Merge branch 'xjdeng_patch-1'

README.md

@@ -17,21 +17,14 @@ Tested on:
 
 ## Usage
 
-### Use pretrained model
-Download pretrained model weights for TensorFlow backend:
-
-```sh
-mkdir -p pretrained_models
-wget -P pretrained_models https://www.dropbox.com/s/rf8hgoev8uqjv3z/weights.18-4.06.hdf5
-```
-
-Run demo script (requires web cam)
+### Use pretrained model for demo
+Run demo the script (requires web cam)
 
 ```sh
 python3 demo.py
 ```
 
-Model weights for Theano backend is also available from [here](https://drive.google.com/file/d/0B_cG1nzvVZlQWGJMc2JjdzkwcVk/view?usp=sharing).
+The pretrained model for TensorFlow backend will be automatically downloaded to the `pretrained_models` directory.
 
 ### Train a model using the IMDB-WIKI dataset
 

demo.py

@@ -4,6 +4,10 @@
 import numpy as np
 import argparse
 from wide_resnet import WideResNet
+from keras.utils.data_utils import get_file
+
+pretrained_model = "https://www.dropbox.com/s/rf8hgoev8uqjv3z/weights.18-4.06.hdf5?dl=1"
+modhash = '89f56a39a78454e96379348bddd78c0d'
 
 
 def get_args():
@@ -35,7 +39,8 @@ def main():
     weight_file = args.weight_file
 
     if not weight_file:
-        weight_file = os.path.join("pretrained_models", "weights.18-4.06.hdf5")
+        weight_file = get_file("weights.18-4.06.hdf5", pretrained_model, cache_subdir="pretrained_models",
+                               file_hash=modhash, cache_dir=os.path.dirname(os.path.abspath(__file__)))
 
     # for face detection
     detector = dlib.get_frontal_face_detector()