关于Numpy数组shape的疑问：处理.npy图像文件后的维度问题

Hey there! Let's walk through exactly why you're getting that shape for your array x—it all lines up with the code you wrote, so let's break it down step by step:

• First, let's look at individual .npy files: Each file has a shape of (37, 3, 224, 224). That 37 is likely the number of augmented image samples tied to a single ID, right?
• The np.mean(..., axis=0) operation: When you calculate the mean along axis 0, you're collapsing that first (37-length) dimension by averaging all 37 samples together. So each individual ID's processed array shrinks from (37, 3, 224, 224) to (3, 224, 224)—you're effectively creating a single "average" image for each ID using its 37 augmented versions.
• Building the final array x: You're looping through 1384 IDs (matching your total number of files), and each iteration adds a (3, 224, 224) array to the list. Converting that list to a numpy array stacks those arrays along a new first dimension, resulting in the shape (1384, 3, 224, 224).

If you were expecting a different shape (like retaining the 37 dimension), you'd skip the np.mean step—your code would then produce an array of shape (1384, 37, 3, 224, 224) instead. But based on the code you wrote, the result you're seeing is exactly what's supposed to happen!

内容的提问来源于stack exchange，提问作者user3789200