如何加载文件夹中存在的多个PPM文件作为单个Numpy ndarray？ [英] How to load mutiple PPM files present in a folder as single Numpy ndarray?

问题描述

以下Python代码创建numpy数组列表。我希望将数据集加载为具有维度 K x M x N x 3 的numpy数组，其中 K 是图像的索引， M x N x 3 是单个图像的维度。如何修改现有代码呢？

The following Python code creates list of numpy array. I want to load by data sets as a numpy array that has dimension K x M x N x 3 , where K is the index of the image and M x N x 3 is the dimension of individual image. How can I modify the existing code to do so ?

    image_list=[]
    for filename in glob.glob(path+"/*.ppm"):
        img = imread(filename,mode='RGB')
        temp_img = img.reshape(img.shape[0]*img.shape[1]*img.shape[2],1)
        image_list.append(temp_img)

推荐答案

你可以初始化那个形状的输出数组，一旦进入循环，就可以索引第一个轴来迭代地分配图像数组 -

You could initialize an output array of that shape and once inside the loop, index into the first axis to assign image arrays iteratively -

out = np.empty((K,M,N,3), dtype=np.uint8) # change dtype if needed
for i,filename in enumerate(glob.glob(path+"/*.ppm")):
    # Get img of shape (M,N,3)
    out[i] = img

如果你事先不知道 K ，我们可以用 len（glob）得到它.glob（路径+/ * .ppm））。

If you don't know K beforehand, we could get it with len(glob.glob(path+"/*.ppm")).

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