VGG16 name normalization

README.md

@@ -21,13 +21,13 @@
 Train a Fast R-CNN detector. For example, train a VGG 16 network on VOC 2007 trainval:
 
 ```
-./tools/train_net.py --gpu 0 --solver models/VGG_16/solver.prototxt --weights /data/reference_caffe_nets/VGG_ILSVRC_16_layers.v2.caffemodel
+./tools/train_net.py --gpu 0 --solver models/VGG16/solver.prototxt --weights data/imagenet_models/VGG16.v2.caffemodel
 ```
 
 Test a Fast R-CNN detector. For example, test the VGG 16 network on VOC 2007 test:
 
 ```
-./tools/test_net.py --gpu 1 --def models/VGG_16/test.prototxt --net snapshots/vgg16_fast_rcnn_iter_40000.caffemodel
+./tools/test_net.py --gpu 1 --def models/VGG16/test.prototxt --net output/voc_2007_trainval/vgg16_fast_rcnn_iter_40000.caffemodel
 ```
 
 Test output is written underneath `$FRCNN/output`.
@@ -35,5 +35,5 @@ Test output is written underneath `$FRCNN/output`.
 Compress a Fast R-CNN model using SVD on the fully-connected layers:
 
 ```
-./tools/compress_model.py --def models/VGG_16/test.prototxt --def-svd models/VGG_16/compressed/test.prototxt --net snapshots/vgg16_fast_rcnn_iter_40000.caffemodel
+./tools/compress_model.py --def models/VGG16/test.prototxt --def-svd models/VGG16/compressed/test.prototxt --net output/voc_2007_trainval/vgg16_fast_rcnn_iter_40000.caffemodel
 ```

experiments/scripts/default_vgg16.sh

@@ -11,7 +11,7 @@ echo Logging output to "$LOG"
 
 time ./tools/train_net.py --gpu $1 \
   --solver models/VGG16/solver.prototxt \
-  --weights data/imagenet_models/VGG_ILSVRC_16_layers.v2.caffemodel \
+  --weights data/imagenet_models/VGG16.v2.caffemodel \
   --imdb voc_2007_trainval
 
 time ./tools/test_net.py --gpu $1 \

experiments/scripts/no_bbox_reg_vgg16.sh

@@ -11,7 +11,7 @@ echo Logging output to "$LOG"
 
 time ./tools/train_net.py --gpu $1 \
   --solver models/VGG16/no_bbox_reg/solver.prototxt \
-  --weights data/imagenet_models/VGG_ILSVRC_16_layers.v2.caffemodel \
+  --weights data/imagenet_models/VGG16.v2.caffemodel \
   --imdb voc_2007_trainval \
   --cfg experiments/cfgs/no_bbox_reg.yml
 

lib/fast_rcnn/config.py

@@ -106,11 +106,11 @@ __C.TEST.BBOX_REG = True
 # some boxes that are distinct in image space to become identical in feature
 # coordinates. If DEDUP_BOXES > 0, then DEDUP_BOXES is used as the scale factor
 # for identifying duplicate boxes.
-# 1/16 is correct for {Alex,Caffe}Net, VGG_CNN_M_1024, and VGG_16
+# 1/16 is correct for {Alex,Caffe}Net, VGG_CNN_M_1024, and VGG16
 __C.DEDUP_BOXES = 1./16.
 
 # Pixel mean values (BGR order) as a (1, 1, 3) array
-# These are the values originally used for training VGG_16
+# These are the values originally used for training VGG16
 __C.PIXEL_MEANS = np.array([[[102.9801, 115.9465, 122.7717]]])
 
 # For reproducibility

models/VGG16/fc_only/solver.prototxt

-train_net: "models/VGG_16/fc_only/train.prototxt"
+train_net: "models/VGG16/fc_only/train.prototxt"
 base_lr: 0.001
 lr_policy: "step"
 gamma: 0.1

models/VGG16/no_bbox_reg/solver.prototxt

-train_net: "models/VGG_16/no_bbox_reg/train.prototxt"
+train_net: "models/VGG16/no_bbox_reg/train.prototxt"
 base_lr: 0.001
 lr_policy: "step"
 gamma: 0.1

models/VGG16/piecewise/solver.prototxt

-train_net: "models/VGG_16/piecewise/train.prototxt"
+train_net: "models/VGG16/piecewise/train.prototxt"
 base_lr: 0.001
 lr_policy: "step"
 gamma: 0.1

models/VGG16/solver.prototxt

-train_net: "models/VGG_16/train.prototxt"
+train_net: "models/VGG16/train.prototxt"
 base_lr: 0.001
 lr_policy: "step"
 gamma: 0.1

tools/compress_net.py

@@ -62,11 +62,11 @@ def compress_weights(W, l):
 def main():
     args = parse_args()
 
-    # prototxt = 'models/VGG_16/test.prototxt'
+    # prototxt = 'models/VGG16/test.prototxt'
     # caffemodel = 'snapshots/vgg16_fast_rcnn_iter_40000.caffemodel'
     net = caffe.Net(args.prototxt, args.caffemodel, caffe.TEST)
 
-    # prototxt_svd = 'models/VGG_16/svd/test_fc6_fc7.prototxt'
+    # prototxt_svd = 'models/VGG16/svd/test_fc6_fc7.prototxt'
     # caffemodel = 'snapshots/vgg16_fast_rcnn_iter_40000.caffemodel'
     net_svd = caffe.Net(args.prototxt_svd, args.caffemodel, caffe.TEST)