Changes

Most recent releases are shown at the top. Each release shows:

Note that the top-most release is changes in the unreleased master branch on Github.

1.0.7 (2018-10-19)

New class ImagePoints for targets that are a set of point coordinates
New function Image.predict(learn:Learner) to get the activations of the model in Learner for an image
New function Learner.validate to validate on a given dl (default valid_dl), with maybe new metrics or callbacks
New function error_rate which is just 1-accuracy()
New ~/fastai home directory, config file ~/.fastai/config.yml, and default data directory ~/.fastai/data

data is now called basic_data to avoid weird conflicts when naming our data objects data.
All vision models are now in the models module, including torchvision models (where tested and supported). So use models instead of tvm now. If your preferred torchvision model isn't imported, feel free to test it out and tell us on the forum if it works. And if it doesn't, a PR with a test and a fix would be appreciated!
ImageBBox is now a subclass of ImagePoints
All metrics are now Callback. You can pass a regular function like accuracy that will get averaged over batch or a full Callback that can do more complex things
All datasets convenience functions and paths are inside the URLs class
URLs that are a sample have name now suffixed with _SAMPLE
datasets.untar_data and datasets.download_data will now download to fastai home directory ~/.fastai/data if the dataset does not already exist locally ./data.