使用python在图块中转换和裁剪图像

Question

[我试图在python中平铺JPG图像。通常，我使用imageMagick ..所以我比wand似乎能完成这项工作...

但是我无法翻译

 convert -crop 256x256 +repage big_image.jpg tiles_%d.jpg

有人可以帮我吗？

Answer 1

Python的魔杖库提供了唯一的crop alternative.，使用wand.image.Image[left:right, top:bottom]可以对新的虚拟像素图像进行分切片。

from wand.image import Image

with Image(filename="big_image.jpg") as img:
i = 0
for h in range(0, img.height, 256):
    for w in range(0, img.width, 256):
        w_end = w + 256
        h_end = h + 256
        with img[w:w_end, h:h_end] as chunk:
            chunk.save(filename='tiles_{0}.jpg'.format(i))
        i += 1

上面的代码将生成许多与+repage选项匹配的图块图像：

convert -crop 256x256 +repage big_image.jpg tiles_%d.jpg

Answer 2

用于构建功能金字塔样式网络

def image_to_square_tiles(img, SQUARE_SIZE = 256, plot=False, save=False):
"""
Function that splits multi channel channel images into overlapping square tiles (divisible by 128)
:param img: image: multi channel image (NxMxC matrix)
:param number_of_tiles: squared number
:param plot: whether to plot an aimage
:return tiles: named tuple of tiled images (.img) and coordinates (.coords)

------------------------
Examples usage:
_ = image_to_square_tiles(img, SQUARE_SIZE = 512, plot=True)
--------------------------
"""
def get_overlap(l, SQUARE_SIZE):
    N_squares =  np.ceil(l/SQUARE_SIZE)
    pixel_padding = np.remainder(l,SQUARE_SIZE)
    if pixel_padding!=0:
        overlap = int((SQUARE_SIZE-pixel_padding)//(N_squares-1))
    else:
        overlap = 0
    return overlap
def get_tuples(l, overlap, SQUARE_SIZE):
    r = np.arange(0, l-overlap, (SQUARE_SIZE-overlap))
    tuples = [(i, i+SQUARE_SIZE) for i in r]
    return tuples

[w, h] = img.shape[:2]
assert SQUARE_SIZE%128==0, "has to be a multiple of 128 . i.e. [128,256,384,512,640,768,896,1024]"

w_overlap = get_overlap(w, SQUARE_SIZE)
w_tuples = get_tuples(w, w_overlap, SQUARE_SIZE)
h_overlap = get_overlap(h, SQUARE_SIZE)
h_tuples = get_tuples(h, h_overlap, SQUARE_SIZE)

tile_record = namedtuple("info", "img coords")
tiles = []
for row in range(len(w_tuples)):
    for column in range(len(h_tuples)):
        #print(row,column)
        x1, x2, y1, y2 = *w_tuples[row], *h_tuples[column] 
        record = tile_record(img[x1:x2, y1:y2], (x1, y1, x2, y2))
        tiles.append(record)

if plot:
    c = 0
    fig, axes = plt.subplots(len(w_tuples), len(h_tuples), figsize=(15,8))
    for row in range(len(w_tuples)):
        for column in range(len(h_tuples)):
            axes[row, column].imshow(tiles[c].img)
            #axes[row,column].set_title("ave: {:.3f}".format(np.average(tiles[c].img)))
            axes[row,column].axis('off')
            c+=1
    if save:
        plt.savefig("{}.png".format(SQUARE_SIZE), bbox_inches = "tight")
print("h overlap: {}\t w overlap: {}".format(w_overlap, h_overlap))
return tiles