model-defs -> models

experiments/test_net.py

@@ -4,7 +4,7 @@ import fast_rcnn_test
 import caffe
 
 if __name__ == '__main__':
-    prototxt = 'model-defs/vgg16_bbox_reg_deploy.prototxt'
+    prototxt = 'models/vgg16_bbox_reg_deploy.prototxt'
     caffemodel = 'snapshots/vgg16_finetune_joint_flipped_iter_40000.caffemodel'
     GPU_ID = 2
 

fast_rcnn_train.py

@@ -175,10 +175,10 @@ if __name__ == '__main__':
         bbox_regression_targets.append_bbox_regression_targets(roidb_train)
 
     # CAFFE_MODEL = '/data/reference_caffe_nets/ilsvrc_2012_train_iter_310k'
-    # SOLVER_DEF = './model-defs/pyramid_solver.prototxt'
+    # SOLVER_DEF = './models/pyramid_solver.prototxt'
     CAFFE_MODEL = '/data/reference_caffe_nets/VGG_ILSVRC_16_layers.caffemodel'
     if args.solver is None:
-        args.solver = './model-defs/vgg16_solver.prototxt'
+        args.solver = './models/vgg16_solver.prototxt'
 
     print 'Solving...'
     sw = SolverWrapper(args.solver, pretrained_model=CAFFE_MODEL)

model-defs/pyramid_solver.prototxt

-train_net: "model-defs/pyramid.prototxt"
-#test_iter: 100
-#test_interval: 1000
-base_lr: 0.001
-lr_policy: "step"
-gamma: 0.1
-stepsize: 30000
-display: 20
-average_loss: 20
-max_iter: 500000
-momentum: 0.9
-weight_decay: 0.0005
-snapshot: 10000
-snapshot_prefix: "snapshots/pyramid_finetune"

model-defs/vgg16_solver.prototxt → models/vgg16_solver.prototxt

-#train_net: "model-defs/vgg16.prototxt"
-train_net: "model-defs/vgg16_bbox_reg.prototxt"
+#train_net: "models/vgg16.prototxt"
+train_net: "models/vgg16_bbox_reg.prototxt"
 base_lr: 0.001
 lr_policy: "step"
 gamma: 0.1