this repository is fork from chainer examples for imagenet training.
- Pillow (Pillow requires an external library that corresponds to the image format)
This is an experimental example of learning from the ILSVRC2012 classification dataset. It requires the training and validation dataset of following format:
- Each line contains one training example.
- Each line consists of two elements separated by space(s).
- The first element is a path to 256x256 RGB image.
- The second element is its ground truth label from 0 to 999.
The text format is equivalent to what Caffe uses for ImageDataLayer. This example currently does not include dataset preparation script.
This example requires "mean file" which is computed by compute_mean.py.