] + ' ' + data[1] + ' ' + str(w_0_0) + ' ' + data[3] + ' ' + str(w_1_0) + ' ' + data[5]
txt_name = 'core_battery' + str(num_i) + '.txt'
with open(os.path.join(annotation_save_path, txt_name), 'w') as fp:
fp.write(string)
if __name__ == '__main__':
image_save_path = 'C:\data\core_500\image_new' #处理后的图像保存位置
annotation_save_path = 'C:\data\core_500/annotation_new' #处理后的目标框保存位置
annotation_path = 'C:\data\core_500\Annotation' #原图像保存位置
image_path = 'C:\data\core_500\Image' #原目标框保存位置
# 图像翻转
img_flip(image_path,annotation_path,image_save_path,annotation_save_path)
# 图像旋转
img_rot(image_path, annotation_path, image_save_path, annotation_save_path)