Python:中心阵列图像

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1条回答

网友

1楼 · 发布于 2024-10-08 18:30:03

img = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 11, 203, 229, 32, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 26, 47, 47, 30, 95, 254, 215, 13, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 45, 154, 185, 185, 223, 253, 253, 133, 175, 255, 188, 19, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 110, 253, 253, 253, 246, 161, 228, 253, 253, 254, 92, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 128, 245, 253, 158, 137, 21, 0, 48, 233, 253, 233, 8, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 139, 254, 223, 25, 0, 0, 36, 170, 254, 244, 106, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 55, 212, 253, 161, 11, 26, 178, 253, 236, 113, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 155, 253, 228, 80, 223, 253, 253, 109, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 141, 253, 253, 253, 254, 253, 154, 29, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 110, 253, 253, 253, 254, 179, 38, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 171, 254, 254, 254, 179, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 171, 253, 253, 253, 253, 178, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 26, 123, 254, 253, 203, 156, 253, 200, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 93, 253, 254, 121, 13, 93, 253, 158, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 64, 239, 253, 76, 8, 32, 219, 253, 126, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 133, 254, 191, 0, 5, 108, 234, 254, 106, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 132, 253, 190, 5, 85, 253, 236, 154, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 153, 253, 169, 192, 253, 253, 77, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 112, 253, 253, 254, 236, 129, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 17, 118, 243, 191, 113, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
            [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])

所以问题的第一部分是找到包含图像的边界框，第二部分涉及图像的居中，因为第二部分我们将为边界框的每个顶点添加填充。在

第1部分：

为了绘制一个边界框，我们可以遍历每一行并找到一个包含1个或多个非零元素的行，通过从上到下两个步骤，我们将得到Y-axis的限制，与我们对{}的限制一样，Numpy提供了一些很棒的函数，比如^{}，我们将使用此函数检查行/列是否有任何非零字符，在这种情况下，sum > 0：

设（x1，y1）为左上角坐标，（x2，y2）为右下角坐标，这两点足以定义边界框。在

^{pr2}$

第二部分：

现在我们必须将图像居中，而不是计算每边所需的填充，而是将图像裁剪成边界框的形状，然后将相等的填充应用到每一侧。在

def add_padding(img, pad_l, pad_t, pad_r, pad_b):
    height, width = img.shape
    #Adding padding to the left side.
    pad_left = np.zeros((height, pad_l), dtype = np.int)
    img = np.concatenate((pad_left, img), axis = 1)

    #Adding padding to the top.
    pad_up = np.zeros((pad_t, pad_l + width))
    img = np.concatenate((pad_up, img), axis = 0)

    #Adding padding to the right.
    pad_right = np.zeros((height + pad_t, pad_r))
    img = np.concatenate((img, pad_right), axis = 1)

    #Adding padding to the bottom
    pad_bottom = np.zeros((pad_b, pad_l + width + pad_r))
    img = np.concatenate((img, pad_bottom), axis = 0)

    return img

cropped_image = img[y1:y2, x1:x2]
padded_image = add_padding(cropped_image, 20, 20, 20, 20)

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