自定义保持图片宽高比例的resize函数

自定义保持图片宽高比例的resize函数

引用

CSDN

1.

https://blog.csdn.net/m0_57142352/article/details/140048200

在深度学习中，在将图片输入模型之前，一般会进行resize操作，如果直接使用cv2.resize(img,size)函数，可能会导致图片变形，从而引起模型推理错误，需要自定义一个能够保持图片宽高比例的resize函数

代码

def make_image(frame, img_size):
    img = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    img = ratio_preserving_resize(img, img_size)
    return img

def ratio_preserving_resize(image, img_size):
    # ratio preserving resize
    img_h, img_w = image.shape
    scale_h = img_size[1] / img_h
    scale_w = img_size[0] / img_w
    scale_max = max(scale_h, scale_w)
    new_size = (int(img_w * scale_max), int(img_h * scale_max))
    image = cv2.resize(image, new_size, interpolation=cv2.INTER_LINEAR)
    
    # pad the image if necessary
    pad_height = math.ceil(max(0, img_size[1]-new_size[1])/2)
    pad_width = math.ceil(max(0, img_size[0]-new_size[0])/2)
    padded_image = cv2.copyMakeBorder(image, pad_height, pad_height, pad_width, pad_width, cv2.BORDER_CONSTANT,value=(0,0,0) )
    
    # center crop
    x = padded_image.shape[1] // 2 - img_size[0] // 2
    y = padded_image.shape[0] // 2 - img_size[1] // 2
    image = padded_image[y:y + img_size[1], x:x + img_size[0]]
    
    return image  

测试结果

输入的图片：

1、使用opencv提供的resize函数

img_raw = cv2.imread("./001.png")
img_size = (640, 480)
img = cv2.cvtColor(img_raw, cv2.COLOR_BGR2GRAY)
img = cv2.resize(img,img_size)
win_name = 'Test Resize'
cv2.namedWindow(win_name, cv2.WINDOW_FREERATIO)
while(True):
    cv2.imshow(win_name, img)
    key = cv2.waitKey(delay=1)
    if key == ord('q'):
        print('Quitting, \'q\' pressed.')
        break
cv2.destroyAllWindows()  

2、使用自定义的 ratio_preserving_resize函数

img_raw = cv2.imread("./001.png")
img_size = (640, 480)
img = make_image(img_raw.copy(), img_size)
    
win_name = 'Test Ratio Preserving Resize'
cv2.namedWindow(win_name, cv2.WINDOW_FREERATIO)
while(True):
    cv2.imshow(win_name, img)
    key = cv2.waitKey(delay=1)
    if key == ord('q'):
        print('Quitting, \'q\' pressed.')
        break
cv2.destroyAllWindows()