Initial import

4 files changed, 469 insertions, 0 deletions

diff --git a/.SRCINFO b/.SRCINFO
new file mode 100644
index 000000000000..72a302b50191
--- /dev/null
+++ b/.SRCINFO
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+pkgbase = caffe-git
+	pkgdesc = A fast framework for deep learning built in C++ for speed with a Python 2 interface
+	pkgver = r3035.543afd3
+	pkgrel = 2
+	url = https://github.com/BVLC/caffe
+	arch = x86_64
+	license = custom
+	makedepends = git
+	makedepends = python2-setuptools
+	makedepends = gcc-fortran
+	depends = cuda
+	depends = opencv
+	depends = openblas-lapack
+	depends = google-glog
+	depends = gflags
+	depends = liblmdb
+	depends = cython2
+	depends = ipython2
+	depends = python2-pillow
+	depends = python2-numpy
+	depends = python2-yaml
+	depends = python2-numpy
+	depends = python2-scipy
+	depends = python2-scikit-image
+	depends = python2-scikit-learn
+	depends = python2-matplotlib
+	depends = python2-h5py
+	depends = python2-leveldb-svn
+	depends = python2-networkx
+	depends = python2-nose
+	depends = python2-pandas
+	depends = python2-dateutil
+	depends = python2-protobuf
+	depends = python2-gflags
+	depends = python2-pandas
+	depends = boost
+	depends = boost-libs
+	depends = bc
+	provides = caffe
+	provides = pycaffe
+	provides = python2-pycaffe
+	conflicts = caffe
+	conflicts = pycaffe
+	conflicts = python2-pycaffe
+	conflicts = pycaffe-git
+	conflicts = python2-pycaffe-git
+	source = git+https://github.com/BVLC/caffe.git
+	source = classify-print-results.py
+	source = Makefile.config
+	sha256sums = SKIP
+	sha256sums = SKIP
+	sha256sums = SKIP
+
+pkgname = caffe-git
+
diff --git a/Makefile.config b/Makefile.config
new file mode 100644
index 000000000000..0cdacbf20d88
--- /dev/null
+++ b/Makefile.config
@@ -0,0 +1,76 @@
+## Refer to http://caffe.berkeleyvision.org/installation.html
+# Contributions simplifying and improving our build system are welcome!
+
+# cuDNN acceleration switch (uncomment to build with cuDNN).
+# USE_CUDNN := 1
+
+# CPU-only switch (uncomment to build without GPU support).
+# CPU_ONLY := 1
+
+# 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++
+# CUSTOM_CXX := g++
+
+# CUDA directory contains bin/ and lib/ directories that we need.
+CUDA_DIR := /opt/cuda
+# On Ubuntu 14.04, if cuda tools are installed via
+# "sudo apt-get install nvidia-cuda-toolkit" then use this instead:
+# CUDA_DIR := /usr
+
+# CUDA architecture setting: going with all of them.
+# For CUDA < 6.0, comment the *_50 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 \
+		-gencode arch=compute_35,code=sm_35 \
+		-gencode arch=compute_50,code=sm_50 \
+		-gencode arch=compute_50,code=compute_50
+
+# BLAS choice:
+# atlas for ATLAS (default)
+# mkl for MKL
+# open for OpenBlas
+BLAS := open
+# Custom (MKL/ATLAS/OpenBLAS) include and lib directories.
+# Leave commented to accept the defaults for your choice of BLAS
+# (which should work)!
+# BLAS_INCLUDE := /path/to/your/blas
+# BLAS_LIB := /path/to/your/blas
+
+# This is required only if you will compile the matlab interface.
+# MATLAB directory should contain the mex binary in /bin.
+# MATLAB_DIR := /usr/local
+# MATLAB_DIR := /Applications/MATLAB_R2012b.app
+
+# 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 \
+		/usr/lib/python2.7/site-packages/numpy/core/include
+# Anaconda Python distribution is quite popular. Include path:
+# PYTHON_INCLUDE := $(HOME)/anaconda/include \
+		# $(HOME)/anaconda/include/python2.7 \
+		# $(HOME)/anaconda/lib/python2.7/site-packages/numpy/core/include
+
+# We need to be able to find libpythonX.X.so or .dylib.
+PYTHON_LIB := /usr/lib
+# PYTHON_LIB := $(HOME)/anaconda/lib
+
+# Uncomment to support layers written in Python (will link against Python libs)
+WITH_PYTHON_LAYER := 1
+
+# Whatever else you find you need goes here.
+INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/include
+LIBRARY_DIRS := $(PYTHON_LIB) /usr/lib
+
+BUILD_DIR := build
+DISTRIBUTE_DIR := distribute
+
+# Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171
+# DEBUG := 1
+
+# The ID of the GPU that 'make runtest' will use to run unit tests.
+TEST_GPUID := 0
+
+# enable pretty build (comment to see full commands)
+Q ?= @
+
diff --git a/PKGBUILD b/PKGBUILD
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index 000000000000..6cfc068d7443
--- /dev/null
+++ b/PKGBUILD
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+# Maintainer:  jyantis <yantis@yantis.net>
+
+pkgname=caffe-git
+pkgver=r3035.543afd3
+pkgrel=2
+pkgdesc='A fast framework for deep learning built in C++ for speed with a Python 2 interface'
+arch=(x86_64)
+url='https://github.com/BVLC/caffe'
+license=('custom')
+
+# if using an AWS EC2 make sure to use the community repo for cuda and not the ec2 repo. 
+depends=('cuda'
+         'opencv'
+         'openblas-lapack'
+         'google-glog'
+         'gflags'
+         'liblmdb'
+         'cython2'
+         'ipython2'
+         'python2-pillow'
+         'python2-numpy'
+         'python2-yaml'
+         'python2-numpy'
+         'python2-scipy'
+         'python2-scikit-image'
+         'python2-scikit-learn'
+         'python2-matplotlib'
+         'python2-h5py'
+         'python2-leveldb-svn'
+         'python2-networkx'
+         'python2-nose'
+         'python2-pandas'
+         'python2-dateutil'
+         'python2-protobuf'
+         'python2-gflags'
+         'python2-pandas'
+         'boost'
+         'boost-libs'
+         'bc'
+        )
+
+source=('git+https://github.com/BVLC/caffe.git'
+        'classify-print-results.py'
+        'Makefile.config')
+makedepends=('git' 'python2-setuptools' 'gcc-fortran')
+provides=('caffe' 'pycaffe' 'python2-pycaffe' )
+conflicts=('caffe' 'pycaffe' 'python2-pycaffe' 'pycaffe-git' 'python2-pycaffe-git')
+sha256sums=('SKIP'
+            'SKIP'
+            'SKIP')
+
+pkgver() {
+  cd caffe
+  set -o pipefail
+  _gitversion=$( git describe --long | sed -r 's/([^-]*-g)/r\1/;s/-/./g' ||
+  printf "r%s.%s" "$(git rev-list --count HEAD)" "$(git rev-parse --short HEAD)" )
+  printf "%s" $_gitversion
+}
+
+build() {
+  # You can modify this file and do some stuff like turn off using the GPU etc
+  cp Makefile.config caffe
+
+  # Modified classify.py for testing that will output results
+  cp classify-print-results.py caffe/python/
+
+  cd caffe
+
+  # Patch any #!/usr/bin/python to #!/usr/bin/python2
+  for file in $(find . -name '*.py' -print); do
+    sed -r -i 's_^#!.*/usr/bin/python(\s|$)_#!/usr/bin/python2_' $file
+    sed -r -i 's_^#!.*/usr/bin/env(\s)*python(\s|$)_#!/usr/bin/env python2_' $file
+  done
+ # Do the same for python examples
+  for file in $(find . -name '*.py.example' -print); do
+    sed -r -i 's_^#!.*/usr/bin/python(\s|$)_#!/usr/bin/python2_' $file
+    sed -r -i 's_^#!.*/usr/bin/env(\s)*python(\s|$)_#!/usr/bin/env python2_' $file
+  done
+
+  # If the user has colormake installed then use that instead of make.
+  if hash colormake 2>/dev/null; then
+    colormake all
+    colormake pycaffe
+  else
+    make all
+    make pycaffe
+  fi
+
+  msg "Downloading the ImageNet Caffe model and labels" 
+  python2 scripts/download_model_binary.py models/bvlc_reference_caffenet # 232 MB
+  sh data/ilsvrc12/get_ilsvrc_aux.sh # 17 MB
+
+  msg "Downloading the mnist data"
+  sh data/mnist/get_mnist.sh #10 MB
+}
+
+# check() {
+#   cd caffe
+
+#   # Unrem these next two lines to run the 838 tests
+#   # make test
+#   # make runtest
+
+#   # A simple test to make sure its working (Attempt to classify a picture of a cat)
+#   # Expected result: [('tabby', '0.27933'), ('tiger cat', '0.21915'), ('Egyptian cat', '0.16064'), ('lynx', '0.12844'), ('kit fox', '0.05155')]
+#   python2 python/classify-print-results.py --print_results examples/images/cat.jpg foo
+#   msg "Tested that everything works.. you should see some cat type classifiations above this message"
+# }
+
+package() {
+  cd caffe
+
+  # We don't need anything related to git in the package
+  rm -rf .git*
+
+  # Setup Python by hand since no setup.py 
+  mkdir -p $pkgdir/usr/lib/python2.7/site-packages/caffe/
+  cp -R python/caffe/* $pkgdir/usr/lib/python2.7/site-packages/caffe/
+
+  # Add missing __init__.py file to ensure that the modules are detected.
+  find "$pkgdir/usr/lib/python2.7/site-packages/caffe" -type d -exec touch '{}'/__init__.py \;
+
+  # Still leaving a copy of the python code in the main caffe directory since it might be useful for some
+  # Though because of that namcap will give this error:
+  # caffe-git E: ELF file ('opt/caffe/python/caffe/_caffe.so') outside of a valid path.
+
+  # Install shared libraries
+  mkdir -p $pkgdir/usr/lib/
+  install -Dm644 .build_release/lib/* "${pkgdir}/usr/lib/"
+
+  ### Install all the execulables ###
+  mkdir -p $pkgdir/usr/bin/
+
+  # Primary executable
+  install -D -m755 .build_release/tools/caffe.bin "$pkgdir/usr/bin/caffe"
+
+  # Conversion executables 
+  install -D -m755 .build_release/examples/cifar10/convert_cifar_data.bin "$pkgdir/usr/bin/convert_cifar_data"
+  install -D -m755 .build_release/examples/mnist/convert_mnist_data.bin "$pkgdir/usr/bin/convert_mnist_data"
+  install -D -m755 .build_release/examples/siamese/convert_mnist_siamese_data.bin "$pkgdir/usr/bin/convert_mnist_siamese_data"
+
+  # Depreciated executables. All in caffe executable now but included here for backwards compatiblity
+  install -D -m755 .build_release/tools/finetune_net.bin "$pkgdir/usr/bin/finetune_net"
+  install -D -m755 .build_release/tools/train_net.bin "$pkgdir/usr/bin/train_net"
+  install -D -m755 .build_release/tools/device_query.bin "$pkgdir/usr/bin/device_query"
+  install -D -m755 .build_release/tools/net_speed_benchmark.bin "$pkgdir/usr/bin/net_speed_benchmark"
+  install -D -m755 .build_release/tools/compute_image_mean.bin "$pkgdir/usr/bin/compute_image_mean"
+  install -D -m755 .build_release/tools/convert_imageset.bin "$pkgdir/usr/bin/convert_imageset"
+  install -D -m755 .build_release/tools/test_net.bin "$pkgdir/usr/bin/test_net"
+  install -D -m755 .build_release/tools/upgrade_net_proto_text.bin "$pkgdir/usr/bin/upgrade_net_proto_text"
+  # install -D -m755 .build_release/tools/dump_network.bin "$pkgdir/usr/bin/dump_network"
+  install -D -m755 .build_release/tools/extract_features.bin "$pkgdir/usr/bin/extract_features"
+
+  # clean up before copying over
+  rm -r .build_release
+  rm -r build
+
+  mkdir -p $pkgdir/opt/caffe
+  cp -r . $pkgdir/opt/caffe
+
+  # Install BSD2 License (not in common licenses so lets make it custom)
+  install -D -m644 LICENSE "${pkgdir}/usr/share/licenses/${pkgname}/LICENSE"
+
+  # Install Documentation
+  install -D -m644 README.md "${pkgdir}/usr/share/doc/${pkgname}/README.md"
+}
+
+# vim:set ts=2 sw=2 et:
diff --git a/classify-print-results.py b/classify-print-results.py
new file mode 100755
index 000000000000..e356c94f653c
--- /dev/null
+++ b/classify-print-results.py
@@ -0,0 +1,170 @@
+#!/usr/bin/env python2
+"""
+classify.py is an out-of-the-box image classifer callable from the command line.
+
+By default it configures and runs the Caffe reference ImageNet model.
+"""
+import numpy as np
+import os
+import sys
+import argparse
+import glob
+import time
+import pandas as pd
+import caffe
+
+
+def main(argv):
+    pycaffe_dir = os.path.dirname(__file__)
+
+    parser = argparse.ArgumentParser()
+    # Required arguments: input and output files.
+    parser.add_argument(
+        "input_file",
+        help="Input image, directory, or npy."
+    )
+    parser.add_argument(
+        "output_file",
+        help="Output npy filename."
+    )
+    # Optional arguments.
+    parser.add_argument(
+        "--model_def",
+        default=os.path.join(pycaffe_dir,
+                             "../models/bvlc_reference_caffenet/deploy.prototxt"),
+        help="Model definition file."
+    )
+    parser.add_argument(
+        "--pretrained_model",
+        default=os.path.join(
+            pycaffe_dir,
+            "../models/bvlc_reference_caffenet/bvlc_reference_caffenet.caffemodel"),
+        help="Trained model weights file.")
+
+    # parser.add_argument(
+    #     "--gpu",
+    #     action='store_true',
+    #     help="Switch for gpu computation."
+    # )
+
+    parser.add_argument(
+        "--center_only",
+        action='store_true',
+        help="Switch for prediction from center crop alone instead of " +
+             "averaging predictions across crops (default)."
+    )
+    parser.add_argument(
+        "--images_dim",
+        default='256,256',
+        help="Canonical 'height,width' dimensions of input images."
+    )
+    parser.add_argument(
+        "--mean_file",
+        default=os.path.join(pycaffe_dir,
+                             'caffe/imagenet/ilsvrc_2012_mean.npy'),
+        help="Data set image mean of H x W x K dimensions (numpy array). " +
+             "Set to '' for no mean subtraction."
+    )
+    parser.add_argument(
+        "--input_scale",
+        type=float,
+        help="Multiply input features by this scale to finish preprocessing."
+    )
+    parser.add_argument(
+        "--raw_scale",
+        type=float,
+        default=255.0,
+        help="Multiply raw input by this scale before preprocessing."
+    )
+    parser.add_argument(
+        "--channel_swap",
+        default='2,1,0',
+        help="Order to permute input channels. The default converts " +
+             "RGB -> BGR since BGR is the Caffe default by way of OpenCV."
+    )
+    parser.add_argument(
+        "--ext",
+        default='jpg',
+        help="Image file extension to take as input when a directory " +
+             "is given as the input file."
+    )
+    parser.add_argument(
+        "--labels_file",
+        default=os.path.join(pycaffe_dir,
+                             "../data/ilsvrc12/synset_words.txt"),
+        help="Readable label definition file."
+    )
+    parser.add_argument(
+        "--print_results",
+        action='store_true',
+        help="Write output text to stdout rather than serializing to a file."
+    )
+
+    args = parser.parse_args()
+
+    image_dims = [int(s) for s in args.images_dim.split(',')]
+
+    mean, channel_swap = None, None
+    if args.mean_file:
+        mean = np.load(args.mean_file)
+    if args.channel_swap:
+        channel_swap = [int(s) for s in args.channel_swap.split(',')]
+
+    # Make classifier.
+
+    classifier = caffe.Classifier(args.model_def, args.pretrained_model,
+                                  image_dims=image_dims, mean=mean,
+                                  input_scale=args.input_scale, raw_scale=args.raw_scale,
+                                  channel_swap=channel_swap)
+    # # Make classifier.
+    # classifier = caffe.Classifier(args.model_def, args.pretrained_model,
+    #                               image_dims=image_dims, gpu=args.gpu, mean=mean,
+    #                               input_scale=args.input_scale, raw_scale=args.raw_scale,
+    #                               channel_swap=channel_swap)
+
+    # if args.gpu:
+    #     print 'GPU mode'
+
+    # Load numpy array (.npy), directory glob (*.jpg), or image file.
+    args.input_file = os.path.expanduser(args.input_file)
+    if args.input_file.endswith('npy'):
+        inputs = np.load(args.input_file)
+    elif os.path.isdir(args.input_file):
+        inputs = [caffe.io.load_image(im_f)
+                  for im_f in glob.glob(args.input_file + '/*.' + args.ext)]
+    else:
+        inputs = [caffe.io.load_image(args.input_file)]
+
+    print "Classifying %d inputs." % len(inputs)
+
+    # Classify.
+    start = time.time()
+    scores = classifier.predict(inputs, not args.center_only).flatten()
+    print "Done in %.2f s." % (time.time() - start)
+
+    if args.print_results:
+        with open(args.labels_file) as f:
+            labels_df = pd.DataFrame([
+                {
+                    'synset_id': l.strip().split(' ')[0],
+                    'name': ' '.join(l.strip().split(' ')[1:]).split(',')[0]
+                }
+                for l in f.readlines()
+            ])
+        labels = labels_df.sort('synset_id')['name'].values
+
+        indices = (-scores).argsort()[:5]
+        predictions = labels[indices]
+
+        meta = [
+            (p, '%.5f' % scores[i])
+            for i, p in zip(indices, predictions)
+        ]
+
+        print meta
+
+    # Save
+    np.save(args.output_file, scores)
+
+if __name__ == '__main__':
+    main(sys.argv)