Metadata-Version: 2.1
Name: segmentation-models
Version: 0.1.1
Summary: Image segmentation models with pre-trained backbones with Keras.
Home-page: https://github.com/qubvel/segmentation_models
Author: Pavel Yakubovskiy
Author-email: qubvel@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Python: >=3.6.0
Description-Content-Type: text/markdown


# Segmentation models Zoo
Segmentation models with pretrained backbones

#### Unet and FPN like models
| Backbone model      |Name| Weights    | UNet |  FPN |   LinkNet | 
|---------------------|:--:|:------------:|:------:|:------:|:------:| 
| VGG16               |`vgg16`| `imagenet` | +    | +    | +    | 
| VGG19               |`vgg19`| `imagenet` | +    | +    | +    | 
| ResNet18            |`resnet18`| `imagenet` | +    | +    | +    | 
| ResNet34            |`resnet34`| `imagenet` | +    | +    | +    | 
| ResNet50            |`resnet50`| `imagenet`<br>`imagenet11k-places365ch` | +    | +    |  +    |
| ResNet101           |`resnet101`| `imagenet` | +    | +    |  +    |
| ResNet152           |`resnet152`| `imagenet`<br>`imagenet11k` | +    | +    |  +    |
| ResNeXt50           |`resnext50`| `imagenet` | +    | +    |  +    |
| ResNeXt101          |`resnext101`| `imagenet` | +    | +    |  +    |
| DenseNet121         |`densenet121`| `imagenet` | +    | +    |  +    |
| DenseNet169         |`densenet169`| `imagenet` | +    | +    |  +    |
| DenseNet201         |`densenet201`| `imagenet` | +    | +    |  +    |
| Inception V3        |`inceptionv3`| `imagenet` | +    | +    |  +    |
| Inception ResNet V2 |`inceptionresnetv2`| `imagenet` | +    | +    |  +    |

### Requirements
1) Python 3.6 or higher
2) Keras >=2.1.0
3) Tensorflow >= 1.4

### Installation  

#### Installing via pip  
`$ pip install segmentation_models`

#### Using latest version in your project
```bash
$ git clone https://github.com/qubvel/segmentation_models.git
$ cd segmentation_models
$ git submodule update --init --recursive
```

### Code examples

Train Unet model:  
```python
from segmentation_models import Unet

# prepare data
x, y = ...

# prepare model
model = Unet(backbone_name='resnet34', encoder_weights='imagenet')
model.compile('Adam', 'binary_crossentropy', ['binary_accuracy'])

# train model
model.fit(x, y)
```
Train FPN model:  
```python
from segmentation_models import FPN

model = FPN(backbone_name='resnet34', encoder_weights='imagenet')
```

#### Useful trick
Freeze encoder weights for fine-tuning during first epochs of training:
```python
from segmentation_models import FPN
from segmentation_models.utils import set_trainable

model = FPN(backbone_name='resnet34', encoder_weights='imagenet', freeze_encoder=True)
model.compile('Adam', 'binary_crossentropy', ['binary_accuracy'])

# pretrain model decoder
model.fit(x, y, epochs=2)

# release all layers for training
set_trainable(model) # set all layers trainable and recompile model

# continue training
model.fit(x, y, epochs=100)
```

### TODO
- [x] Update Unet API
- [x] Update FPN API
- [x] Add Linknet models
- [ ] Add PSP models
- [ ] Add DPN backbones

### Change Log

**Version 0.1.1**  
 - Added `Linknet` model
 - Keras 2.2+ compatibility (fixed import of `_obtain_input_shape`)
 - Small code improvements and bug fixes

**Version 0.1.0**  
 - `Unet` and `FPN` models


