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A lot of websites on CNN for large datasets of images talk about starting with the pretrained model for 1.2 million images in 1000 categories available via AlexNet / Imagenet. These sites seem to imply that this dataset is freely available, but I'm having trouble actually getting access to it. For example, I tried going to https://github.com/deep-diver/AlexNet but couldn't get the code in alexnet.ipynb to run. Consider the following code:

for f in data_file.iterdir():
    data = pickle.loads(f.read_bytes(), encoding='bytes')
    if 'meta' in str(f):
        meta = data
    elif 'test' in str(f):
        test = data
    elif 'batch' in str(f.name):
        train_dic = merge(train_dic, data)

This seems to imply that there should be some data files which include the text strings 'meta', 'test', and/or 'batch', but I couldn't seem to find those files.

Where is the best place to get access to this dataset--ideally somewhere where there is good documentation as to how to download/use it?

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The ImageNet data is online: http://www.image-net.org/.

The data descriptions says:

14,197,122 images, 21841 synsets indexed

However, you don't need to train a model on all of the data from scratch, since you can use pre-trained models, e.g. in TF/Keras. See the docs: https://keras.io/applications/.

I don't think the original Alexnet is available, but a lot of other models are ready to load from Keras. You may also find a Alexnet version stored as .hdf5 or so online (which you could load with Keras/TF).

I don't know what you actually want to do, but here is a simple example of how to use a pretrained model (VGG16 in this case) in Keras.

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