Start adding optimise step to unsupervised train, add demo to main

main.py

@@ -1,4 +1,6 @@
 import fast_depth_functional as fd
+from unsupervised.models import pose_net, wrap_mobilenet_nnconv5_for_utrain
+from unsupervised.train import UnsupervisedPoseDepthLearner
 
 if __name__ == '__main__':
     fd.fix_windows_gpu()
@@ -9,3 +11,11 @@ if __name__ == '__main__':
 
     # Save in Tensorflow SavedModel format
     # tf.saved_model.save(model, 'fast_depth_nyu_v2_224_224_3_e1_saved_model')
+
+    # Unsupervised
+    depth_model = fd.mobilenet_nnconv5()
+    pose_model = pose_net()
+    model = UnsupervisedPoseDepthLearner(wrap_mobilenet_nnconv5_for_utrain(depth_model), pose_model)
+    model.compile(optimizer='adam')
+    # TODO: Incorporate data generator
+    # model.fit()