conda, caffe

conda create -n caffe2.7
conda activate caffe2.7

然後安裝下面 package..

python=2.7
numpy
matplotlib
scikit-image
pyyaml
protobuf

額外安裝 jupyter

測試結果裝了 protobuf 的話，會是 libprotobuf.so.2，make OK，但是 執行 .build_release/tools/caffe 會出現找不到 libprotobuf.so.2 的 Error
用 export LD_LIBRARY_PATH=... 之後就可以 run
但是不安裝，用系統的 libprotobuf.so.1 就可以。

在 python 中 import caffe 時，如果沒有 conda install protobuf，不會用系統的 libprotobuf.so.1。
所以還是要安裝。

安裝完後，build runtest OK, 然後修改 Make.config.example, rename 成 Make.config

@@ -2,7 +2,7 @@
 # Contributions simplifying and improving our build system are welcome!

 # cuDNN acceleration switch (uncomment to build with cuDNN).
-# USE_CUDNN := 1
+USE_CUDNN := 1

 # CPU-only switch (uncomment to build without GPU support).
 # CPU_ONLY := 1
@@ -20,7 +20,7 @@
 # ALLOW_LMDB_NOLOCK := 1

 # Uncomment if you're using OpenCV 3
-# OPENCV_VERSION := 3
+OPENCV_VERSION := 3

 # To customize your choice of compiler, uncomment and set the following.
 # N.B. the default for Linux is g++ and the default for OSX is clang++
@@ -36,9 +36,7 @@
 # For CUDA < 6.0, comment the *_50 through *_61 lines for compatibility.
 # For CUDA < 8.0, comment the *_60 and *_61 lines for compatibility.
 # For CUDA >= 9.0, comment the *_20 and *_21 lines for compatibility.
-CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \
-               -gencode arch=compute_20,code=sm_21 \
-               -gencode arch=compute_30,code=sm_30 \
+CUDA_ARCH := -gencode arch=compute_30,code=sm_30 \
                -gencode arch=compute_35,code=sm_35 \
                -gencode arch=compute_50,code=sm_50 \
                -gencode arch=compute_52,code=sm_52 \
@@ -68,34 +66,34 @@

 # NOTE: this is required only if you will compile the python interface.
 # We need to be able to find Python.h and numpy/arrayobject.h.
-PYTHON_INCLUDE := /usr/include/python2.7 \
+#PYTHON_INCLUDE := /usr/include/python2.7 \
                /usr/lib/python2.7/dist-packages/numpy/core/include
                                                                                                                                 16,1          
 # Anaconda Python distribution is quite popular. Include path:
 # Verify anaconda location, sometimes it's in root.
-# ANACONDA_HOME := $(HOME)/anaconda
-# PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
-               # $(ANACONDA_HOME)/include/python2.7 \
-               # $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include
+ANACONDA_HOME := $(HOME)/miniconda3/envs/caffe2.7
+PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
+                $(ANACONDA_HOME)/include/python2.7 \
+                $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include

 # Uncomment to use Python 3 (default is Python 2)
-# PYTHON_LIBRARIES := boost_python3 python3.5m
-# PYTHON_INCLUDE := /usr/include/python3.5m \
-#                 /usr/lib/python3.5/dist-packages/numpy/core/include
+#PYTHON_LIBRARIES := boost_python3 python3.6m
+#PYTHON_INCLUDE := /usr/include/python3.6m \
+                 /usr/lib/python3.6/dist-packages/numpy/core/include

 # We need to be able to find libpythonX.X.so or .dylib.
-PYTHON_LIB := /usr/lib
-# PYTHON_LIB := $(ANACONDA_HOME)/lib
+#PYTHON_LIB := /usr/lib
+PYTHON_LIB := $(ANACONDA_HOME)/lib

 # Homebrew installs numpy in a non standard path (keg only)
 # PYTHON_INCLUDE += $(dir $(shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include
 # PYTHON_LIB += $(shell brew --prefix numpy)/lib

 # Uncomment to support layers written in Python (will link against Python libs)
-# WITH_PYTHON_LAYER := 1
+WITH_PYTHON_LAYER := 1

 # Whatever else you find you need goes here.
-INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
-LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib
+INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/
+LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu/hdf5/serial

 # If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies
 # INCLUDE_DIRS += $(shell brew --prefix)/include
@@ -107,7 +105,7 @@

 # Uncomment to use `pkg-config` to specify OpenCV library paths.
 # (Usually not necessary -- OpenCV libraries are normally installed in one of the above $LIBRARY_DIRS.)
-# USE_PKG_CONFIG := 1
+USE_PKG_CONFIG := 1

 # N.B. both build and distribute dirs are cleared on `make clean`
 BUILD_DIR := build

..原來 的 example 就有考慮到 conda environment 的環境，所以要修改 ANACONDA_PATH (雖然使用 miniconda)