Update dependencies.

README.md

@@ -188,7 +188,7 @@ Keras uses the following dependencies:
 - Theano
     - See installation instructions: http://deeplearning.net/software/theano/install.html#install
 
-- PIL (optional, required if you use preprocessing.image)
+- h5py (optional, required if you use model saving/loading functions)
 
 - Optional but recommended if you use CNNs: cuDNN.
 

docs/sources/index.md

@@ -92,7 +92,7 @@ Keras uses the following dependencies:
 - numpy, scipy
 - Theano
     - See [installation instructions](http://deeplearning.net/software/theano/install.html#install).
-- PIL (optional, required if you use preprocessing.image)
+- h5py (optional, required if you use model saving/loading functions)
 - Optional but recommended if you use CNNs: cuDNN.
 
 Once you have the dependencies installed, clone the repo:

docs/sources/models.md

@@ -32,7 +32,7 @@ model = keras.models.Sequential()
     - __train__(X, y, accuracy=False): Single gradient update on one batch. if accuracy==False, return tuple (loss_on_batch, accuracy_on_batch). Else, return loss_on_batch.
     - __test__(X, y, accuracy=False): Single performance evaluation on one batch. if accuracy==False, return tuple (loss_on_batch, accuracy_on_batch). Else, return loss_on_batch.
     - __save_weights__(fname): Store the weights of all layers to a HDF5 file. 
-    - __load_weights__(fname): Sets the weights of a model, based to weights stored by __save__weights__. You can only __load__weights__ on a savefile from a model with an identical architecture. __save__weights__ can be called either before or after the __compile__ step.
+    - __load_weights__(fname): Sets the weights of a model, based to weights stored by __save__weights__. You can only __load__weights__ on a savefile from a model with an identical architecture. __load_weights__ can be called either before or after the __compile__ step.
 
 __Examples__:
 

setup.py

@@ -8,6 +8,6 @@
       author_email='[email protected]',
       url='https://github.com/fchollet/keras',
       license='MIT',
+      install_requires=['theano', 'h5py'],
       packages=find_packages(),
-      # TODO: dependencies
 )