cpplint

diff --git a/src/caffe/blob.cpp b/src/caffe/blob.cpp
index 8260fe0..40ee548 100644 (file)
--- a/src/caffe/blob.cpp
+++ b/src/caffe/blob.cpp
@@ -24,8 +24,8 @@ void Blob<Dtype>::Reshape(const int num, const int channels, const int height,
     data_.reset(new SyncedMemory(count_ * sizeof(Dtype)));
     diff_.reset(new SyncedMemory(count_ * sizeof(Dtype)));
   } else {
-    data_.reset((SyncedMemory*)NULL);
-    diff_.reset((SyncedMemory*)NULL);
+    data_.reset(reinterpret_cast<SyncedMemory*>(NULL));
+    diff_.reset(reinterpret_cast<SyncedMemory*>(NULL));
   }
 }
 

diff --git a/src/caffe/caffe.hpp b/src/caffe/caffe.hpp
index 5a813f8..800138f 100644 (file)
--- a/src/caffe/caffe.hpp
+++ b/src/caffe/caffe.hpp
@@ -13,4 +13,4 @@
 
 #include "caffe/proto/caffe.pb.h"
 
-#endif  // CAFFE_CAFFE_HPP_
\ No newline at end of file
+#endif  // CAFFE_CAFFE_HPP_

diff --git a/src/caffe/common.cpp b/src/caffe/common.cpp
index 04124bf..6c366b4 100644 (file)
--- a/src/caffe/common.cpp
+++ b/src/caffe/common.cpp
@@ -68,7 +68,7 @@ void Caffe::set_random_seed(const unsigned int seed) {
   CURAND_CHECK(curandCreateGenerator(&Get().curand_generator_,
       CURAND_RNG_PSEUDO_DEFAULT));
   CURAND_CHECK(curandSetPseudoRandomGeneratorSeed(curand_generator(),
-      (unsigned long long)seed));
+      seed));
   // VSL seed
   VSL_CHECK(vslDeleteStream(&(Get().vsl_stream_)));
   VSL_CHECK(vslNewStream(&(Get().vsl_stream_), VSL_BRNG_MT19937, seed));

diff --git a/src/caffe/common.hpp b/src/caffe/common.hpp
index 18c5b41..c87db01 100644 (file)
--- a/src/caffe/common.hpp
+++ b/src/caffe/common.hpp
@@ -23,7 +23,7 @@
   }
 
 #define DISABLE_COPY_AND_ASSIGN(classname) \
- private:\
+private:\
   classname(const classname&);\
   classname& operator=(const classname&)
 

diff --git a/src/caffe/filler.hpp b/src/caffe/filler.hpp
index ffe7a50..99cb5bc 100644 (file)
--- a/src/caffe/filler.hpp
+++ b/src/caffe/filler.hpp
@@ -118,7 +118,7 @@ class XavierFiller : public Filler<Dtype> {
     int fan_in = blob->width();
     Dtype scale = sqrt(Dtype(3) / fan_in);
     caffe_vRngUniform<Dtype>(blob->count(), blob->mutable_cpu_data(),
-        -scale, scale);    
+        -scale, scale);
   }
 };
 

diff --git a/src/caffe/layers/data_layer.cpp b/src/caffe/layers/data_layer.cpp
index c4bb8cc..5786a0b 100644 (file)
--- a/src/caffe/layers/data_layer.cpp
+++ b/src/caffe/layers/data_layer.cpp
@@ -1,11 +1,11 @@
 // Copyright 2013 Yangqing Jia
 
 #include <stdint.h>
+#include <leveldb/db.h>
+
 #include <string>
 #include <vector>
 
-#include <leveldb/db.h>
-
 #include "caffe/layer.hpp"
 #include "caffe/vision_layers.hpp"
 

diff --git a/src/caffe/layers/inner_product_layer.cpp b/src/caffe/layers/inner_product_layer.cpp
index e5e8e52..e6f77ae 100644 (file)
--- a/src/caffe/layers/inner_product_layer.cpp
+++ b/src/caffe/layers/inner_product_layer.cpp
@@ -1,10 +1,11 @@
 // Copyright 2013 Yangqing Jia
 
-#include <vector>
 
 #include <mkl.h>
 #include <cublas_v2.h>
 
+#include <vector>
+
 #include "caffe/blob.hpp"
 #include "caffe/common.hpp"
 #include "caffe/filler.hpp"
@@ -44,7 +45,8 @@ void InnerProductLayer<Dtype>::SetUp(const vector<Blob<Dtype>*>& bottom,
         GetFiller<Dtype>(this->layer_param_.bias_filler()));
     bias_filler->Fill(this->blobs_[1].get());
     bias_multiplier_.reset(new SyncedMemory(M_ * sizeof(Dtype)));
-    Dtype* bias_multiplier_data = (Dtype*)bias_multiplier_->mutable_cpu_data();
+    Dtype* bias_multiplier_data =
+        reinterpret_cast<Dtype*>(bias_multiplier_->mutable_cpu_data());
     for (int i = 0; i < M_; ++i) {
         bias_multiplier_data[i] = 1.;
     }

diff --git a/src/caffe/layers/softmax_layer.cpp b/src/caffe/layers/softmax_layer.cpp
index 7e8bbd1..a263ad3 100644 (file)
--- a/src/caffe/layers/softmax_layer.cpp
+++ b/src/caffe/layers/softmax_layer.cpp
@@ -1,6 +1,7 @@
 // Copyright 2013 Yangqing Jia
 
 #include <algorithm>
+#include <vector>
 
 #include "caffe/layer.hpp"
 #include "caffe/vision_layers.hpp"
@@ -82,7 +83,7 @@ Dtype SoftmaxLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top,
   return Dtype(0);
 }
 
-// TODO: implement the GPU version of softmax.
+// TODO(Yangqing): implement the GPU version of softmax.
 
 INSTANTIATE_CLASS(SoftmaxLayer);
 

diff --git a/src/caffe/util/io.cpp b/src/caffe/util/io.cpp
index 929fdd6..d827176 100644 (file)
--- a/src/caffe/util/io.cpp
+++ b/src/caffe/util/io.cpp
@@ -1,33 +1,38 @@
+// Copyright 2013 Yangqing Jia
+
 #include <stdint.h>
-#include <string>
 #include <opencv2/core/core.hpp>
 #include <opencv2/highgui/highgui.hpp>
 
+#include <algorithm>
+#include <string>
+
 #include "caffe/common.hpp"
 #include "caffe/util/io.hpp"
 #include "caffe/proto/caffe.pb.h"
 
 using cv::Mat;
 using cv::Vec3b;
+using std::max;
 using std::string;
 
 namespace caffe {
 
 void ReadImageToProto(const string& filename, BlobProto* proto) {
-  Mat cv_image;
-  cv_image = cv::imread(filename, CV_LOAD_IMAGE_COLOR);
-  CHECK(cv_image.data) << "Could not open or find the image.";
-  DCHECK_EQ(cv_image.channels(), 3);
+  Mat cv_img;
+  cv_img = cv::imread(filename, CV_LOAD_IMAGE_COLOR);
+  CHECK(cv_img.data) << "Could not open or find the image.";
+  DCHECK_EQ(cv_img.channels(), 3);
   proto->set_num(1);
   proto->set_channels(3);
-  proto->set_height(cv_image.rows);
-  proto->set_width(cv_image.cols);
+  proto->set_height(cv_img.rows);
+  proto->set_width(cv_img.cols);
   proto->clear_data();
   proto->clear_diff();
   for (int c = 0; c < 3; ++c) {
-    for (int h = 0; h < cv_image.rows; ++h) {
-      for (int w = 0; w < cv_image.cols; ++w) {
-        proto->add_data(float(cv_image.at<Vec3b>(h, w)[c]) / 255.);
+    for (int h = 0; h < cv_img.rows; ++h) {
+      for (int w = 0; w < cv_img.cols; ++w) {
+        proto->add_data(static_cast<float>(cv_img.at<Vec3b>(h, w)[c]) / 255.);
       }
     }
   }
@@ -35,21 +40,21 @@ void ReadImageToProto(const string& filename, BlobProto* proto) {
 
 void WriteProtoToImage(const string& filename, const BlobProto& proto) {
   CHECK_EQ(proto.num(), 1);
-  CHECK_EQ(proto.channels(), 3);
+  CHECK(proto.channels() == 3 || proto.channels() == 1);
   CHECK_GT(proto.height(), 0);
   CHECK_GT(proto.width(), 0);
-  Mat cv_image(proto.height(), proto.width(), CV_8UC3);
-  // TODO: copy the blob data to image.
+  Mat cv_img(proto.height(), proto.width(), CV_8UC3);
   for (int c = 0; c < 3; ++c) {
-    for (int h = 0; h < cv_image.rows; ++h) {
-      for (int w = 0; w < cv_image.cols; ++w) {
-        cv_image.at<Vec3b>(h, w)[c] =
-            uint8_t(proto.data((c * cv_image.rows + h) * cv_image.cols + w)
+    int source_c = max(c, proto.channels() - 1);
+    for (int h = 0; h < cv_img.rows; ++h) {
+      for (int w = 0; w < cv_img.cols; ++w) {
+        cv_img.at<Vec3b>(h, w)[c] =
+            uint8_t(proto.data((source_c * cv_img.rows + h) * cv_img.cols + w)
                 * 255.);
       }
     }
   }
-  CHECK(cv::imwrite(filename, cv_image));
+  CHECK(cv::imwrite(filename, cv_img));
 }
 
 

diff --git a/src/caffe/util/io.hpp b/src/caffe/util/io.hpp
index c3917c3..f55de8a 100644 (file)
--- a/src/caffe/util/io.hpp
+++ b/src/caffe/util/io.hpp
@@ -1,3 +1,5 @@
+// Copyright Yangqing Jia 2013
+
 #ifndef CAFFE_UTIL_IO_H_
 #define CAFFE_UTIL_IO_H_
 
@@ -14,4 +16,4 @@ void WriteProtoToImage(const string& filename, const BlobProto& proto);
 
 }  // namespace caffe
 
-#endif   // CAFFE_UTIL_IO_H_
\ No newline at end of file
+#endif   // CAFFE_UTIL_IO_H_

diff --git a/src/caffe/vision_layers.hpp b/src/caffe/vision_layers.hpp
index dbf278c..66eeda0 100644 (file)
--- a/src/caffe/vision_layers.hpp
+++ b/src/caffe/vision_layers.hpp
@@ -267,12 +267,12 @@ class SoftmaxLayer : public Layer<Dtype> {
  protected:
   virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom,
       vector<Blob<Dtype>*>* top);
-  //virtual void Forward_gpu(const vector<Blob<Dtype>*>& bottom,
-  //    vector<Blob<Dtype>*>* top);
+  // virtual void Forward_gpu(const vector<Blob<Dtype>*>& bottom,
+  //     vector<Blob<Dtype>*>* top);
   virtual Dtype Backward_cpu(const vector<Blob<Dtype>*>& top,
       const bool propagate_down, vector<Blob<Dtype>*>* bottom);
-  //virtual Dtype Backward_gpu(const vector<Blob<Dtype>*>& top,
-  //    const bool propagate_down, vector<Blob<Dtype>*>* bottom);
+  // virtual Dtype Backward_gpu(const vector<Blob<Dtype>*>& top,
+  //     const bool propagate_down, vector<Blob<Dtype>*>* bottom);
 
   // sum_multiplier is just used to carry out sum using blas
   Blob<Dtype> sum_multiplier_;
@@ -297,8 +297,8 @@ class MultinomialLogisticLossLayer : public Layer<Dtype> {
       vector<Blob<Dtype>*>* top) { return; }
   virtual Dtype Backward_cpu(const vector<Blob<Dtype>*>& top,
       const bool propagate_down, vector<Blob<Dtype>*>* bottom);
-  //virtual Dtype Backward_gpu(const vector<Blob<Dtype>*>& top,
-  //    const bool propagate_down, vector<Blob<Dtype>*>* bottom);
+  // virtual Dtype Backward_gpu(const vector<Blob<Dtype>*>& top,
+  //     const bool propagate_down, vector<Blob<Dtype>*>* bottom);
 };
 
 }  // namespace caffe