BVLC · shelhamer · Aug 29, 2014 · Aug 28, 2014 · Aug 28, 2014
diff --git a/.gitignore b/.gitignore
@@ -47,11 +47,16 @@ python/caffe/proto/
 # User's build configuration
 Makefile.config
 
-# Data and examples are either
+# Data and models are either
 # 1. reference, and not casually committed
 # 2. custom, and live on their own unless they're deliberated contributed
 data/*
-examples/*
+*model
+*_iter_*
+*.solverstate
+*.binaryproto
+*leveldb
+*lmdb
 
 # Generated documentation
 docs/_site

diff --git a/examples/cifar10/cifar10_full_solver.prototxt b/examples/cifar10/cifar10_full_solver.prototxt
@@ -2,7 +2,7 @@
 # then another factor of 10 after 10 more epochs (5000 iters)
 
 # The train/test net protocol buffer definition
-net: "cifar10_full_train_test.prototxt"
+net: "examples/cifar10/cifar10_full_train_test.prototxt"
 # test_iter specifies how many forward passes the test should carry out.
 # In the case of CIFAR10, we have test batch size 100 and 100 test iterations,
 # covering the full 10,000 testing images.
@@ -21,6 +21,6 @@ display: 200
 max_iter: 60000
 # snapshot intermediate results
 snapshot: 10000
-snapshot_prefix: "cifar10_full"
+snapshot_prefix: "examples/cifar10/cifar10_full"
 # solver mode: CPU or GPU
 solver_mode: GPU
diff --git a/examples/cifar10/cifar10_full_solver_lr1.prototxt b/examples/cifar10/cifar10_full_solver_lr1.prototxt
@@ -2,7 +2,7 @@
 # then another factor of 10 after 10 more epochs (5000 iters)
 
 # The train/test net protocol buffer definition
-net: "cifar10_full_train_test.prototxt"
+net: "examples/cifar10/cifar10_full_train_test.prototxt"
 # test_iter specifies how many forward passes the test should carry out.
 # In the case of CIFAR10, we have test batch size 100 and 100 test iterations,
 # covering the full 10,000 testing images.
@@ -21,6 +21,6 @@ display: 200
 max_iter: 65000
 # snapshot intermediate results
 snapshot: 5000
-snapshot_prefix: "cifar10_full"
+snapshot_prefix: "examples/cifar10/cifar10_full"
 # solver mode: CPU or GPU
 solver_mode: GPU
diff --git a/examples/cifar10/cifar10_full_solver_lr2.prototxt b/examples/cifar10/cifar10_full_solver_lr2.prototxt
@@ -2,7 +2,7 @@
 # then another factor of 10 after 10 more epochs (5000 iters)
 
 # The train/test net protocol buffer definition
-net: "cifar10_full_train_test.prototxt"
+net: "examples/cifar10/cifar10_full_train_test.prototxt"
 # test_iter specifies how many forward passes the test should carry out.
 # In the case of CIFAR10, we have test batch size 100 and 100 test iterations,
 # covering the full 10,000 testing images.
@@ -21,6 +21,6 @@ display: 200
 max_iter: 70000
 # snapshot intermediate results
 snapshot: 5000
-snapshot_prefix: "cifar10_full"
+snapshot_prefix: "examples/cifar10/cifar10_full"
 # solver mode: CPU or GPU
 solver_mode: GPU
diff --git a/examples/cifar10/cifar10_full_train_test.prototxt b/examples/cifar10/cifar10_full_train_test.prototxt
@@ -5,10 +5,10 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "cifar10-leveldb/cifar-train-leveldb"
+    source: "examples/cifar10/cifar10_train_leveldb"
     batch_size: 100
     transform_param {
-      mean_file: "mean.binaryproto"
+      mean_file: "examples/cifar10/mean.binaryproto"
     }
   }
   include: { phase: TRAIN }
@@ -19,10 +19,10 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "cifar10-leveldb/cifar-test-leveldb"
+    source: "examples/cifar10/cifar10_test_leveldb"
     batch_size: 100
     transform_param {
-      mean_file: "mean.binaryproto"
+      mean_file: "examples/cifar10/mean.binaryproto"
     }
   }
   include: { phase: TEST }

diff --git a/examples/cifar10/cifar10_quick_solver.prototxt b/examples/cifar10/cifar10_quick_solver.prototxt
@@ -1,7 +1,7 @@
 # reduce the learning rate after 8 epochs (4000 iters) by a factor of 10
 
 # The train/test net protocol buffer definition
-net: "cifar10_quick_train_test.prototxt"
+net: "examples/cifar10/cifar10_quick_train_test.prototxt"
 # test_iter specifies how many forward passes the test should carry out.
 # In the case of MNIST, we have test batch size 100 and 100 test iterations,
 # covering the full 10,000 testing images.
@@ -20,6 +20,6 @@ display: 100
 max_iter: 4000
 # snapshot intermediate results
 snapshot: 4000
-snapshot_prefix: "cifar10_quick"
+snapshot_prefix: "examples/cifar10/cifar10_quick"
 # solver mode: CPU or GPU
 solver_mode: GPU
diff --git a/examples/cifar10/cifar10_quick_solver_lr1.prototxt b/examples/cifar10/cifar10_quick_solver_lr1.prototxt
@@ -1,7 +1,7 @@
 # reduce the learning rate after 8 epochs (4000 iters) by a factor of 10
 
 # The train/test net protocol buffer definition
-net: "cifar10_quick_train_test.prototxt"
+net: "examples/cifar10/cifar10_quick_train_test.prototxt"
 # test_iter specifies how many forward passes the test should carry out.
 # In the case of MNIST, we have test batch size 100 and 100 test iterations,
 # covering the full 10,000 testing images.
@@ -20,6 +20,6 @@ display: 100
 max_iter: 5000
 # snapshot intermediate results
 snapshot: 5000
-snapshot_prefix: "cifar10_quick"
+snapshot_prefix: "examples/cifar10/cifar10_quick"
 # solver mode: CPU or GPU
 solver_mode: GPU
diff --git a/examples/cifar10/cifar10_quick_train_test.prototxt b/examples/cifar10/cifar10_quick_train_test.prototxt
@@ -5,10 +5,10 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "cifar10-leveldb/cifar-train-leveldb"
+    source: "examples/cifar10/cifar10_train_leveldb"
     batch_size: 100
     transform_param {
-      mean_file: "mean.binaryproto"
+      mean_file: "examples/cifar10/mean.binaryproto"
     }
   }
   include: { phase: TRAIN }
@@ -19,10 +19,10 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "cifar10-leveldb/cifar-test-leveldb"
+    source: "examples/cifar10/cifar10_test_leveldb"
     batch_size: 100
     transform_param {
-      mean_file: "mean.binaryproto"
+      mean_file: "examples/cifar10/mean.binaryproto"
     }
   }
   include: { phase: TEST }

diff --git a/examples/cifar10/convert_cifar_data.cpp b/examples/cifar10/convert_cifar_data.cpp
@@ -48,7 +48,7 @@ void convert_dataset(const string& input_folder, const string& output_folder) {
   LOG(INFO) << "Writing Training data";
   leveldb::DB* train_db;
   leveldb::Status status;
-  status = leveldb::DB::Open(options, output_folder + "/cifar-train-leveldb",
+  status = leveldb::DB::Open(options, output_folder + "/cifar10_train_leveldb",
       &train_db);
   CHECK(status.ok()) << "Failed to open leveldb.";
   for (int fileid = 0; fileid < kCIFARTrainBatches; ++fileid) {
@@ -71,7 +71,7 @@ void convert_dataset(const string& input_folder, const string& output_folder) {
 
   LOG(INFO) << "Writing Testing data";
   leveldb::DB* test_db;
-  CHECK(leveldb::DB::Open(options, output_folder + "/cifar-test-leveldb",
+  CHECK(leveldb::DB::Open(options, output_folder + "/cifar10_test_leveldb",
       &test_db).ok()) << "Failed to open leveldb.";
   // Open files
   std::ifstream data_file((input_folder + "/test_batch.bin").c_str(),

diff --git a/examples/cifar10/create_cifar10.sh b/examples/cifar10/create_cifar10.sh
@@ -1,19 +1,18 @@
 #!/usr/bin/env sh
 # This script converts the cifar data into leveldb format.
 
-EXAMPLES=../../build/examples/cifar10
-DATA=../../data/cifar10
-TOOLS=../../build/tools
+EXAMPLE=examples/cifar10
+DATA=data/cifar10
 
 echo "Creating leveldb..."
 
-rm -rf cifar10-leveldb
-mkdir cifar10-leveldb
+rm -rf $EXAMPLE/cifar10_train_leveldb $EXAMPLE/cifar10_test_leveldb
 
-$EXAMPLES/convert_cifar_data.bin $DATA ./cifar10-leveldb
+./build/examples/cifar10/convert_cifar_data.bin $DATA $EXAMPLE
 
 echo "Computing image mean..."
 
-$TOOLS/compute_image_mean.bin ./cifar10-leveldb/cifar-train-leveldb mean.binaryproto
+./build/tools/compute_image_mean $EXAMPLE/cifar10_train_leveldb \
+  $EXAMPLE/mean.binaryproto
 
 echo "Done."
diff --git a/examples/finetune_pascal_detection/pascal_finetune_solver.prototxt b/examples/finetune_pascal_detection/pascal_finetune_solver.prototxt
@@ -0,0 +1,14 @@
+train_net: "examples/finetuning_pascal_detection/pascal_finetune_train.prototxt"
+test_net: "examples/finetuning_pascal_detection/pascal_finetune_val.prototxt"
+test_iter: 100
+test_interval: 1000
+base_lr: 0.001
+lr_policy: "step"
+gamma: 0.1
+stepsize: 20000
+display: 20
+max_iter: 100000
+momentum: 0.9
+weight_decay: 0.0005
+snapshot: 10000
+snapshot_prefix: "examples/finetuning_pascal_detection/pascal_det_finetune"
diff --git a/...finetuning/pascal_finetune_train.prototxt → ..._detection/pascal_finetune_train.prototxt b/...finetuning/pascal_finetune_train.prototxt → ..._detection/pascal_finetune_train.prototxt
@@ -5,8 +5,8 @@ layers {
   top: "data"
   top: "label"
   window_data_param {
-    source: "window_file_2007_trainval.txt"
-    mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
+    source: "examples/finetune_pascal_detection/window_file_2007_trainval.txt"
+    mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
     batch_size: 128
     crop_size: 227
     mirror: true

diff --git a/...l-finetuning/pascal_finetune_val.prototxt → ...al_detection/pascal_finetune_val.prototxt b/...l-finetuning/pascal_finetune_val.prototxt → ...al_detection/pascal_finetune_val.prototxt
@@ -5,8 +5,8 @@ layers {
   top: "data"
   top: "label"
   window_data_param {
-    source: "window_file_2007_test.txt"
-    mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
+    source: "examples/finetune_pascal_detection/window_file_2007_test.txt"
+    mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
     batch_size: 128
     crop_size: 227
     mirror: true

diff --git a/examples/imagenet/alexnet_solver.prototxt b/examples/imagenet/alexnet_solver.prototxt
@@ -1,4 +1,4 @@
-net: "alexnet_train_val.prototxt"
+net: "examples/imagenet/alexnet_train_val.prototxt"
 test_iter: 1000
 test_interval: 1000
 base_lr: 0.01
@@ -10,5 +10,5 @@ max_iter: 450000
 momentum: 0.9
 weight_decay: 0.0005
 snapshot: 10000
-snapshot_prefix: "caffe_alexnet_train"
+snapshot_prefix: "examples/imagenet/caffe_alexnet"
 solver_mode: GPU
diff --git a/examples/imagenet/alexnet_train_val.prototxt b/examples/imagenet/alexnet_train_val.prototxt
@@ -5,11 +5,11 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "ilsvrc12_train_leveldb"
+    source: "examples/imagenet/ilsvrc12_train_leveldb"
     batch_size: 256
     transform_param {
       crop_size: 227
-      mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
+      mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
       mirror: true
     }
   }
@@ -21,11 +21,11 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "ilsvrc12_val_leveldb"
+    source: "examples/imagenet/ilsvrc12_val_leveldb"
     batch_size: 50
     transform_param {
       crop_size: 227
-      mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
+      mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
       mirror: false
     }
   }

diff --git a/examples/imagenet/create_imagenet.sh b/examples/imagenet/create_imagenet.sh
@@ -2,8 +2,9 @@
 # Create the imagenet leveldb inputs
 # N.B. set the path to the imagenet train + val data dirs
 
-TOOLS=../../build/tools
-DATA=../../data/ilsvrc12
+EXAMPLE=examples/imagenet
+DATA=data/ilsvrc12
+TOOLS=build/tools
 
 TRAIN_DATA_ROOT=/path/to/imagenet/train/
 VAL_DATA_ROOT=/path/to/imagenet/val/
@@ -35,22 +36,22 @@ fi
 
 echo "Creating train leveldb..."
 
-GLOG_logtostderr=1 $TOOLS/convert_imageset.bin \
+GLOG_logtostderr=1 $TOOLS/convert_imageset \
     --resize_height=$RESIZE_HEIGHT \
     --resize_width=$RESIZE_WIDTH \
     --shuffle \
     $TRAIN_DATA_ROOT \
     $DATA/train.txt \
-    ilsvrc12_train_leveldb
+    $EXAMPLE/ilsvrc12_train_leveldb
 
 echo "Creating val leveldb..."
 
-GLOG_logtostderr=1 $TOOLS/convert_imageset.bin \
+GLOG_logtostderr=1 $TOOLS/convert_imageset \
     --resize_height=$RESIZE_HEIGHT \
     --resize_width=$RESIZE_WIDTH \
     --shuffle \
     $VAL_DATA_ROOT \
     $DATA/val.txt \
-    ilsvrc12_val_leveldb
+    $EXAMPLE/ilsvrc12_val_leveldb
 
 echo "Done."
diff --git a/examples/imagenet/get_caffe_alexnet_model.sh b/examples/imagenet/get_caffe_alexnet_model.sh
@@ -23,6 +23,6 @@ fi
 
 echo "Downloading..."
 
-wget http://dl.caffe.berkeleyvision.org/caffe_alexnet_model
+wget http://dl.caffe.berkeleyvision.org/$MODEL examples/imagenet/$MODEL
 
 echo "Done. Please run this command again to verify that checksum = $CHECKSUM."
diff --git a/examples/imagenet/get_caffe_rcnn_imagenet_model.sh b/examples/imagenet/get_caffe_rcnn_imagenet_model.sh
@@ -23,5 +23,6 @@ fi
 
 echo "Downloading..."
 
-wget http://dl.caffe.berkeleyvision.org/$MODEL
+wget http://dl.caffe.berkeleyvision.org/$MODEL examples/imagenet/$MODEL
+
 echo "Done. Please run this command again to verify that checksum = $CHECKSUM."
diff --git a/examples/imagenet/get_caffe_reference_imagenet_model.sh b/examples/imagenet/get_caffe_reference_imagenet_model.sh
@@ -23,6 +23,6 @@ fi
 
 echo "Downloading..."
 
-wget http://dl.caffe.berkeleyvision.org/$MODEL
+wget http://dl.caffe.berkeleyvision.org/$MODEL examples/imagenet/$MODEL
 
 echo "Done. Please run this command again to verify that checksum = $CHECKSUM."
diff --git a/examples/imagenet/imagenet_solver.prototxt b/examples/imagenet/imagenet_solver.prototxt
@@ -1,4 +1,4 @@
-net: "imagenet_train_val.prototxt"
+net: "examples/imagenet/imagenet_train_val.prototxt"
 test_iter: 1000
 test_interval: 1000
 base_lr: 0.01
@@ -10,5 +10,5 @@ max_iter: 450000
 momentum: 0.9
 weight_decay: 0.0005
 snapshot: 10000
-snapshot_prefix: "caffe_imagenet_train"
+snapshot_prefix: "examples/imagenet/caffe_imagenet"
 solver_mode: GPU
diff --git a/examples/imagenet/imagenet_train_val.prototxt b/examples/imagenet/imagenet_train_val.prototxt
@@ -5,11 +5,11 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "ilsvrc12_train_leveldb"
+    source: "examples/imagenet/ilsvrc12_train_leveldb"
     batch_size: 256
     transform_param {
       crop_size: 227
-      mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
+      mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
       mirror: true
     }
   }
@@ -21,11 +21,11 @@ layers {
   top: "data"
   top: "label"
   data_param {
-    source: "ilsvrc12_val_leveldb"
+    source: "examples/imagenet/ilsvrc12_val_leveldb"
     batch_size: 50
     transform_param {
       crop_size: 227
-      mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto"
+      mean_file: "data/ilsvrc12/imagenet_mean.binaryproto"
       mirror: false
     }
   }

diff --git a/examples/imagenet/make_imagenet_mean.sh b/examples/imagenet/make_imagenet_mean.sh
@@ -2,9 +2,7 @@
 # Compute the mean image from the imagenet training leveldb
 # N.B. this is available in data/ilsvrc12
 
-TOOLS=../../build/tools
-DATA=../../data/ilsvrc12
-
-$TOOLS/compute_image_mean.bin ilsvrc12_train_leveldb $DATA/imagenet_mean.binaryproto
+./build/tools/compute_image_mean examples/imagenet/ilsvrc12_train_leveldb \
+  data/ilsvrc12/imagenet_mean.binaryproto
 
 echo "Done."