add copyright notices in files

README.md

@@ -161,10 +161,10 @@ As an example, let's see how you would fine-tune a CNN for detection on PASCAL V
   0. Change directories to `external/caffe/examples/pascal-finetuning`
   0. Execute the fine-tuning code (make sure to replace `/path/to/rcnn` with the actual path to where R-CNN is installed):
   
-<pre>
-GLOG_logtostderr=1 ../../build/tools/finetune_net.bin \
-pascal_finetune_solver.prototxt \
-/path/to/rcnn/data/caffe_nets/ilsvrc_2012_train_iter_310k 2>&1 | tee log.txt
-</pre>
+  <pre>
+  GLOG_logtostderr=1 ../../build/tools/finetune_net.bin \
+  pascal_finetune_solver.prototxt \
+  /path/to/rcnn/data/caffe_nets/ilsvrc_2012_train_iter_310k 2>&1 | tee log.txt
+  </pre>
       
 **Note:** In my experiments, I've let fine-tuning run for 70k iterations, although with hindsight it appears that improvement in mAP saturates at around 40k iterations.

bbox_regression/rcnn_predict_bbox_regressor.m

@@ -11,6 +11,16 @@ function pred_boxes = ...
 %   Outputs
 %   pred_boxes  Modified (hopefully better) ex_boxes
 
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
+
 if isempty(ex_boxes)
   pred_boxes = [];
   return;

bbox_regression/rcnn_test_bbox_regressor.m

 function res = rcnn_test_bbox_regressor(imdb, rcnn_model, bbox_reg, suffix)
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
 
 conf = rcnn_config('sub_dir', imdb.name);
 image_ids = imdb.image_ids;

bbox_regression/rcnn_train_bbox_regressor.m

 function bbox_reg = rcnn_train_bbox_regressor(imdb, rcnn_model, varargin)
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
 
 ip = inputParser;
 ip.addRequired('imdb',       @isstruct);

bbox_regression/vis_debug_bbox_pred.m

 function vis_debug_bbox_pred(imdb, rcnn_model, bbox_reg, cls)
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
 
 image_ids = imdb.image_ids;
 min_overlap = 0.3;

finetuning/rcnn_make_window_file.m

@@ -2,6 +2,16 @@ function rcnn_make_window_file(imdb, out_dir)
 % Makes a window file that can be used by the caffe WindowDataLayer for
 % finetuning.
 
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
+
 roidb = imdb.roidb_func(imdb);
 
 % window_file format

finetuning/voc_2007_prototxt/pascal_finetune_solver.prototxt

@@ -11,4 +11,4 @@ max_iter: 100000
 momentum: 0.9
 weight_decay: 0.0005
 snapshot: 10000
-snapshot_prefix: "./snapshots/v1/finetune_voc_2007_trainval"
+snapshot_prefix: "finetune_voc_2007_trainval"

rcnn_cache_pool5_features.m

 function rcnn_cache_pool5_features(imdb, varargin)
 
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
+
+
 ip = inputParser;
 ip.addRequired('imdb', @isstruct);
 ip.addOptional('start', 1, @isscalar);

rcnn_create_model.m

 function rcnn_model = rcnn_create_model(cnn_definition_file, cnn_binary_file, cache_name)
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
 
 if ~exist('cache_name', 'var') || isempty(cache_name)
   cache_name = 'none';

rcnn_detect.m

 function dets = rcnn_detect(im, rcnn_model)
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
 
 % compute selective search candidates
 fprintf('Computing candidate regions...');

rcnn_extract_regions.m

@@ -5,6 +5,16 @@ function [batches, batch_padding] = rcnn_extract_regions(im, boxes, rcnn_model)
 % (format: BGR channel order; single precision; mean subtracted;
 %  dimensions from fastest to slowest: width, height, channels, batch_index)
 
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
+
 % convert image to BGR and single
 im = single(im(:,:,[3 2 1]));
 num_boxes = size(boxes, 1);

rcnn_feature_stats.m

 function [mean_norm, stdd] = rcnn_feature_stats(imdb, layer, rcnn_model)
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
 
 conf = rcnn_config('sub_dir', imdb.name);
 save_file = sprintf('%s/feature_stats_%s_layer_%d_%s.mat', ...

rcnn_features.m

 function feat = rcnn_features(im, boxes, rcnn_model)
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
 
 % make sure that caffe has been initialized for this model
 if rcnn_model.cnn.init_key ~= caffe('get_init_key')

rcnn_im_crop.m

 function window = rcnn_im_crop(im, bbox, crop_mode, crop_size, padding, image_mean)
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
 
 use_square = false;
 if strcmp(crop_mode, 'square')

rcnn_load_cached_pool5_features.m

 function d = rcnn_load_cached_pool5_features(cache_name, imdb_name, id)
 % loads feat_cache/[cache_name]/[split]/[id].mat
 
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
+
+
 file = sprintf('./feat_cache/%s/%s/%s', cache_name, imdb_name, id);
 
 if exist([file '.mat'], 'file')

rcnn_load_model.m

 function rcnn_model = rcnn_load_model(rcnn_model_or_file, use_gpu)
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
 
 if isstr(rcnn_model_or_file)
   assert(exist(rcnn_model_or_file, 'file') ~= 0);

rcnn_pool5_to_fcX.m

 function feat = rcnn_pool5_to_fcX(feat, layer, rcnn_model)
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
 
 % no-op for layer <= 5
 if layer > 5

rcnn_test.m

 function res = rcnn_test(rcnn_model, imdb, suffix)
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
 
 conf = rcnn_config('sub_dir', imdb.name);
 image_ids = imdb.image_ids;

selective_search/op_selective_search_boxes.m

 function result = op_selective_search_boxes(first_el, last_el, imdb)
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
 
 fast_mode = true;
 mean_num = 0;

selective_search/selective_search_boxes_batch.m

 function [images, boxes] = selective_search_boxes_batch(imdb)
+% AUTORIGHTS
+% ---------------------------------------------------------
+% Copyright (c) 2014, Ross Girshick
+% 
+% This file is part of the R-CNN code and is available 
+% under the terms of the Simplified BSD License provided in 
+% LICENSE. Please retain this notice and LICENSE if you use 
+% this file (or any portion of it) in your project.
+% ---------------------------------------------------------
 
 fast_mode = true;