Consolidate weights files

Author: fchollet

keras/applications/densenet.py

@@ -38,12 +38,12 @@
 from .imagenet_utils import _obtain_input_shape
 
 
-DENSENET121_WEIGHT_PATH = 'https://github.com/taehoonlee/deep-learning-models/releases/download/densenet/densenet121_weights_tf_dim_ordering_tf_kernels.h5'
-DENSENET121_WEIGHT_PATH_NO_TOP = 'https://github.com/taehoonlee/deep-learning-models/releases/download/densenet/densenet121_weights_tf_dim_ordering_tf_kernels_notop.h5'
-DENSENET169_WEIGHT_PATH = 'https://github.com/taehoonlee/deep-learning-models/releases/download/densenet/densenet169_weights_tf_dim_ordering_tf_kernels.h5'
-DENSENET169_WEIGHT_PATH_NO_TOP = 'https://github.com/taehoonlee/deep-learning-models/releases/download/densenet/densenet169_weights_tf_dim_ordering_tf_kernels_notop.h5'
-DENSENET201_WEIGHT_PATH = 'https://github.com/taehoonlee/deep-learning-models/releases/download/densenet/densenet201_weights_tf_dim_ordering_tf_kernels.h5'
-DENSENET201_WEIGHT_PATH_NO_TOP = 'https://github.com/taehoonlee/deep-learning-models/releases/download/densenet/densenet201_weights_tf_dim_ordering_tf_kernels_notop.h5'
+DENSENET121_WEIGHT_PATH = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.8/densenet121_weights_tf_dim_ordering_tf_kernels.h5'
+DENSENET121_WEIGHT_PATH_NO_TOP = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.8/densenet121_weights_tf_dim_ordering_tf_kernels_notop.h5'
+DENSENET169_WEIGHT_PATH = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.8/densenet169_weights_tf_dim_ordering_tf_kernels.h5'
+DENSENET169_WEIGHT_PATH_NO_TOP = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.8/densenet169_weights_tf_dim_ordering_tf_kernels_notop.h5'
+DENSENET201_WEIGHT_PATH = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.8/densenet201_weights_tf_dim_ordering_tf_kernels.h5'
+DENSENET201_WEIGHT_PATH_NO_TOP = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.8/densenet201_weights_tf_dim_ordering_tf_kernels_notop.h5'
 
 
 def dense_block(x, blocks, name):

keras/applications/nasnet.py

@@ -60,10 +60,10 @@
 from ..applications.imagenet_utils import decode_predictions
 from .. import backend as K
 
-NASNET_MOBILE_WEIGHT_PATH = 'https://github.com/titu1994/Keras-NASNet/releases/download/v1.2/NASNet-mobile.h5'
-NASNET_MOBILE_WEIGHT_PATH_NO_TOP = 'https://github.com/titu1994/Keras-NASNet/releases/download/v1.2/NASNet-mobile-no-top.h5'
-NASNET_LARGE_WEIGHT_PATH = 'https://github.com/titu1994/Keras-NASNet/releases/download/v1.2/NASNet-large.h5'
-NASNET_LARGE_WEIGHT_PATH_NO_TOP = 'https://github.com/titu1994/Keras-NASNet/releases/download/v1.2/NASNet-large-no-top.h5'
+NASNET_MOBILE_WEIGHT_PATH = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.8/NASNet-mobile.h5'
+NASNET_MOBILE_WEIGHT_PATH_NO_TOP = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.8/NASNet-mobile-no-top.h5'
+NASNET_LARGE_WEIGHT_PATH = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.8/NASNet-large.h5'
+NASNET_LARGE_WEIGHT_PATH_NO_TOP = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.8/NASNet-large-no-top.h5'
 
 
 def NASNet(input_shape=None,