From 4e36f3f35e383eb0909b680a1a117724508eae18 Mon Sep 17 00:00:00 2001 From: nttstar Date: Fri, 17 Nov 2017 14:56:06 +0800 Subject: [PATCH] tiny --- src/data.py | 2 +- src/train_softmax.py | 5 +++-- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/src/data.py b/src/data.py index c1e23f1..0e64edd 100644 --- a/src/data.py +++ b/src/data.py @@ -557,7 +557,7 @@ class FaceImageIter2(io.DataIter): _data = mx.ndarray.flip(data=_data, axis=1) if self.nd_mean is not None: _data = _data.astype('float32') - _data -= self.nd_mean + _data -= self.nd_mean _data *= 0.0078125 #_npdata = _data.asnumpy() #if landmark is not None: diff --git a/src/train_softmax.py b/src/train_softmax.py index d5d2ab2..061ff03 100644 --- a/src/train_softmax.py +++ b/src/train_softmax.py @@ -303,7 +303,8 @@ def train_net(args): data_shape = (args.image_channel,112,96) mean = [127.5,127.5,127.5] - if args.network[0]=='m' and args.num_layers==27: + #if args.network[0]=='m' and args.num_layers==27: + if args.network[0]=='m': mean = None if args.use_val: @@ -588,7 +589,7 @@ def train_net(args): #lr_steps = [40000, 70000, 90000] lr_steps = [30000, 50000, 70000, 90000] if args.loss_type==1: - lr_steps = [70000, 100000] + lr_steps = [100000, 140000, 160000] else: lr_steps = [int(x) for x in args.lr_steps.split(',')] print('lr_steps', lr_steps)