我有一组不同尺寸的图片 (45,50,3), (69,34,3), (34,98,3)，我想按照以下方式为这些图片添加填充：
找出所有图片中宽度和长度的最大值，并将图片调整到该尺寸。
import os
import glob
import cv2
input_path="/home/images"
os.chdir(indput_path)
images=glob.glob("*.png")
Length=[]
Width=[]
for img in images:
img=cv2.imread(img)
width,length=img.shape[0:2]
Length.append(length)
Width.append(width)
W=max(Width)
L=max(Length)
如何在OpenCV中添加填充以使所有图像具有相同的大小？ 在我给出的例子中，图像将获得形状（69,98,3）
如何在OpenCV中添加填充以使所有图像具有相同的大小？ 在我给出的例子中，图像将获得形状（69,98,3）
你可以使用：
image = cv2.copyMakeBorder(src, top, bottom, left, right, borderType)
其中src是您的源图像，top、bottom、left、right是图像周围的填充。
您可以在while循环中使用最大尺寸(max(sizes))减去图像大小(size)的值来为每个图像添加填充。 边框类型可以是以下之一：
cv2.BORDER_CONSTANTcv2.BORDER_REFLECTcv2.BORDER_REFLECT_101cv2.BORDER_DEFAULTcv2.BORDER_REPLICATEcv2.BORDER_WRAP以下是在Python/OpenCV/Numpy中另一种实现方法。它使用Numpy切片将输入图像复制到所需的输出大小和给定偏移量的新图像中。这里我计算偏移量以进行中心填充。我认为这种方法更容易使用宽度、高度、x偏移量和y偏移量，而不是在每侧填充多少。
输入：
import cv2
import numpy as np
# read image
img = cv2.imread('lena.jpg')
old_image_height, old_image_width, channels = img.shape
# create new image of desired size and color (blue) for padding
new_image_width = 300
new_image_height = 300
color = (255,0,0)
result = np.full((new_image_height,new_image_width, channels), color, dtype=np.uint8)
# compute center offset
x_center = (new_image_width - old_image_width) // 2
y_center = (new_image_height - old_image_height) // 2
# copy img image into center of result image
result[y_center:y_center+old_image_height,
x_center:x_center+old_image_width] = img
# view result
cv2.imshow("result", result)
cv2.waitKey(0)
cv2.destroyAllWindows()
# save result
cv2.imwrite("lena_centered.jpg", result)
h，w，c = img.shape。因此，单个字母是可以的，但不是双字母？没有人想一直输入高度和宽度！尽管如此，我确实理解可读性和理解方面的关注。 - fmw42尝试使用这个函数：
from PIL import Image, ImageOps
def padding(img, expected_size):
desired_size = expected_size
delta_width = desired_size[0] - img.size[0]
delta_height = desired_size[1] - img.size[1]
pad_width = delta_width // 2
pad_height = delta_height // 2
padding = (pad_width, pad_height, delta_width - pad_width, delta_height - pad_height)
return ImageOps.expand(img, padding)
def resize_with_padding(img, expected_size):
img.thumbnail((expected_size[0], expected_size[1]))
# print(img.size)
delta_width = expected_size[0] - img.size[0]
delta_height = expected_size[1] - img.size[1]
pad_width = delta_width // 2
pad_height = delta_height // 2
padding = (pad_width, pad_height, delta_width - pad_width, delta_height - pad_height)
return ImageOps.expand(img, padding)
if __name__ == "__main__":
img = Image.open("./demo.jpg")
print(img)
img = resize_with_padding(img, (500, 400))
print(img.size)
img.show()
img.save("resized_img.jpg")
原始图像
使用填充调整大小后
请查看https://gist.github.com/BIGBALLON/cb6ab73f6aaaa068ab6756611bb324b2
像这样（在OpenCV中称为边框的填充）：
BLUE = [255,255,255]
constant= cv2.copyMakeBorder(image.copy(),10,10,10,10,cv2.BORDER_CONSTANT,value=BLUE)
蓝色甚至可以变成白色
来源： https://docs.opencv.org/3.4/da/d0c/tutorial_bounding_rects_circles.html
由于我没有看到被接受的答案，而且还需要确定函数的顶部、底部、左侧和右侧，因此我在下面提供了我容易理解的方法。参考自：https://jdhao.github.io/2017/11/06/resize-image-to-square-with-padding/
import cv2
desired_size = 368
im_pth = "/home/jdhao/test.jpg"
im = cv2.imread(im_pth)
old_size = im.shape[:2] # old_size is in (height, width) format
ratio = float(desired_size)/max(old_size)
new_size = tuple([int(x*ratio) for x in old_size])
# new_size should be in (width, height) format
im = cv2.resize(im, (new_size[1], new_size[0]))
delta_w = desired_size - new_size[1]
delta_h = desired_size - new_size[0]
top, bottom = delta_h//2, delta_h-(delta_h//2)
left, right = delta_w//2, delta_w-(delta_w//2)
color = [0, 0, 0]
new_im = cv2.copyMakeBorder(im, top, bottom, left, right, cv2.BORDER_CONSTANT,
value=color)
cv2.imshow("image", new_im)
cv2.waitKey(0)
cv2.destroyAllWindows()
im = cv2.resize(im, (new_size[1], new_size[0])) 中，你需要将其中一个 new_size 改为 old_size。第一个是为了保持高度不变，第二个是为了保持宽度不变。 - George Sotiropoulosimport cv2
def pad_images_to_same_size(images):
"""
:param images: sequence of images
:return: list of images padded so that all images have same width and height (max width and height are used)
"""
width_max = 0
height_max = 0
for img in images:
h, w = img.shape[:2]
width_max = max(width_max, w)
height_max = max(height_max, h)
images_padded = []
for img in images:
h, w = img.shape[:2]
diff_vert = height_max - h
pad_top = diff_vert//2
pad_bottom = diff_vert - pad_top
diff_hori = width_max - w
pad_left = diff_hori//2
pad_right = diff_hori - pad_left
img_padded = cv2.copyMakeBorder(img, pad_top, pad_bottom, pad_left, pad_right, cv2.BORDER_CONSTANT, value=0)
assert img_padded.shape[:2] == (height_max, width_max)
images_padded.append(img_padded)
return images_padded
这里只需要一行代码就可以完成
from PIL import Image
from PIL import ImageOps
image = Image.open("demo.jpg").convert("RGB")
ImageOps.pad(image,(100,100)).save('imaged-with-border.png')
这将保持我的图像在100x100的大小，同时保持其宽高比并添加零填充。
受@sebl ful的启发。它应该适用于黑白图像或彩色图像
def resize_with_padding(image, shape_out, DO_PADDING=True, TINY_FLOAT=1e-5):
"""
Resizes an image to the specified size,
adding padding to preserve the aspect ratio.
"""
if image.ndim == 3 and len(shape_out) == 2:
shape_out = [*shape_out, 3]
hw_out, hw_image = [np.array(x[:2]) for x in (shape_out, image.shape)]
resize_ratio = np.min(hw_out / hw_image)
hw_wk = (hw_image * resize_ratio + TINY_FLOAT).astype(int)
# Resize the image
resized_image = cv2.resize(
image, tuple(hw_wk[::-1]), interpolation=cv2.INTER_NEAREST
)
if not DO_PADDING or np.all(hw_out == hw_wk):
return resized_image
# Create a black image with the target size
padded_image = np.zeros(shape_out, dtype=np.uint8)
# Calculate the number of rows/columns to add as padding
dh, dw = (hw_out - hw_wk) // 2
# Add the resized image to the padded image, with padding on the left and right sides
padded_image[dh : hw_wk[0] + dh, dw : hw_wk[1] + dw] = resized_image
return padded_image
crop_pad()函数即可。它可以自动调整大小，并在需要时添加“零”填充（rgb=（0,0,0）/黑色），而不会进行任何图片缩放。from PIL import Image
img = Image.open(your_file_path)
img.crop_pad((width, height))
这是我所能做到的最好，仅适用于黑白图像
def resize_with_padding(image, size=(224,224)):
'''
Resizes a black and white image to the specified size,
adding padding to preserve the aspect ratio.
'''
# Get the height and width of the image
height, width = image.shape
# Calculate the aspect ratio of the image
aspect_ratio = height / width
# Calculate the new height and width after resizing to (224,224)
new_height, new_width = size
if aspect_ratio > 1:
new_width = int(new_height / aspect_ratio)
else:
new_height = int(new_width * aspect_ratio)
# Resize the image
resized_image = cv2.resize(image, (new_width, new_height), interpolation = cv2.INTER_NEAREST)
# Create a black image with the target size
padded_image = np.zeros((224,224), dtype=np.uint8)
# Calculate the number of rows/columns to add as padding
padding_rows = (224 - new_height) // 2
padding_cols = (224 - new_width) // 2
# Add the resized image to the padded image, with padding on the left and right sides
padded_image[padding_rows:padding_rows+new_height, padding_cols:padding_cols+new_width] = resized_image
return padded_image