opencv实现数据增强（图片+标签）平移，翻转，缩放，旋转

面试问到了，让手撕数据增强，图片+标签。这里整理一下，直接上代码。

import math
import cv2
import numpy as np

def pan(img, anns, size=(50, 100)):
    '''
    :param img: np.ndarray[h,w,c]
    :param anns: np.ndarray[n,4]
    :param size: list[shift_x, shift_y]
    '''
    shift_x, shift_y = size
    h, w, _ = img.shape
    M = np.array([[1, 0, shift_x], [0, 1, shift_y]], dtype=np.float32)  # 平移矩阵
    img_change = cv2.warpAffine(img, M, (w, h))
    anns_change = anns + np.array([shift_x, shift_y, shift_x, shift_y])
    return img_change, anns_change

def flip(img, anns, flip_code=0):
    # flip_code: 1:水平翻转, 0:垂直翻转, -1:水平垂直翻转
    h, w, _ = img.shape
    img_change = cv2.flip(img, flipCode=flip_code)
    anns_change = anns.copy()
    if flip_code == 1:
        anns_change[:, 0], anns_change[:, 2] = w - anns_change[:, 2], w - anns_change[:, 0]
    elif flip_code == 0:
        anns_change[:, 1], anns_change[:, 3] = h - anns_change[:, 3], h - anns_change[:, 1]
    else:
        anns_change[:, 0], anns_change[:, 2] = w - anns_change[:, 2], w - anns_change[:, 0]
        anns_change[:, 1], anns_change[:, 3] = h - anns_change[:, 3], h - anns_change[:, 1]
    anns_change = np.int32(anns_change)
    return img_change, anns_change

def resize(img, anns, scale=(2, 1)):
    h, w, _ = img.shape
    scale_x, scale_y = scale
    anns_change = anns.copy()
    M = np.array([[scale_x, 0, 0], [0, scale_y, 0]], dtype=np.float32)  # 缩放矩阵
    img_change = cv2.warpAffine(img, M, (int(w * scale_x), int(h * scale_y)))
    anns_change[:, 0], anns_change[:, 2] = anns_change[:, 0] * scale_x, anns_change[:, 2] * scale_x
    anns_change[:, 1], anns_change[:, 3] = anns_change[:, 1] * scale_y, anns_change[:, 3] * scale_y
    anns_change = np.int32(anns_change)
    return img_change, anns_change

def rotate(img, anns, center=(0, 0), angle=-45, scale=1):
    # scale为缩放比例，默认为1，也就是不缩放。 图像旋转+缩放，bboxes对不上，暂时不知道怎么解决。有人知道的话，请评论区告诉我，感谢。
    angle_pi = -angle * math.pi / 180.0  # 弧度
    h, w, _ = img.shape
    M = cv2.getRotationMatrix2D(center, angle, scale)
    img_change = cv2.warpAffine(img, M, (w, h))
    anns_change = anns.copy() * scale

    x1, y1, x2, y2 = anns_change[:, 0], anns_change[:, 1], anns_change[:, 2], anns_change[:, 3]
    x3, y3, x4, y4 = x1, y2, x2, y1
    x1_ = (x1 - center[0]) * math.cos(angle_pi) - (y1 - center[1]) * math.sin(angle_pi) + center[0]
    y1_ = (x1 - center[0]) * math.sin(angle_pi) + (y1 - center[1]) * math.cos(angle_pi) + center[1]
    x2_ = (x2 - center[0]) * math.cos(angle_pi) - (y2 - center[1]) * math.sin(angle_pi) + center[0]
    y2_ = (x2 - center[0]) * math.sin(angle_pi) + (y2 - center[1]) * math.cos(angle_pi) + center[1]
    x3_ = (x3 - center[0]) * math.cos(angle_pi) - (y3 - center[1]) * math.sin(angle_pi) + center[0]
    y3_ = (x3 - center[0]) * math.sin(angle_pi) + (y3 - center[1]) * math.cos(angle_pi) + center[1]
    x4_ = (x4 - center[0]) * math.cos(angle_pi) - (y4 - center[1]) * math.sin(angle_pi) + center[0]
    y4_ = (x4 - center[0]) * math.sin(angle_pi) + (y4 - center[1]) * math.cos(angle_pi) + center[1]

    xs, ys = np.array([x1_, x2_, x3_, x4_]), np.array([y1_, y2_, y3_, y4_])
    xmin, xmax = np.amin(xs, axis=0), np.amax(xs, axis=0)
    ymin, ymax = np.amin(ys, axis=0), np.amax(ys, axis=0)
    anns_change = np.array(list(zip(xmin, ymin, xmax, ymax)))  # 4个[2] ---》 [2, 4]
    anns_change = np.int32(anns_change)

    return img_change, anns_change

if __name__ == '__main__':
    img = cv2.imread("head.jpg")		# 测试图片
    anns = np.array([[180, 100, 250, 150], [340, 100, 380, 150]])	# 测试bbox
    for i in anns:
        cv2.rectangle(img, (i[0], i[1]), (i[2], i[3]), (0, 0, 255), 2)
    cv2.imshow("origin", img)

    # 移动
    img1, anns1 = pan(img, anns)
    for i in anns1:
        cv2.rectangle(img1, (i[0], i[1]), (i[2], i[3]), (0, 0, 255), 2)
    cv2.imshow("pan", img1)

    # 翻转
    img2, anns2 = flip(img, anns)
    for i in anns2:
        cv2.rectangle(img2, (i[0], i[1]), (i[2], i[3]), (0, 0, 255), 2)
    cv2.imshow("flip", img2)

    # 缩放
    img3, anns3 = resize(img, anns)
    for i in anns3:
        cv2.rectangle(img3, (i[0], i[1]), (i[2], i[3]), (0, 0, 255), 2)
    cv2.imshow("resize", img3)

    # 旋转，anns4是下面可视化中蓝色框
    img4, anns4 = rotate(img, anns, center=(img.shape[1] // 2, img.shape[0] // 2))  # 中心旋转
    # img4, anns4 = rotate(img, anns)                                               # 左上角旋转
    for i in anns4:
        cv2.rectangle(img4, (i[0], i[1]), (i[2], i[3]), (255, 0, 0), 2)
    cv2.imshow("rotate", img4)

    cv2.waitKey(0)

结果展示：