<p>These are the detailed steps on how I obtained ImageNet and ran a PyTorch example training on it:</p>
<pre><code>        1. Go to https://www.image-net.org/download.php
        2. Request to download ImageNet 
        3. Wait about 5 days for approval, write to them if the waiting period is over.
        4. [I think you can skip this step] Download the Development Kit from the ILSVRC2017 page
        5. Download the images from the ILSVRC2012 page
            a. Training images (Task 1 &amp; 2) 138 GB
            b. Validation images (all tasks) 6.3 GB
            c. Test images (all tasks) 13 GB
        6. [I think you can skip this step if you use the script from step 8!] Unpack the tar files 
            a. mkdir val
            b. tar -C val/ -xvf ILSVRC2012_img_val*.tar 
            c. mkdir test
            d. tar -C test/ -xvf ILSVRC2012_img_test_v10102019.tar 
            e. mkdir train
            f. tar -C train/ -xvf ILSVRC2012_img_train.tar
        7. Confirm the number of images in each folder
            a. ls val/ | wc -l # should give 50,000
            b. ls test/ | wc -l # should give 100,000
        8. Run the script extract_ILSVRC.sh from the PyTorch GitHub [https://github.com/pytorch/examples/blob/main/imagenet/extract_ILSVRC.sh]
        #  imagenet/train/
        #  ├── n01440764
        #  │   ├── n01440764_10026.JPEG
        #  │   ├── n01440764_10027.JPEG
        #  │   ├── ......
        #  ├── ......
        #  imagenet/val/
        #  ├── n01440764
        #  │   ├── ILSVRC2012_val_00000293.JPEG
        #  │   ├── ILSVRC2012_val_00002138.JPEG
        #  │   ├── ......
        #  ├── ......
        9. Run a PyTorch example training on your ImageNet dataset [e.g. from the PyTorch examples GitHub repository https://github.com/pytorch/examples/blob/main/imagenet/main.py]
</code></pre>

CC BY-SA 4.0
2022-08-08T11:23:10.417Z
2024-04-25T13:38:56.943Z
2024-04-25T13:38:56.943Z
Anna Christine
<p>ImageNet is available in <code>torchvision datasets</code>. <a href="https://pytorch.org/vision/stable/generated/torchvision.datasets.ImageNet.html" rel="nofollow noreferrer">https://pytorch.org/vision/stable/generated/torchvision.datasets.ImageNet.html</a></p>

CC BY-SA 4.0
2022-07-22T14:18:46.777Z
that is just a wrapper class to import the data from a folder, it does not allow to download the original images and annotations.
Edoardo Guerriero
CC BY-SA 4.0
2022-07-22T08:30:55.817Z
2022-07-22T08:30:55.817Z
DKDK
<p>Please can someone describe how to properly obtain the <strong>ImageNet dataset</strong> (to be precise the ImageNet 2012 Classification Dataset).</p>
<p><strong>What I attempted so far</strong></p>
<p>The <a href="https://image-net.org/download.php" rel="nofollow noreferrer">ImageNet webpage</a> refers the user to download the ImageNet dataset from Kaggle. However, the Kaggle webpage it refers belongs to the Image <em>Localization</em> (not classification) challenge.</p>
<p>I have also requested a download from the ImageNet webpage which is pending since almost one year.</p>

<image-recognition><pytorch><image-net>
ImageNet Dataset (for PyTorch VGG16 training)
Anna Christine
# ImageNet Dataset (for PyTorch VGG16 training)

(Asked by: username_0 on 2022-07-21)

Please can someone describe how to properly obtain the **ImageNet dataset** (to be precise the ImageNet 2012 Classification Dataset).

**What I attempted so far**

The [ImageNet webpage](https://image-net.org/download.php) refers the user to download the ImageNet dataset from Kaggle. However, the Kaggle webpage it refers belongs to the Image *Localization* (not classification) challenge.

I have also requested a download from the ImageNet webpage which is pending since almost one year.

**Tags:** image-recognition, pytorch, image-net


---

## 2 answers

### Answer by username_0 on 2022-08-08. Score: 1

These are the detailed steps on how I obtained ImageNet and ran a PyTorch example training on it:
        1. Go to https://www.image-net.org/download.php
        2. Request to download ImageNet 
        3. Wait about 5 days for approval, write to them if the waiting period is over.
        4. [I think you can skip this step] Download the Development Kit from the ILSVRC2017 page
        5. Download the images from the ILSVRC2012 page
            a. Training images (Task 1 & 2) 138 GB
            b. Validation images (all tasks) 6.3 GB
            c. Test images (all tasks) 13 GB
        6. [I think you can skip this step if you use the script from step 8!] Unpack the tar files 
            a. mkdir val
            b. tar -C val/ -xvf ILSVRC2012_img_val*.tar 
            c. mkdir test
            d. tar -C test/ -xvf ILSVRC2012_img_test_v10102019.tar 
            e. mkdir train
            f. tar -C train/ -xvf ILSVRC2012_img_train.tar
        7. Confirm the number of images in each folder
            a. ls val/ | wc -l # should give 50,000
            b. ls test/ | wc -l # should give 100,000
        8. Run the script extract_ILSVRC.sh from the PyTorch GitHub [https://github.com/pytorch/examples/blob/main/imagenet/extract_ILSVRC.sh]
        #  imagenet/train/
        #  ├── n01440764
        #  │   ├── n01440764_10026.JPEG
        #  │   ├── n01440764_10027.JPEG
        #  │   ├── ......
        #  ├── ......
        #  imagenet/val/
        #  ├── n01440764
        #  │   ├── ILSVRC2012_val_00000293.JPEG
        #  │   ├── ILSVRC2012_val_00002138.JPEG
        #  │   ├── ......
        #  ├── ......
        9. Run a PyTorch example training on your ImageNet dataset [e.g. from the PyTorch examples GitHub repository https://github.com/pytorch/examples/blob/main/imagenet/main.py]


---

### Answer by username_1 on 2022-07-22. Score: -1

ImageNet is available in `torchvision datasets`. <https://pytorch.org/vision/stable/generated/torchvision.datasets.ImageNet.html>

> **Comments:**
> **username_2**: that is just a wrapper class to import the data from a folder, it does not allow to download the original images and annotations.  

---

