computer vision - Access to ImageNet data download

Question

I've already been granted by the ImageNet website http://www.image-net.org/download-images to download the image data. And the page shows:

You have been granted access to the the whole ImageNet database through our site. By doing so you agree to the terms of access.

Download as one tar file

The full ImageNet data is currently unavailable. Data for ILSVRC is available.

ImageNet Fall 2011 release MD5: ...

ImageNet10K from Deng et al. ECCV2010

But both of the links shows "OOPS The url is not valid." when opened. (It's absolutely not due to some problem of my web or browser. I can tell this by the consistency of ImageNet web page style. I guess these links are too old, and moved to other urls, yet their website didn't update at once)

I have two questions here.

(1) Where and how can I really download the ImageNet data (as well as their labels, for classification task)?

(2) I want the data for the purpose to validate my method in my paper. Even if the dataset is downloaded, I'm afraid that it's unnecessarily big. Do I have to validate on ImageNet (Since its adopted in many papers anyway...) ? The Tiny ImageNet data's page seems not broken on their website. But its a dataset much smaller.

Answer 1

ImageNet Download:

Go to https://www.kaggle.com/c/imagenet-object-localization-challenge and click on the data tab. You can use the Kaggle API to download on a remote computer, or that page to download all the files you want directly.

There, they provide both the labels and the image data.

I don't know what is up with the ImageNet website, however, the url list links were also broken for me today. One way you can still get the data is by going to an alternate mirror, such as Kaggle ImageNet download, the link I provided above. From what I have hears, the Kaggle ImageNet is equivalent to the ImageNet from their website.

I'm unsure about how to answer your second question, as I don't know enough about your project. However, ImageNet will probably work to validate your model.