Segmentation-models

Areas of improvement
- Support for `keras` and `tf.keras`
- Losses as classes, base loss operations (sum of losses, multiplied loss)
- NCHW and NHWC support
- Removed pure tf operations to work with other keras backends
- Reduced a number of custom objects for better models serialization and deserialization

New featrues
- New backbones: EfficentNetB[0-7]
- New loss function: Focal loss
- New metrics: Precision, Recall

API changes
- `get_preprocessing` moved from `sm.backbones.get_preprocessing` to `sm.get_preprocessing`

Areas of improvement

- Added `set_regularization` function
- Added `beta` argument to dice loss
- Added `threshold` argument for metrics
- Fixed `prerprocess_input` for mobilenets
- Fixed missing parameter `interpolation` in `ResizeImage` layer config
- Some minor improvements in docs, fixed typos

Areas of improvement

- New backbones (SE-ResNets, SE-ResNeXts, SENet154, MobileNets)
- Metrcis:
- `iou_score` / `jaccard_score`
- `f_score` / `dice_score`
- Losses:
- `jaccard_loss`
- `bce_jaccard_loss`
- `cce_jaccard_loss`
- `dice_loss`
- `bce_dice_loss`
- `cce_dice_loss`
- Documentation [Read the Docs](https://segmentation-models.readthedocs.io)
- Tests + Travis-CI

API changes

- Some parameters renamed (see API docs)
- `encoder_freeze=True` does not `freeze` BatchNormalization layer of encoder

Thanks

[IlyaOvodov](https://github.com/IlyaOvodov) [15](https://github.com/qubvel/segmentation_models/issues/15) [37](https://github.com/qubvel/segmentation_models/pull/37) investigation of `align_corners` parameter in `ResizeImage` layer
[NiklasDL](https://github.com/NiklasDL) [29](https://github.com/qubvel/segmentation_models/issues/29) investigation about convolution kernel in PSPNet final layers

Areas of improvement

- Added PSPModel
- Prepocessing functions for all backbones:
python
from segmentation_models.backbones import get_preprocessing

preprocessing_fn = get_preprocessing('resnet34')
X = preprocessing_fn(x)

API changes
- Default param `use_batchnorm=True` for all decoders
- FPN model `Upsample2D` layer renamed to `ResizeImage`

- Added `Linknet` model
- Keras 2.2+ compatibility (fixed import of `_obtain_input_shape`)
- Small code improvements and bug fixes

- `Unet` and `FPN` models