Merge branch 'master' into DeepCrowd

* master:
  [docs] switch lmdb url for manual install, tweak formatting
  Fix: libm.* doesn not exist
  Check if CPU_ONLY is set when determining CUDA version
  Downgrade Pillow pip requirement
  Add note in example about installing scikit-learn
  Remove scikit-learn dependency

Makefile

@@ -232,13 +232,15 @@ endif
 # libstdc++ for NVCC compatibility on OS X >= 10.9 with CUDA < 7.0
 ifeq ($(OSX), 1)
 	CXX := /usr/bin/clang++
-	CUDA_VERSION := $(shell $(CUDA_DIR)/bin/nvcc -V | grep -o 'release \d' | grep -o '\d')
-	ifeq ($(shell echo $(CUDA_VERSION) \< 7.0 | bc), 1)
-		CXXFLAGS += -stdlib=libstdc++
-		LINKFLAGS += -stdlib=libstdc++
+	ifneq ($(CPU_ONLY), 1)
+		CUDA_VERSION := $(shell $(CUDA_DIR)/bin/nvcc -V | grep -o 'release \d' | grep -o '\d')
+		ifeq ($(shell echo $(CUDA_VERSION) \< 7.0 | bc), 1)
+			CXXFLAGS += -stdlib=libstdc++
+			LINKFLAGS += -stdlib=libstdc++
+		endif
+		# clang throws this warning for cuda headers
+		WARNINGS += -Wno-unneeded-internal-declaration
 	endif
-	# clang throws this warning for cuda headers
-	WARNINGS += -Wno-unneeded-internal-declaration
 	# gtest needs to use its own tuple to not conflict with clang
 	COMMON_FLAGS += -DGTEST_USE_OWN_TR1_TUPLE=1
 	# boost::thread is called boost_thread-mt to mark multithreading on OS X

docs/install_apt.md

@@ -8,12 +8,24 @@ title: Installation: Ubuntu
 
     sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev libhdf5-serial-dev
 
+**CUDA**: Install via the NVIDIA package instead of `apt-get` to be certain of the library and driver versions.
+Install the library and latest driver separately; the driver bundled with the library is usually out-of-date.
+This can be skipped for CPU-only installation.
+
+**BLAS**: install ATLAS by `sudo apt-get install libatlas-base-dev` or install OpenBLAS or MKL for better CPU performance.
+
+**Python** (optional): if you use the default Python you will need to `sudo apt-get install` the `python-dev` package to have the Python headers for building the pycaffe interface.
+
 **Remaining dependencies, 14.04**
 
+Everything is packaged in 14.04.
+
     sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev protobuf-compiler
 
 **Remaining dependencies, 12.04**
 
+These dependencies need manual installation in 12.04.
+
     # glog
     wget https://google-glog.googlecode.com/files/glog-0.3.3.tar.gz
     tar zxvf glog-0.3.3.tar.gz
@@ -28,17 +40,10 @@ title: Installation: Ubuntu
     export CXXFLAGS="-fPIC" && cmake .. && make VERBOSE=1
     make && make install
     # lmdb
-    git clone git://gitorious.org/mdb/mdb.git
+    git clone https://gitorious.org/mdb/mdb.git
     cd mdb/libraries/liblmdb
     make && make install
 
 Note that glog does not compile with the most recent gflags version (2.1), so before that is resolved you will need to build with glog first.
 
-**CUDA**: Install via the NVIDIA package instead of `apt-get` to be certain of the library and driver versions.
-Install the library and latest driver separately; the driver bundled with the library is usually out-of-date.
-
-**BLAS**: install ATLAS by `sudo apt-get install libatlas-base-dev` or install OpenBLAS or MKL for better CPU performance.
-
-**Python** (optional): if you use the default Python you will need to `sudo apt-get install` the `python-dev` package to have the Python headers for building the pycaffe interface.
-
 Continue with [compilation](installation.html#compilation).

examples/hdf5_classification.ipynb

@@ -40,6 +40,7 @@
       "import shutil\n",
       "import tempfile\n",
       "\n",
+      "# You may need to 'pip install scikit-learn'\n",
       "import sklearn\n",
       "import sklearn.datasets\n",
       "import sklearn.linear_model"
@@ -1070,4 +1071,4 @@
    "metadata": {}
   }
  ]
-}
+}

python/requirements.txt

@@ -2,7 +2,6 @@ Cython>=0.19.2
 numpy>=1.7.1
 scipy>=0.13.2
 scikit-image>=0.9.3
-scikit-learn>=0.14.1
 matplotlib>=1.3.1
 ipython>=1.1.0
 h5py>=2.2.0
@@ -14,4 +13,4 @@ python-dateutil>=1.4,<2
 protobuf>=2.5.0
 python-gflags>=2.0
 pyyaml>=3.10
-Pillow>=2.7.0
+Pillow>=2.3.0

scripts/travis/travis_install.sh

@@ -67,4 +67,3 @@ export PATH=/home/travis/miniconda/bin:$PATH
 conda update --yes conda
 conda install --yes numpy scipy matplotlib scikit-image pip
 pip install protobuf
-rm /home/travis/miniconda/lib/libm.*